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CBO Costing Plans With Migrated Rows Part II (“New Killer Star”) March 28, 2023

Posted by Richard Foote in CBO, Index Access Path, Index statistics, Leaf Blocks, Migrated Rows, Non-Equality Predicates, Oracle, Oracle Blog, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Statistics, Performance Tuning, Richard's Blog, ROWID.
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I’ve spent the past few months discussing Migrated Rows, in large part thanks to an excellent 15 minute video by Connor McDonald¬†on how ROWIDs can now be updated on the fly in Oracle Autonomous databases.

Well 14 such posts later, I have finally reached the end of this topic (for now at least). So, an average of about 1 post per minute of video ūüôā

In my previous post, I discussed how the CBO costs execution plans with tables that have migrated rows, when the statistics are collected as recommended via the DBMS_STATS package. In summary, migrated rows are basically just ignored, with the CBO blissfully unaware of the existence of any such migrated rows.

As I discussed, if I want to easily see how many migrated rows I have in a table, I can potentially use the ANALYZE command as follows:

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables
     where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4906              86          415            170        56186

As you can now see, the table currently has 56186 migrated rows (yes CHAIN_CNT can potentially count rows that simply can’t fit within a single block, but all these rows are definitely migrated rows as per the demo in my previous post).

Now, it had always been my belief that although you can use the ANALYZE command to count out these migrated rows, the CBO would simply ignore this statistic in its calculations.

But I was wrong.

If we now re-run the query from the previous post:

SQL> select * from bowie where id > 1 and id < 1001;

999 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0
-------------------------------------
select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |    999 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |    999 |    999 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |    999 |    999 |00:00:00.01 |       4 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

Statistics
-----------------------------------------------------------
            1 CPU used by this session
            1 CPU used when call started
            1 DB time
         9193 RM usage
            3 Requests to/from client
            2 SQL*Net roundtrips to/from client
          664 buffer is not pinned count
         1662 buffer is pinned count
          323 bytes received via SQL*Net from client
       171333 bytes sent via SQL*Net to client
            2 calls to get snapshot scn: kcmgss
            2 calls to kcmgcs
          666 consistent gets
            1 consistent gets examination
            1 consistent gets examination (fastpath)
          666 consistent gets from cache
          665 consistent gets pin
          665 consistent gets pin (fastpath)
            2 execute count
            1 index range scans
      5455872 logical read bytes from cache
          665 no work - consistent read gets
           39 non-idle wait count
            2 opened cursors cumulative
            1 opened cursors current
            2 parse count (total)
            2 process last non-idle time
            1 session cursor cache hits
          666 session logical reads
            1 sorts (memory)
         2024 sorts (rows)
          999 table fetch by rowid
          327 table fetch continued row
            3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'b1vwpu2rgn8p5',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0
-------------------------------------

select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |   302 (100)|    999 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |    999 |   141K|   302   (0)|    999 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |    999 |       |     4   (0)|    999 |00:00:00.01 |       4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

    2 - access("ID">1 AND "ID"<1001)

 

We can see that the cost of the plan has now changed.

Although the cost of reading the index itself is still the same with a cost of 4, the overall cost of the plan has increased to 302 (previously it was 21).

So the difference in plan costs is 302 – 21 = 281. And it’s pretty easy to see where this extra comes from…

The extra costs is basically query selectivity x no of migrated rows

Extra costs = 0.005 x 56186 = 281.

So the index scan costing formula should really be updated to be:

Index Scan Cost = blevel +
                                    ceil(effective index selectivity x leaf_blocks) +
                                    ceil(effective table selectivity x clustering_factor) +
                                    ceil(effective table selectivity x chain_cnt)

Now, IMHO, this new cost is actually more accurate and better matches the true cost of now using the index, which requires 666 Consistent Gets (previously, before the rows migrated, the index plan required just 18 Consistent Gets).

So in some respects, this new cost might not be a bad thing. But then again, a sudden change in such costings due to a flood of new migrated rows might result in an unexpected and undesired plan changes that have been carefully crafted for statistics generated with the conventional DBMS_STATS collection method.

However, it’s not sufficient to simply collect fresh statistics using DBMS_STATS to get the previous CBO costings where migrated rows are ignored:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables
     where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4906              86          415            167        56186

Simply collecting fresh statistics does NOT clear out the CHAIN_CNT statistic and so the CBO costings remain the same as with ANALYZE command:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'b1vwpu2rgn8p5',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0
-------------------------------------

select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |   302 (100)|    999 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |    999 |   141K|   302   (0)|    999 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |    999 |       |     4   (0)|    999 |00:00:00.01 |       4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

You need to first delete the table statistics to remove the CHAIN_CNT statistic (which of course comes with obvious dangers now there are no table statistics present) before you collect fresh statistics using DBMS_STATS:

SQL> execute dbms_stats.delete_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables
     where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4906               0            0            167            0

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 3250

The CHAIN_CNT statistic has finally been cleared to 0 and the CBO costings now returned to as it was previously when such migrated rows were ignored:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'b1vwpu2rgn8p5',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0
-------------------------------------

select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    21 (100)|    999 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   163K|    21   (0)|    999 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |       |     4   (0)|    999 |00:00:00.01 |       4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

The CBO costs are now back to the previous 21.

So I’m a little in two minds about this. I think the statistics generated and used by the CBO are better with the ANALYZE command, but would still suggest collecting the necessary statistics using the recommended DBMS_STATS approach. Perhaps Oracle giving us the option to collect these additional statistics using DBMS_STATS might be a useful enhancement… ūü§∑‚Äć‚ôāÔłŹ

Now, at one point in time, a long long time ago, I’m reasonably sure the CBO previously didn’t use the CHAIN_CNT statistic. However, it came as no real surprise when I researched when the CBO had started using the CHAIN_CNT statistic in its calculations, that Jonathan Lewis had already written on this subject way way back in April 2009 ūüôā

So Oracle definitely had this behaviour all the way back to at least 9i and continues to behave this way in 21c. Ah well, better late than never I guess to finally realise how all this actually works…

UPDATE (29 March 2023): Jonathan Lewis can kindly confirmed with me that CHAIN_CNT was definitely ignored back in version 8.1.7.4 and that this changed to the current behaviour in either 9.0 or 9.2.

CBO Costing Plans With Migrated Rows Part I (“Ignoreland”) March 21, 2023

Posted by Richard Foote in BLEVEL, CBO, Clustering Factor, Data Clustering, Index Access Path, Index Height, Index statistics, Leaf Blocks, Migrated Rows, Non-Equality Predicates, Oracle, Oracle Blog, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Statistics, Performance Tuning, Richard's Blog, ROWID.
3 comments

Whilst recently blogging about Migrated Rows and specifically changes to how ROWIDs are now maintained on the fly in Oracle Autonomous Databases, I made a discovery regarding how the Cost-Based Optimizer (CBO) costs such plans. This is one of the key reasons why I blog, not only to try and share odd titbits about how Oracle works, but also to hopefully learn much myself in the process.

Imagine my surprise in not only learning that Oracle and the CBO works differently to how I had always thought Oracle worked in this respect, but that this behaviour has been the case since at least Oracle 9i.

In Part I, I’ll use the same example of migrated rows as I’ve used in the past few blog posts and initially show how the CBO generally costs such plans (and by which I had incorrectly assumed ALWAYS costed such plans).

Let’s start by creating and populating a tightly packed table (in an environment where ROWIDs are NOT updated on the fly):

SQL> create table bowie(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0;

Table BOWIE created.

SQL> insert into bowie SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

I’ll next create an index on the well clustered ID column (as the rows are inserted in ID column order within the table):

SQL> create index bowie_id_i on bowie(id);

Index BOWIE_ID_I created.

Next, we’ll use the Oracle recommended method of collecting table/index statistics, by using the DBMS_STATS package:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables
where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      3268               0            0            111            0

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 3250

 

Note the key index statistics here: BLEVEL=1, LEAF_BLOCKS=473 and the near perfect CLUSTERING_FACTOR=3250.

If we run the following query featuring a non-equality range predicate:

 

SQL> select * from bowie where id > 1 and id < 1001;

999 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0
-------------------------------------
select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |    999 |00:00:00.01 |      18 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |    999 |00:00:00.01 |      18 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |    999 |00:00:00.01 |       4 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
          1 DB time
       7678 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         16 buffer is not pinned count
       1983 buffer is pinned count
        323 bytes received via SQL*Net from client
     171383 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
         18 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
         18 consistent gets from cache
         17 consistent gets pin
         17 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     147456 logical read bytes from cache
         17 no work - consistent read gets
         40 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          2 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
         18 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
        999 table fetch by rowid
          3 user calls

We notice that the CBO indeed uses the index.

They key statistic to note here is that Consistent Gets is just 18, which is extremely low considering we’re returning 999 rows. This is due to the fact the index is currently extremely efficient as it can fetch multiple rows by visiting the same table block due to the excellent clustering/ordering of the required ID column values (and also due to my high arraysize session setting).

If we look at the CBO costings for this plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'b1vwpu2rgn8p5',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0

-------------------------------------

select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     |Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    21 (100)|    999 |00:00:00.01 |     18 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   108K|      21 (0)|    999 |00:00:00.01 |     18 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |       |       4 (0)|    999 |00:00:00.01 |      4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

 

I’ve previously discussed many times how the CBO costs index access paths, but it’s always useful to go over this again, as it’s the most common question I get asked when I visit customer sites.

The KEY statistic the CBO has to determine is the estimated Selectivity of the query (the estimated percentage of rows to be returned), as this is the driver of all the subsequent CBO calculations.

The Selectivity of this range-based predicate query is calculated as follows:

Selectivity = (Highest Bound Value ‚Äď Lowest Bound Value) / (Highest Value ‚Äď Lowest Value)
= (1001-1) /(200000-1)
= 1000/199999
=  approx. 0.005

Once Oracle has the selectivity, it can calculate the query Cardinality (estimated number of rows) as follows:

Cardinality = Selectivity x No of Rows

Cardinality = 0.005 x 200000 = 1000 rows

This is our visual window into the likelihood that the CBO has made an accurate decision with its execution plan. If the cardinality estimates are reasonably accurate, then the CBO is likely to generate a good plan. If the cardinality estimates are way off, then the CBO is more likely to generate an inappropriate plan.

The CBO cardinality estimate in the above plan is 1000 rows, whereas the number of rows actually returned is 999 rows.

So indeed, the CBO has got the cardinality almost spot on (except for a trivial rounding error) and so we have a high degree of confidence that the CBO is using the correct selectivity estimates when they get plugged into the following CBO formula for costing an index range scan (using this selectivity of 0.005 and the index statistics listed above):

Index Scan Cost = (blevel + ceil(effective index selectivity x leaf_blocks)) + ceil(effective table selectivity x clustering_factor)

= (1 + ceil(0.005 x 467)) + ceil(0.005 x 3250)
= (1 + 3) + 17
= 4 + 17 = 21

So we can clearly see where the CBO gets its costings for both reading the index during the Index Range Scan (4) and for the plan as a whole (21).

The CBO cost of 21 very closely resembles the 18 consistent gets accessed when the plan is executed. This to me suggests that the CBO has indeed costed this plan very accurately and appropriately.

It’s interesting to note in the above execution plan that Oracle is attributing 100% of this cost of 21 to CPU (21 (100)). That will be a discussion for another day…

OK, let’s now perform an update on the table, increasing the size of the rows such that I generate a bunch of migrated rows:

SQL> update bowie set name='THE RISE AND FALL OF BOWIE STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.

SQL> commit;

Commit complete.

If we now collect fresh statistics again using DBMS_STATS:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables
where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4906               0            0            167            0

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 3250

 

We notice that none of the key statistics have changed, except for the number of Table Blocks (now 4906, previously it was 3268) and the Average Row Length has also increased (now 167, previously it was 111). Both of these can of course be attributed to the increase in the size of the values now stored in the NAME column following the Update.

Importantly, notice that collecting statistics via DBMS_STATS does NOT collect data for the CHAIN_CNT statistic, it remains at 0 even though many migrated rows were actually generated by the Update statement (as we’ll see below).

Increasing the Table Blocks will result in an associated increase in the cost of reading this table via a Full Table Scan (FTS).

We notice that none of the index-related statistics changed following the Update statement (as in this example, Oracle does NOT update the ROWIDs of any of the migrated rows, Oracle simply stores a pointer in the original block to denote the new physical location of the migrated rows as previously discussed).

So if we only INCREASE the cost of a FTS (via having more Table Blocks) but keep intact all the previous index related statistics, then the CBO is certainly going to again select the same Index Range Scan plan, as the plan will have the same (cheaper than FTS) costings as before.

If we re-run the query again:

SQL> select * from bowie where id > 1 and id < 1001;

999 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0
-------------------------------------
select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |    999 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |    999 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |    999 |00:00:00.01 |       4 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
       7709 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
        664 buffer is not pinned count
       1662 buffer is pinned count
        323 bytes received via SQL*Net from client
     171500 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
        666 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
        666 consistent gets from cache
        665 consistent gets pin
        665 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
    5455872 logical read bytes from cache
        665 no work - consistent read gets
         39 non-idle wait count
          1 non-idle wait time
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          2 session cursor cache count
        666 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
        999 table fetch by rowid
        327 table fetch continued row
          3 user calls

We notice that indeed it’s the same Index Range Scan plan as before.

But we notice that the number of Consistent Gets has increased substantially to 666 (previously it was just 18). The reason for this large jump is due to the now 327 table fetch continued rows that need to be accessed due to the newly migrated rows following the Update. This number is then doubled (so 2 x 327 = 654) to represent the approximate additional Consistent Gets we now need to perform, as Oracle needs to read the additional table block to access the migrated row’s new physical location AND to now re-read the original table block to access the next row to be fetched (previously Oracle could read all the required consecutive rows required from the same table block within the one consistent get).

So it’s now actually substantially more expensive to read the required 1000 rows via this index due to this increase in necessary consistent gets.

But if we look at the actual cost of this plan now:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'b1vwpu2rgn8p5',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID b1vwpu2rgn8p5, child number 0

-------------------------------------

select * from bowie where id > 1 and id < 1001

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     |Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    21 (100)|    999 |00:00:00.01 |    666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   163K|      21 (0)|    999 |00:00:00.01 |    666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |       |       4 (0)|    999 |00:00:00.01 |      4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">1 AND "ID"<1001)

 

We notice that as expected (as none of the index-related statistics have changed), that despite being much more expensive to now use this index, the costs of this plan (4 for reading the index and 21 overall) remain unchanged.

I would argue that these CBO costs are no longer as accurate as the 21 total CBO cost does not so closely represent the actual 666 consistent gets now required.

Now, the 327 table fetch continued row statistics from the previous run is clear proof we indeed have migrated rows following the Update statement.

But if we want to confirm how many migrated rows we now have in the table, we can use the ANALYZE command to collect these additional statistics:

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables
where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4906              86          415            170        56186

 

We notice that we now have a CHAIN_CNT of 56186.

Now this statistic can represent any row that is not housed inside a single table block (for which there could be a number of possible reasons, such as a row simply being too long to fit in a single table block), but as all rows are still relatively tiny, we can be certain that indeed all 56186 chained rows represent migrated rows.

Now that I’ve gone and used ANALYZE, primarily to generate this CHAIN_CNT statistic, my previous understanding of how the CBO costs migrated rows crumbles away, as I’ll discuss in my next post…

Migrated Rows In Oracle Data Warehouse Autonomous Databases (“Sit Down. Stand Up.”) March 14, 2023

Posted by Richard Foote in 19c, 19c New Features, Autonomous Data Warehouse, Autonomous Database, Changing ROWID, Migrated Rows, Oracle, Oracle Cloud, Oracle Indexes, Oracle19c, ROWID.
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In all my recent discussions on how Oracle can now update ROWIDs on the fly when a row migrates, I’ve mentioned how this only occurs on tables in which the ENABLE ROW MOVEMENT clause has been set.

So you have the option on whether you wish this new behaviour to occur by simply not setting ENABLE ROW MOVEMENT on tables where you want the previous behavior of the ROWIDs not changing when a row migrates (and for Oracle to simply have a pointer in the original table block to denote the new location of the row). You may not what ROWIDs to suddenly change on you for example if you have an application that explicitly stores ROWIDs and relies on them not changing for the application to correctly fetch data.

However, all my previous tests and examples have been run on Oracle Transaction Processing Autonomous Database environments, but as Phil Goldenberg mentioned in this comment, things unfortunately behave somewhat differently in Oracle Data Warehouse Autonomous Database environments.

To illustrate, a simple little demo as usual, but this time using an Oracle Data Warehouse Autonomous Database environment…

Let’s start by creating and populating a tightly packed table, but without setting the ENABLE ROW MOVEMENT clause:

SQL> create table bowie (id number, name varchar2(142)) pctfree 0;

Table BOWIE created.

SQL> insert into bowie select rownum, 'BOWIE' from dual connect by level <=10000;

10,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

Let’s now create an index based on the ID column:

SQL> create index bowie_id_i on bowie(id);

Index BOWIE_ID_I created.

SQL> select index_name, num_rows, blevel, leaf_blocks from user_indexes where table_name='BOWIE';

   INDEX_NAME    NUM_ROWS    BLEVEL    LEAF_BLOCKS
_____________ ___________ _________ ______________
BOWIE_ID_I          10000         1             23

Let’s have a look at the ROWIDs of a few random rows:

SQL> select id, rowid from bowie where id in (42, 424, 4242) order by id;

     ID                 ROWID
_______ _____________________
     42 AAASTdAAAAAAJq0AAp
    424 AAASTdAAAAAAJq0AIH
   4242 AAASTdAAAAAAJq1ADP

If we store these ROWIDs, we can use them to directly access a row of interest very efficiently:

SQL> select id from bowie where rowid='AAASTdAAAAAAJq0AAp';

   ID
_____
   42

Next, I’ll update the table, increasing the size of the rows such that I generate a bunch of migrated rows:

SQL> update bowie set name='THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS';

10,000 rows updated.

SQL> commit;

Commit complete.

As discussed previously, if this were an Oracle Transaction Processing Autonomous Database environment, because I haven’t set ENABLE ROW MOVEMENT on this table, the ROWIDs of any migrated rows would NOT have changed.

But here in this Oracle Data Warehouse Database environment:

SQL> select id, rowid from bowie where id in (42, 424, 4242) order by id;

     ID                 ROWID
_______ _____________________
     42 AAASTdAAAAAAJq3AAp
    424 AAASTdAAAAAAJq3AIH
   4242 AAASTdAAAAAAJrcAFd

We can see that all these rows now have a new ROWID.

If I now re-run my previous query that relied on the ROWIDs not changing:

SQL> select id from bowie where rowid='AAASTdAAAAAAJq0AAp';

no rows selected

We can see that the query no longer returns the required row.

And yet, if we ANALYZE the table:

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> select table_name, num_rows, blocks, chain_cnt, row_movement from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    CHAIN_CNT    ROW_MOVEMENT
_____________ ___________ _________ ____________ _______________
BOWIE               10000        28            0 DISABLED

We can see that we have no migrated/chained rows listed, even though ENABLE ROW MOVEMENT is disabled.

I think this a little unfortunate, because I quite like the concept of ROWIDs being updated when a row migrates, but I also like the option of being able to revert to the previous behaviour if necessary.

I have no idea how this works in the other Oracle Autonomous Database environments (other than Transaction Processing), but regardless, this behaviour can potentially change on any of the environments at any time.

So, what’s the moral of the story? Well there’s a couple.

Firstly, in Oracle Autonomous Database environments, you’re meant to have a “hands-off” attitude and just let Oracle handle all this day to day stuff. So you can’t necessarily rely on the behaviour of the database to be as consistent as in environments where you control all the levers. Indexes might come and go, tables might suddenly get partitioned, ROWIDs might change when a row migrates, etc. etc. etc. etc.

And secondly, it’s becoming an even worse idea for applications to explicitly store and rely on ROWIDs not changing for such applications function properly. Especially, if you use Oracle Autonomous Database environments…

Possible Impact To Clustering Factor Now ROWIDs Are Updated When Rows Migrate Part III (“Dancing With The Big Boys”) March 9, 2023

Posted by Richard Foote in 19c, 19c New Features, Attribute Clustering, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, CBO, Changing ROWID, Clustering Factor, Data Clustering, Full Table Scans, Index Access Path, Index Internals, Index Rebuild, Index statistics, Leaf Blocks, Migrated Rows, Oracle, Oracle 21c, Oracle Blog, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle19c, ROWID.
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In my previous post, I discussed how you can best reorg a table that has a significant number of migrated rows impact the Clustering Factor of important indexes, when such tables have the ENABLED ROW MOVEMENT disabled.

In this post I’ll discuss resolving similar issues, but when ROWIDs are updated on the fly when rows are migrated in Oracle Autonomous Databases.

As I discussed previously, by updating indexes with the new ROWIDs when rows migrate, such indexes can potentially increase in size as they store both old/new index entries concurrently AND due to the increased likelihood of associated index block splits. Additionally, such indexes can also have their Clustering Factor directly impacted when migrated rows disrupt the otherwise tight clustering of specific columns.

As such, we may want to address these issues to improve the performance of impacted queries.¬† But it’s important we address these issues appropriately…

To illustrate all this, I’m going to re-run the same demo as my previous post, but on a table with ENABLE ROW MOVEMENT enabled.

I’ll start by creating and populating a tightly packed table with ENABLE ROW MOVEMENT enabled and with data inserted in ID column order:

SQL> create table bowie2(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0 ENABLE ROW MOVEMENT;

Table BOWIE2 created.

SQL> insert into bowie2 SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

I’ll now create an index on this well ordered/clustered ID column:

SQL> create index bowie2_id_i on bowie2(id);

Index BOWIE2_ID_I created.

Next, I’ll update the table, increasing the size of the rows such that I generate a bunch of migrated rows:

SQL> update bowie2 set name='THE RISE AND FALL OF BOWIE STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.

SQL> commit;

Commit complete.

 

If we check the number of migrated rows:

SQL> analyze table bowie2 compute statistics;

Table BOWIE2 analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables where table_name='BOWIE2';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE2             200000      4654              82          367            169            0

We notice there are indeed 0 migrated rows. This is because in Oracle Autonomous Databases, the associated ROWIDs of migrated rows as updated on the fly in this scenario.

If we check the current Clustering Factor of the index:

SQL> execute dbms_stats.delete_table_stats(ownname=>null, tabname=>'BOWIE2');

PL/SQL procedure successfully completed.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE2', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE2';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE2             200000      4654

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE2';

    INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
______________ _________ ______________ ____________________
BOWIE2_ID_I            2            945               109061

We can see that although the data was initially inserted in ID column order, we now have a relatively poor Clustering Factor at 109061 as the migrated rows have disrupted this previously perfect clustering.

We also notice that the BLEVEL has increased from 1 to now be 2 and the number of Leaf Blocks has increased to 945 from 473 after the rows migrated (as I discussed previously).

If we now run a query that returns 4200 rows from a 200,000 row table:

SQL> select * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 1495904576

----------------------------------------------------------------------------------------------
| Id | Operation                  | Name   | Starts | E-Rows | A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |        |      1 |        |   4200 |00:00:00.02 |    4572 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE2 |      1 |   4200 |   4200 |00:00:00.02 |    4572 |
----------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

Note
-----
    - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          4 CPU used by this session
          4 CPU used when call started
          4 DB time
      37101 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
          2 buffer is not pinned count
        325 bytes received via SQL*Net from client
     461965 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
         14 calls to kcmgcs
       4572 consistent gets
       4572 consistent gets from cache
       4572 consistent gets pin
       4572 consistent gets pin (fastpath)
          2 execute count
   37453824 logical read bytes from cache
       4560 no work - consistent read gets
         72 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
       4572 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4560 table scan blocks gotten
     252948 table scan disk non-IMC rows gotten
     252948 table scan rows gotten
          1 table scans (short tables)
          3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'25qktyn35b662',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
______________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 1495904576

-------------------------------------------------------------------------------------------------------------------
| Id | Operation                  | Name   | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |        |      1 |        |       |  1264 (100)|   4200 |00:00:00.02 |    4572 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE2 |      1 |   4200 |   684K|    1264 (1)|   4200 |00:00:00.02 |    4572 |
-------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

 

We can see that Oracle has decided to perform a Full Table Scan (FTS) and not use the index.

The Clustering Factor of the ID column is now so bad, that returning 4200 rows via such an index is just too expensive. The FTS is now deemed the cheaper option by the CBO.

We notice that the CBO cost of the FTS is 1264.

If we run a query that forces the use of the index:

SQL> select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID bzm2vhchqpq7w, child number 0
-------------------------------------
select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   4200 |00:00:00.01 |    2665 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   4200 |00:00:00.01 |    2665 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      21 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)


Statistics
-----------------------------------------------------------
          2 CPU used by this session
          2 CPU used when call started
          2 DB time
      14531 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
       2646 buffer is not pinned count
       5755 buffer is pinned count
        348 bytes received via SQL*Net from client
     462143 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       2665 consistent gets
          2 consistent gets examination
          2 consistent gets examination (fastpath)
       2665 consistent gets from cache
       2663 consistent gets pin
       2663 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
   21831680 logical read bytes from cache
       2663 no work - consistent read gets
         73 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          3 process last non-idle time
          2 session cursor cache count
       2665 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
          3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'bzm2vhchqpq7w',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID bzm2vhchqpq7w, child number 0

-------------------------------------

select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |  2314 (100)|   4200 |00:00:00.01 |    2665 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   684K|    2314 (1)|   4200 |00:00:00.01 |    2665 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |       |      22 (0)|   4200 |00:00:00.01 |      21 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

The cost of the Index Range Scan plan has an overall cost of 2314, greater than the 1264 cost of the FTS plan.

Notice that the cost of using just the index within the plan is currently 22.

So the vast majority of the cost of this plan (2314 – 22 = 2292) is in Oracle having to access so many different table blocks due to the poor index Clustering Factor and NOT in the increased size of the index.

As I’ve discussed numerous times, you can potentially make an index smaller by rebuilding the index (if there’s free space within the index), but the impact on the Clustering Factor will be nothing but “disappointing”…

If we just rebuild the index:

SQL> alter index bowie2_id_i rebuild online;

Index BOWIE2_ID_I altered.

And now look at the new index related statistics:

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE2';

    INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
______________ _________ ______________ ____________________
BOWIE2_ID_I            1            473               109061

We notice that the index has indeed decreased in size, back to what is was before the row migrated following the Update (Blevel=1 and Leaf Blocks=473).

But the Clustering Factor remains unchanged at 109061.

If we now re-run the query:

 

SQL> select * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 1495904576

----------------------------------------------------------------------------------------------
| Id | Operation                  | Name   | Starts | E-Rows | A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |        |      1 |        |   4200 |00:00:00.02 |    4572 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE2 |      1 |   4200 |   4200 |00:00:00.02 |    4572 |
----------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          3 CPU used by this session
          3 CPU used when call started
          3 DB time
      31738 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
          2 buffer is not pinned count
        325 bytes received via SQL*Net from client
     461972 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
         14 calls to kcmgcs
       4572 consistent gets
       4572 consistent gets from cache
       4572 consistent gets pin
       4572 consistent gets pin (fastpath)
          2 execute count
   37453824 logical read bytes from cache
       4560 no work - consistent read gets
         73 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          3 process last non-idle time
          2 session cursor cache count
       4572 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4560 table scan blocks gotten
     252948 table scan disk non-IMC rows gotten
     252948 table scan rows gotten
          1 table scans (short tables)
          3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'25qktyn35b662',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
______________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 1495904576

-------------------------------------------------------------------------------------------------------------------
| Id | Operation                  | Name   | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |        |      1 |        |       |  1264 (100)|   4200 |00:00:00.02 |    4572 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE2 |      1 |   4200 |   684K|    1264 (1)|   4200 |00:00:00.02 |    4572 |
-------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

 

The CBO decides to still use a FTS instead of the index.

If we look at the cost now of using the index for this query:

SQL> select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID bzm2vhchqpq7w, child number 0
-------------------------------------
select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   4200 |00:00:00.01 |    2655 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   4200 |00:00:00.01 |    2655 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          2 CPU used by this session
          2 CPU used when call started
          1 DB time
      13484 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
       2646 buffer is not pinned count
       5755 buffer is pinned count
        347 bytes received via SQL*Net from client
     461972 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       2655 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
       2655 consistent gets from cache
       2654 consistent gets pin
       2654 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
   21749760 logical read bytes from cache
       2654 no work - consistent read gets
         73 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
       2655 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
          3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'bzm2vhchqpq7w',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID bzm2vhchqpq7w, child number 0

-------------------------------------

select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |  2303 (100)|   4200 |00:00:00.01 |    2655 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   684K|    2303 (1)|   4200 |00:00:00.01 |    2655 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We notice the cost of the index has only moderately gone down to 2303 (previously it was 2314).

This reduction of 11 in the CBO cost is due entirely to the fact the index is now approximately 1/2 the size as it was before the index rebuild and has thus reduced the cost of reading the index blocks to 11 within the execution plan (previously it was 22).

But the vast majority of the cost within the Index Range Scan plan comes again with accessing the table blocks, which remains unchanged due to the unchanged Clustering Factor.

To reduce the Clustering Factor, we need to change the clustering of the data with the TABLE.

So, to improve the performance of this potentially important query, we need to re-cluster the data just as we did in the example in my previous post when we had migrated rows listed and ROWIDs were not updated on the fly.

We can now add an appropriate Clustering Attribute before we perform the table reorg:

SQL> alter table bowie2 add clustering by linear order (id);

Table BOWIE2 altered.

SQL> alter table bowie2 move online;

Table BOWIE2 altered.

If we now look at the Clustering Factor of this important index:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE2', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE2';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE2             200000      4936

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE2';

    INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
______________ _________ ______________ ____________________
BOWIE2_ID_I            1            473                 4850

The Clustering Factor has been reduced down to the almost perfect 4850, down from the previous 109061.

If we now re-run the query:

SQL> select * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   4200 |00:00:00.01 |     102 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   4200 |00:00:00.01 |     102 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
         90 Cached Commit SCN referenced
      11345 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         93 buffer is not pinned count
       8308 buffer is pinned count
        325 bytes received via SQL*Net from client
     462117 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
        102 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
        102 consistent gets from cache
        101 consistent gets pin
        101 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     835584 logical read bytes from cache
        101 no work - consistent read gets
         72 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          2 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
        102 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
          3 user calls

 

We can see the query now automatically uses the index and only requires just 102 consistent gets, down from 4572 when it performed the FTS.

If we look at the cost of this new plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'25qktyn35b662',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0

-------------------------------------

select * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |   113 (100)|   4200 |00:00:00.01 |     102 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   684K|     113 (0)|   4200 |00:00:00.01 |     102 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We can see the plan has a cost of just 113, which is both much more accurate and close to the 102 consistent gets and much less than the previous cost of 1340 for the FTS plan.

So in specific examples where migrated rows significantly impact the Clustering Factor of indexes important to our applications, including when ROWIDs are updated on the fly in Oracle Autonomous Databases, we may need to appropriately reorg such tables to repair the Clustering Factor of impacted indexes.

I’ve mentioned a number of times in this series how tables in Oracle Autonomous Databases with ENABLE ROW MOVEMENT have their ROWIDs updated on the fly when a row migrates. In my next post, I’ll discuss how even tables that don’t have the ENABLE ROW MOVEMENT clause set can still have their ROWIDs updated on the fly when a row migrates…

Possible Impact To Clustering Factor Now ROWIDs Are Updated When Rows Migrate Part II (“Dancing Out In Space”) March 7, 2023

Posted by Richard Foote in 19c, 19c New Features, Attribute Clustering, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, CBO, Changing ROWID, Clustering Factor, Data Clustering, David Bowie, Full Table Scans, Index Access Path, Index Internals, Index Rebuild, Index statistics, Leaf Blocks, Migrated Rows, Oracle, Oracle 21c, Oracle Blog, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Statistics, Oracle19c, Performance Tuning, Richard's Musings, ROWID.
1 comment so far

In my previous post, I discussed how the clustering of data can be impacted if rows migrate and how this in turn can have a detrimental impact on the efficiency of associated indexes.

In this post, I’ll discuss what you can do (and not do) to remedy things in the relatively unlikely event that you hit this issue with migrated rows.

I’ll just discuss initially the example where the table is defined without ENABLE ROW MOVEMENT enabled in the Transaction Processing Autonomous Database (and so does NOT update ROWIDs on the fly when a row migrates).

I’ll start by again creating and populating a tightly packed table, with the data inserted in ID column order:

SQL> create table bowie(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0;

Table BOWIE created.

SQL> insert into bowie SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

I’ll now create an index on this well ordered/clustered ID column:

SQL> create index bowie_id_i on bowie(id);

Index BOWIE_ID_I created.

Next, I’ll update the table, increasing the size of the rows such that I generate a bunch of migrated rows:

SQL> update bowie set name='THE RISE AND FALL OF BOWIE STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.

SQL> commit;

Commit complete.

 

If we check the number of migrated rows:

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables

where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4906              86          414            170        56186

 

We notice there are indeed 56186 migrated rows.

If we check the current Clustering Factor of the index:

SQL> execute dbms_stats.delete_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE              200000      4906

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 3250

 

We notice the index still has an excellent Clustering Factor of just 3250. As the ROWIDs are NOT updated in this example when rows migrate, the index retains the same Clustering Factor as before the Update statement.

If we run the following query that returns 4200 rows (as per my previous post):

SQL> select * from bowie where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0
-------------------------------------
select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   4200 |00:00:00.01 |    2771 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   4200 |00:00:00.01 |    2771 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)


Statistics
-----------------------------------------------------------
          2 CPU used by this session
          2 CPU used when call started
          3 DB time
      24901 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
       2762 buffer is not pinned count
       7005 buffer is pinned count
        324 bytes received via SQL*Net from client
     461909 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       2771 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
       2771 consistent gets from cache
       2770 consistent gets pin
       2770 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
   22700032 logical read bytes from cache
       2770 no work - consistent read gets
         73 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
       2771 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
       1366 table fetch continued row
          3 user calls

We can see the query currently uses 2771 consistent gets, which is significantly higher than it could be, as Oracle has to visit the original table block and then follow the pointer to the new location for any migrated row that needs to be retrieved.

However, if we look at the cost of the current plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'c376kdhy5b0x9',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0

-------------------------------------

select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    80 (100)|   4200 |00:00:00.01 |    2771 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   684K|      80 (0)|   4200 |00:00:00.01 |    2771 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
---------------------------------------------------------------------------------------------------------------------------------

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We can see it only has a cost of 80, as Oracle does not consider the additional accesses required now for these migrated rows. With such a perfect Clustering Factor, this cost is not particularly accurate and does not represent the true cost of the 2771 consistent gets now required.

Now there are various ways we can look at fixing this issue with all these migrated rows requiring additional consistent gets to access.

One method is to capture all the ROWIDs of the migrated rows, copy these rows to a temporary holding table, delete these rows and then re-insert them all back into the table from the temporary table.

We can identify the migrated rows by creating the CHAIN_ROWS table as per the Oracle supplied UTLCHAIN.SQL script and then use the ANALYZE command to store their ROWIDs in this CHAIN_ROWS table:

SQL> create table CHAINED_ROWS (
2 owner_name varchar2(128),
3 table_name varchar2(128),
4 cluster_name varchar2(128),
5 partition_name varchar2(128),
6 subpartition_name varchar2(128),
7 head_rowid rowid,
8 analyze_timestamp date
9* );

Table CHAINED_ROWS created.

SQL> analyze table bowie list chained rows;

Table BOWIE analyzed.

SQL> select table_name, head_rowid from chained_rows where table_name='BOWIE' and rownum<=10;

   TABLE_NAME            HEAD_ROWID
_____________ _____________________
BOWIE         AAAqFjAAAAAE6CzAAP
BOWIE         AAAqFjAAAAAE6CzAAR
BOWIE         AAAqFjAAAAAE6CzAAU
BOWIE         AAAqFjAAAAAE6CzAAW
BOWIE         AAAqFjAAAAAE6CzAAZ
BOWIE         AAAqFjAAAAAE6CzAAb
BOWIE         AAAqFjAAAAAE6CzAAe
BOWIE         AAAqFjAAAAAE6CzAAg
BOWIE         AAAqFjAAAAAE6CzAAj
BOWIE         AAAqFjAAAAAE6CzAAl

 

Another method we can now utilise is to simply MOVE ONLINE the table:

SQL> alter table bowie move online;

Table BOWIE altered.

 

If we now look at the number of migrated rows after the table reorg:

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
BOWIE              200000      4936              56          838            169            0

 

We can see we no longer have any migrated rows.

BUT, if we now look at the Clustering Factor of this index:

SQL> execute dbms_stats.delete_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE              200000      4936

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473               114560

 

We can see it has now significantly increased to 114560 (previously it was just 3250).

The problem of course is that if the ROWIDs now represent the correct new physical location of the migrated rows, the previously perfect clustering/ordering of the ID column has been impacted.

If we now re-run the query returning the 4200 rows:

SQL> select * from bowie where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0
-------------------------------------
select * from bowie where id between 1 and 4200

Plan hash value: 1845943507

---------------------------------------------------------------------------------------------
| Id | Operation                  | Name  | Starts | E-Rows | A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |       |      1 |        |   4200 |00:00:00.02 |    4857 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE |      1 |   4200 |   4200 |00:00:00.02 |    4857 |
---------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

Statistics
-----------------------------------------------------------
          3 CPU used by this session
          3 CPU used when call started
       4849 Cached Commit SCN referenced
          2 DB time
      25870 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
          2 buffer is not pinned count
        324 bytes received via SQL*Net from client
     461962 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          9 calls to kcmgcs
       4857 consistent gets
       4857 consistent gets from cache
       4857 consistent gets pin
       4857 consistent gets pin (fastpath)
          2 execute count
   39788544 logical read bytes from cache
       4850 no work - consistent read gets
         72 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          2 process last non-idle time
          1 session cursor cache count
       4857 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4850 table scan blocks gotten
     200000 table scan disk non-IMC rows gotten
     200000 table scan rows gotten
          1 table scans (short tables)
          3 user calls

 

Oracle is now performing a Full Table Scan (FTS). The number of consistent gets now at 4857 is actually worse than when we had the migrated rows (previously at 2771)

The Clustering Factor of the ID column is now so bad, that returning 4200 rows via such an index is just too expensive. The FTS is now deemed the cheaper option by the CBO.

If we look at the CBO cost of using this FTS plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'c376kdhy5b0x9',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0
-------------------------------------
select * from bowie where id between 1 and 4200

Plan hash value: 1845943507

------------------------------------------------------------------------------------------------------------------
| Id | Operation                  | Name  | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |       |      1 |        |       |  1340 (100)|   4200 |00:00:00.02 |    4857 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE |      1 |   4200 |   684K|    1340 (1)|   4200 |00:00:00.02 |    4857 |
------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

 

We can see the cost of this plan is 1340.

If we compare this with the cost of using the (now deemed) inefficient index:

SQL> select /*+ index (bowie) */ * from bowie where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID 9215hkzd3v1up, child number 0
-------------------------------------
select /*+ index (bowie) */ * from bowie where id between 1 and 4200

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   4200 |00:00:00.01 |    2784 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   4200 |00:00:00.01 |    2784 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)


Statistics
-----------------------------------------------------------
          2 CPU used by this session
          2 CPU used when call started
       2741 Cached Commit SCN referenced
          2 DB time
      12633 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
       2775 buffer is not pinned count
       5626 buffer is pinned count
        345 bytes received via SQL*Net from client
     462170 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       2784 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
       2784 consistent gets from cache
       2783 consistent gets pin
       2783 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
   22806528 logical read bytes from cache
       2783 no work - consistent read gets
         72 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          4 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
       2784 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
          3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'9215hkzd3v1up',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID 9215hkzd3v1up, child number 0

-------------------------------------

select /*+ index (bowie) */ * from bowie where id between 1 and 4200

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |  2418 (100)|   4200 |00:00:00.01 |    2784 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   684K|    2418 (1)|   4200 |00:00:00.01 |    2784 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We can see the CBO cost of the index is now 2418, more than the 1340 cost of using the FTS.

So in the scenario where by migrating a significant number of rows, we impact the Clustering Factor and so the efficiency of vital indexes in our applications, we need to eliminate the migrated rows in a more thoughtful manner.

An option we have available is to first add an appropriate Clustering Attribute before we perform the table reorg:

SQL> alter table bowie add clustering by linear order (id);

Table BOWIE altered.

SQL> alter table bowie move online;

Table BOWIE altered.

 

If we now look at the Clustering Factor of this important index:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE              200000      4936

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 4850

 

The Clustering Factor has been reduced down to the almost perfect 4850, down from the previous 114560.

If we now re-run the query:

SQL> select * from bowie where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0
-------------------------------------
select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   4200 |00:00:00.01 |     102 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   4200 |00:00:00.01 |     102 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)


Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
         89 Cached Commit SCN referenced
          1 DB time
      11249 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         93 buffer is not pinned count
       8308 buffer is pinned count
        324 bytes received via SQL*Net from client
     462165 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
        102 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
        102 consistent gets from cache
        101 consistent gets pin
        101 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     835584 logical read bytes from cache
        101 no work - consistent read gets
         72 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
        102 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
          3 user calls

We can see the query now automatically uses the index and only requires just 102 consistent gets (down from 4857 when it performed the FTS and down from 2771 when we had the migrated rows).

If we look at the cost of this new plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'c376kdhy5b0x9',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0

-------------------------------------

select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |   113 (100)|   4200 |00:00:00.01 |     102 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   684K|     113 (0)|   4200 |00:00:00.01 |     102 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We can see the plan has a cost of just 113, which is both much more accurate and close to the 102 consistent gets and much less than the previous cost of 1340 for the FTS plan.

So in specific scenarios where by having migrated rows we significantly impact the Clustering Factor of indexes important to our applications, we have to be a little cleverer in how we address the migrated rows.

This can also the case in the new scenario where Oracle automatically updates the ROWIDs of migrated rows, as I’ll discuss in my next post…

Possible Impact To Clustering Factor Now ROWIDs Are Updated When Rows Migrate Part I (“Growin’ Up”) March 1, 2023

Posted by Richard Foote in 19c, 19c New Features, Attribute Clustering, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, BLEVEL, CBO, Changing ROWID, Clustering Factor, Data Clustering, Hints, Index Access Path, Index Block Splits, Index Delete Operations, Index Height, Index Internals, Index Rebuild, Index statistics, Leaf Blocks, Migrated Rows, Oracle, Oracle Blog, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Indexing Internals Webinar, Oracle Statistics, Oracle19c, Performance Tuning, Richard Foote Training, Richard's Blog, ROWID.
2 comments

In my previous post I discussed how an index can potentially be somewhat inflated in size after ROWIDs are updated on the fly after a substantial number of rows are migrated.

However, there’s another key “factor” of an index that in some scenarios can be impacted by this new ROWID behaviour with regard migrated rows.

To highlight this scenario, I’ll again start by creating and populating a table with ENABLE ROW MOVEMENT disabled:

SQL> create table bowie(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0;

Table BOWIE created.

SQL> insert into bowie SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

I’ll next create an index on the ID column. The important aspect with the ID column is that the data is entered monotonically in ID column order, so the associated index will have an excellent (very low) Clustering Factor:

SQL> create index bowie_id_i on bowie(id);

Index BOWIE_ID_I created.

If we look at some key statistics of the table and index:

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE              200000      3268

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 3250

We can see that the number of table blocks is 3268, the number of index leaf blocks is 473 and we indeed have a near perfect Clustering Factor of 3250.

If we run a couple of queries:

SQL> select * from bowie where id between 1 and 1000;

1,000 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID gz5u92hmjwz1h, child number 0
-------------------------------------
select * from bowie where id between 1 and 1000

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   1000 |00:00:00.01 |      18 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   1000 |00:00:00.01 |      18 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |   1000 |00:00:00.01 |       4 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
       7353 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         16 buffer is not pinned count
       1985 buffer is pinned count
        324 bytes received via SQL*Net from client
     171305 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
         18 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
         18 consistent gets from cache
         17 consistent gets pin
         17 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     147456 logical read bytes from cache
         17 no work - consistent read gets
         38 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          2 session cursor cache count
         18 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       1000 table fetch by rowid
          3 user calls

We can see for this first query that returns 1000 rows, it requires just 18 consistent gets, thanks primarily due to the efficient index with the perfect Clustering Factor.

If we look at the cost of this plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'gz5u92hmjwz1h',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID gz5u92hmjwz1h, child number 0

-------------------------------------

select * from bowie where id between 1 and 1000

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    21 (100)|   1000 |00:00:00.01 |      18 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   108K|      21 (0)|   1000 |00:00:00.01 |      18 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |       |       4 (0)|   1000 |00:00:00.01 |       4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

We can see the plan has an accurate cost of just 21.

If we now run a similar query that returns a few more rows:

SQL> select * from bowie where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0
-------------------------------------
select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   4200 |00:00:00.01 |      68 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   4200 |00:00:00.01 |      68 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
          1 DB time
      11353 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         59 buffer is not pinned count
       8342 buffer is pinned count
        324 bytes received via SQL*Net from client
     461834 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
         68 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
         68 consistent gets from cache
         67 consistent gets pin
         67 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     557056 logical read bytes from cache
         67 no work - consistent read gets
         73 non-idle wait count
         2 opened cursors cumulative
         1 opened cursors current
         2 parse count (total)
         1 process last non-idle time
         2 session cursor cache count
        68 session logical reads
         1 sorts (memory)
      2024 sorts (rows)
      4200 table fetch by rowid
         3 user calls

We can see that it only required just 68 consistent gets to return 4200 rows, thanks to the excellent data clustering and associated very low Clustering Factor.

If we look at the cost of this plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'c376kdhy5b0x9',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0

-------------------------------------

select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    80 (100)|   4200 |00:00:00.01 |      68 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   455K|      80 (0)|   4200 |00:00:00.01 |      68 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We can see the cost of the plan is currently a relatively accurate 80.

OK, let’s now perform an update on this table that generates a bunch of migrated rows:

SQL> update bowie set name='THE RISE AND FALL OF BOWIE STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.

SQL> commit;

Commit complete.

If we now look at the table and index statistics:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE              200000      4906

We can see that the table blocks value has increased to 4906 (previously 3268). This as explained previously is to due in large part to the increased NAME column values and also due to the pointers in the original table blocks that point to the new locations of the migrated rows.

This relates to approximately a 50% increase in table blocks.

If we look at the current index statistics:

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE';

   INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_____________ _________ ______________ ____________________
BOWIE_ID_I            1            473                 3250

We can see that these values are all unchanged, as the ROWIDs in indexes remain unchanged when a row migrates, when ENABLE ROW MOVEMENT is not set.

Therefore, when we re-run these same queries:

SQL> select * from bowie where id between 1 and 1000;

1,000 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID gz5u92hmjwz1h, child number 0
-------------------------------------
select * from bowie where id between 1 and 1000

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   1000 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   1000 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |   1000 |00:00:00.01 |       4 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          1 DB time
       7967 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
        664 buffer is not pinned count
       1664 buffer is pinned count
        324 bytes received via SQL*Net from client
     171419 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
        666 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
        666 consistent gets from cache
        665 consistent gets pin
        665 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
    5455872 logical read bytes from cache
        665 no work - consistent read gets
         37 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          2 session cursor cache count
        666 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       1000 table fetch by rowid
        327 table fetch continued row
          3 user calls

The number of consistent gets has increased significantly to 666 (previously it was just 18).

Now we can attributed an increase of approximately 50% of the previous consistent gets (18 x 0.50 = 9) due to the 50% increase in table blocks required now to store the rows due to the increased row size.

We can also attribute an additional 327 consistent gets for the table fetch continued row value listed in the statistics, representing the extra consistent gets required to access the migrated rows from their new physical location.

But 18 + 9 + 327 = 354 still leaves us short of the new 666 consistent gets value.

The problem with having to visit another table block to get a row from its new location is that it means Oracle has to re-access again the original table block to get the next row (rather than reading multiple rows with the same consistent get).

So it’s actually approximately 2 x table fetch continued row, by which the number of consistent gets is going to increase when accessing migrated rows (noting that the last migrated row in a block will only incur a additional consistent get as the next table block accessed will differ regardless).

If we look at the new CBO cost for this plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'gz5u92hmjwz1h',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
____________________________________________________________________________________________________________________________________
SQL_ID gz5u92hmjwz1h, child number 0

-------------------------------------

select * from bowie where id between 1 and 1000

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    21 (100)|   1000 |00:00:00.01 |     666 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   1000 |   163K|      21 (0)|   1000 |00:00:00.01 |     666 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   1000 |       |       4 (0)|   1000 |00:00:00.01 |       4 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

 

We notice the CBO cost for this plan remains unchanged at 21.

This is totally to be expected, as the index statistics by which the cost of an index scan is calculated are unchanged.

Considering the rough “rule of thumb” is that the CBO cost of an index scan should be in the ball-park of the number of possible IOs, the fact the plan now uses 666 consistent gets highlights this cost of just 21 is no longer as accurate…

If we look at the second SQL that returns 4200 rows:

SQL> select * from bowie where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID c376kdhy5b0x9, child number 0
-------------------------------------
select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |   4200 |00:00:00.01 |    2771 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   4200 |00:00:00.01 |    2771 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          2 CPU used by this session
          2 CPU used when call started
          2 DB time
      14103 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
       2762 buffer is not pinned count
       7005 buffer is pinned count
        324 bytes received via SQL*Net from client
      461947 bytes sent via SQL*Net to client
           2 calls to get snapshot scn: kcmgss
           2 calls to kcmgcs
        2771 consistent gets
           1 consistent gets examination
           1 consistent gets examination (fastpath)
        2771 consistent gets from cache
        2770 consistent gets pin
        2770 consistent gets pin (fastpath)
           2 execute count
           1 index range scans
    22700032 logical read bytes from cache
        2770 no work - consistent read gets
          72 non-idle wait count
           2 opened cursors cumulative
           1 opened cursors current
           2 parse count (total)
           1 process last non-idle time
           2 session cursor cache count
        2771 session logical reads
           1 sorts (memory)
        2024 sorts (rows)
        4200 table fetch by rowid
        1366 table fetch continued row
           3 user calls

We again notice consistent gets has increased significantly to 2771 (previously it was just 68). Again, these additional consistent gets can not be attributed to the extra size of the table and the additional approximate 2 x 1366 table fetch continued row gets.

If we now look at the cost of this plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'c376kdhy5b0x9',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________________
____________

SQL_ID c376kdhy5b0x9, child number 0

-------------------------------------

select * from bowie where id between 1 and 4200

Plan hash value: 1405654398

---------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name       | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
---------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |            |      1 |        |       |    80 (100)|   4200 |00:00:00.01 |    2771 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |      1 |   4200 |   684K|      80 (0)|   4200 |00:00:00.01 |    2771 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
---------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

We again notice the CBO cost for this plan remains unchanged at 80, again totally expected as the underlying index statistics have remain unchanged after the update statement.

But again, not necessary as accurate a cost as it was previously…

 

If we repeat this demo, but this time on a table with ENABLE ROW MOVEMENT enabled:

SQL> create table bowie2(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0 ENABLE ROW MOVEMENT;

Table BOWIE2 created.

SQL> insert into bowie2 SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE2', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

SQL> create index bowie2_id_i on bowie2(id);

Index BOWIE2_ID_I created.

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE2';

   TABLE_NAME    NUM_ROWS    BLOCKS
_____________ ___________ _________
BOWIE2             200000      3268

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE2';

        INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
__________________ _________ ______________ ____________________
BOWIE2_ID_I                1            473                 3250

 

The table and index statistics are currently identical to the previous demo.

If we run the same two equivalent queries:

 

SQL> select * from bowie2 where id between 1 and 1000;

1,000 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID gtkw2704bxj7q, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 1000

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   1000 |00:00:00.01 |      18 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   1000 |   1000 |00:00:00.01 |      18 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   1000 |   1000 |00:00:00.01 |       4 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
       7909 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         16 buffer is not pinned count
       1985 buffer is pinned count
        325 bytes received via SQL*Net from client
     171306 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
         18 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
         18 consistent gets from cache
         17 consistent gets pin
         17 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     147456 logical read bytes from cache
         17 no work - consistent read gets
         37 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          2 session cursor cache count
         18 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       1000 table fetch by rowid
     3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'gtkw2704bxj7q',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID gtkw2704bxj7q, child number 0

-------------------------------------

select * from bowie2 where id between 1 and 1000

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |    21 (100)|   1000 |00:00:00.01 |      18 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   1000 |   108K|      21 (0)|   1000 |00:00:00.01 |      18 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   1000 |       |       4 (0)|   1000 |00:00:00.01 |       4 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)



SQL> select * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   4200 |00:00:00.01 |      68 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   4200 |00:00:00.01 |      68 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      11 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
          2 DB time
      13157 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
         59 buffer is not pinned count
       8342 buffer is pinned count
        325 bytes received via SQL*Net from client
     461838 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
         68 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
         68 consistent gets from cache
         67 consistent gets pin
         67 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
     557056 logical read bytes from cache
         67 no work - consistent read gets
         73 non-idle wait count
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          2 session cursor cache count
         68 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       4200 table fetch by rowid
          3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'25qktyn35b662',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0

-------------------------------------

select * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |    80 (100)|   4200 |00:00:00.01 |      68 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   455K|      80 (0)|   4200 |00:00:00.01 |      68 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |       |      11 (0)|   4200 |00:00:00.01 |      11 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

 

With identical table/index statistics, we notice as expected that both SQLs have the same consistent gets and CBO costs as with the previous demo.

If we now repeat the equivalent Update statement:

SQL> update bowie2 set name='THE RISE AND FALL OF BOWIE STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE2', estimate_percent=> null, no_invalidate=>false);

PL/SQL procedure successfully completed.

 

If we look at the table statistics:

SQL> select table_name, num_rows, blocks from user_tables where table_name='BOWIE2';

   TABLE_NAME   NUM_ROWS     BLOCKS
_____________ ___________ _________
BOWIE2             200000      4654

 

We notice the number of table blocks has increased to 4654 due to the increased row lengths, but not as much as with the previous demo (where table blocks increased to 4906) as in this scenario, Oracle does not have to store the row location pointers in the original blocks for the migrated rows.

If we look at the index statistics:

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes where table_name='BOWIE2';

    INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
______________ _________ ______________ ____________________
BOWIE2_ID_I            2            945               109061

We notice that these are substantially different from the first demo, where ROWIDs for migrated rows are not updated on the fly.

By now updating the ROWIDs, the indexes can possibly increase in size as they have to store both the previous and new ROWIDs in separate index entries and hence Oracle is more likely to perform additional index block splits (as I discussed in my previous post).

The LEAF_BLOCKS are now 945 (previously 473) and even the BLEVEL has increased from 1 to 2.

Additionally, and perhaps importantly for specific key indexes, the Clustering Factor value of indexes can also be impacted. By migrating rows and physically storing them in different locations, this can potentially detrimentally impact the tight clustering of rows based on specific column values.

The Clustering Factor for the index on the monotonically increased ID column has now increased significantly to 109061, up from the previously perfect 3250.

So columns that have naturally good clustering (e.g.: monotonically increasing values such as IDs and dates) or have been manually well clustered for performance purposes, can have the Clustering Factor of associated indexes detrimentally impacted by migrated rows.

If we re-run the first query:

SQL> select * from bowie2 where id between 1 and 1000;

1,000 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID gtkw2704bxj7q, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 1000

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   1000 |00:00:00.01 |     639 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   1000 |   1000 |00:00:00.01 |     639 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   1000 |   1000 |00:00:00.01 |       7 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          1 CPU used by this session
          1 CPU used when call started
          1 DB time
      15262 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
        634 buffer is not pinned count
       1367 buffer is pinned count
        325 bytes received via SQL*Net from client
     171421 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
        639 consistent gets
          2 consistent gets examination
          2 consistent gets examination (fastpath)
        639 consistent gets from cache
        637 consistent gets pin
        637 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
    5234688 logical read bytes from cache
        637 no work - consistent read gets
         38 non-idle wait count
          1 non-idle wait time
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 process last non-idle time
          2 session cursor cache count
        639 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
       1000 table fetch by rowid
          3 user calls

I discussed in a previous post how by updating the ROWIDs of migrated rows we can improve performance, as Oracle can go directly to the correct new physical location of a migrated row.

But for some specific indexes, where data clustering is crucial, and we have a significant number migrated rows, this might not necessarily be the case.

We can see consistent gets here has increased to 639 (previously is was just 21), and so not hugely different from the 666 consistent gets required to fetch the migrated rows when the ROWIDs were not updated in the first demo.

If we look at the CBO costings:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'gtkw2704bxj7q',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID gtkw2704bxj7q, child number 0

-------------------------------------

select * from bowie2 where id between 1 and 1000

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |   553 (100)|   1000 |00:00:00.01 |     639 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   1000 |   163K|     553 (0)|   1000 |00:00:00.01 |     639 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   1000 |       |       7 (0)|   1000 |00:00:00.01 |       7 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=1000)

 

We can see the CBO cost has increased significantly to 553 (previously it was just 21).

With a much increased Clustering Factor, this will obviously impact the CBO costs of associated index scans.

In very extreme cases, these possible changes in the Clustering Factor can even impact the viability of using the index.

If we re-run the second query returning the 4200 rows:

SQL> select * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 1495904576

----------------------------------------------------------------------------------------------
| Id | Operation                  | Name   | Starts | E-Rows | A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |        |      1 |        |   4200 |00:00:00.02 |    4572 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE2 |      1 |   4200 |   4200 |00:00:00.02 |    4572 |
----------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

We can see that the CBO has now chosen to perform a Full Table Scan (FTS), rather than use the now less efficient index to return this number of rows.

If we look at the CBO costings of this FTS plan:

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'25qktyn35b662',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
______________________________________________________________________________________________________________________
SQL_ID 25qktyn35b662, child number 0
-------------------------------------
select * from bowie2 where id between 1 and 4200

Plan hash value: 1495904576

-------------------------------------------------------------------------------------------------------------------
| Id | Operation                  | Name   | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT           |        |      1 |        |       |  1264 (100)|   4200 |00:00:00.02 |    4572 |
|* 1 |  TABLE ACCESS STORAGE FULL | BOWIE2 |      1 |   4200 |   684K|    1264 (1)|   4200 |00:00:00.02 |    4572 |
-------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("ID"<=4200 AND "ID">=1))
       filter(("ID"<=4200 AND "ID">=1))

 

The cost of the FTS plan is 1264.

If we compare this is a plan that used the index:

SQL> select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200;

4,200 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID bzm2vhchqpq7w, child number 0
-------------------------------------
select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |   4200 |00:00:00.01 |    2665 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   4200 |00:00:00.01 |    2665 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |   4200 |00:00:00.01 |      21 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=4200)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          2 CPU used by this session
          2 CPU used when call started
          2 DB time
      14531 RM usage
          3 Requests to/from client
          2 SQL*Net roundtrips to/from client
       2646 buffer is not pinned count
       5755 buffer is pinned count
        348 bytes received via SQL*Net from client
     462143 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       2665 consistent gets
         2 consistent gets examination
         2 consistent gets examination (fastpath)
      2665 consistent gets from cache
      2663 consistent gets pin
      2663 consistent gets pin (fastpath)
         2 execute count
         1 index range scans
  21831680 logical read bytes from cache
      2663 no work - consistent read gets
        73 non-idle wait count
         2 opened cursors cumulative
         1 opened cursors current
         2 parse count (total)
         3 process last non-idle time
         2 session cursor cache count
      2665 session logical reads
         1 sorts (memory)
      2024 sorts (rows)
      4200 table fetch by rowid
         3 user calls

SQL> SELECT * FROM TABLE(DBMS_XPLAN.display_cursor(sql_id=>'bzm2vhchqpq7w',format=>'ALLSTATS LAST +cost +bytes'));

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________________________________________
SQL_ID bzm2vhchqpq7w, child number 0

-------------------------------------

select /*+ index (bowie2) */ * from bowie2 where id between 1 and 4200

Plan hash value: 3243780227

----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows |E-Bytes| Cost (%CPU)| A-Rows | A-Time     | Buffers |
----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |       |  2314 (100)|   4200 |00:00:00.01 |    2665 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE2      |      1 |   4200 |   684K|    2314 (1)|   4200 |00:00:00.01 |    2665 |
|* 2 |   INDEX RANGE SCAN                   | BOWIE2_ID_I |      1 |   4200 |       |      22 (0)|   4200 |00:00:00.01 |      21 |
----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

2 - access("ID">=1 AND "ID"<=4200)

 

The cost of using the index to retrieve the 4200 rows is 2310, more than the 1264 of the FTS.

 

For the vast majority of indexes, updating the ROWIDs for migrated rows will result in better performance, as such indexes will be able to directly access the correct new physical location of migrated rows, rather than having to visit the original table block and then follow the stored pointer to the new table block.

But for some very specific indexes, where data clustering is crucial, AND we have a significant number migrated rows, this might not necessarily be the case. The performance benefit might be minimal at best.

That’s more than enough for one post ūüôā

In my next post, I’ll discuss how to potentially remedy these performance implications, both for tables with or without ENABLE TABLE MOVEMENT enabled…

Some Things To Consider Now ROWIDs Are Updated When Rows Migrate Part II (“Look Back In Anger”) February 24, 2023

Posted by Richard Foote in 19c, Autonomous Database, Autonomous Transaction Processing, BLEVEL, Changing ROWID, Index Internals, Leaf Blocks, Migrated Rows, Oracle, Oracle Blog, Oracle Cloud, Oracle General, Oracle Indexes, Oracle19c, Richard's Blog, ROWID.
4 comments

Some weekend reading…

In my previous post, I discussed a couple of potential areas of concern with the ROWIDs of migrated rows now being updated on the fly in Oracle Autonomous Databases, namely that it can cause issues with applications that reply on stored ROWIDs not changing and that there are additional resources required to maintain such ROWIDs in corresponding indexes, especially if there are many indexes on a table.

In this post, I’ll discuss another issue to just bear in mind with this change in behaviour.

To illustrate, I’ll run a demo similar to the previous post, first creating and populating a table with no ENABLE ROW MOVEMENT set:

SQL> create table ziggy(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0;

Table ZIGGY created.

SQL> insert into ziggy SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY');

PL/SQL procedure successfully completed.

SQL> analyze table ziggy compute statistics;

Table ZIGGY analyzed.

I’ll next create a bunch of indexes on the table:

SQL> create index ziggy_id_i on ziggy(id);

Index ZIGGY_ID_I created.

SQL> create index ziggy_code1_i on ziggy(code1);

Index ZIGGY_CODE1_I created.

SQL> create index ziggy_code2_i on ziggy(code2);

Index ZIGGY_CODE2_I created.

SQL> create index ziggy_code3_i on ziggy(code3);

Index ZIGGY_CODE3_I created.

SQL> create index ziggy_code4_i on ziggy(code4);

Index ZIGGY_CODE4_I created.

SQL> create index ziggy_code5_i on ziggy(code5);

Index ZIGGY_CODE5_I created.

SQL> create index ziggy_code6_i on ziggy(code6);

Index ZIGGY_CODE6_I created.

SQL> create index ziggy_code7_i on ziggy(code7);

Index ZIGGY_CODE7_I created.

SQL> create index ziggy_code8_i on ziggy(code8);

Index ZIGGY_CODE8_I created.

SQL> create index ziggy_code9_i on ziggy(code9);

Index ZIGGY_CODE9_I created.

SQL> create index ziggy_code10_i on ziggy(code10);

Index ZIGGY_CODE10_I created.

SQL> create index ziggy_code11_i on ziggy(code11);

Index ZIGGY_CODE11_I created.

SQL> create index ziggy_code12_i on ziggy(code12);

Index ZIGGY_CODE12_I created.

SQL> create index ziggy_code13_i on ziggy(code13);

Index ZIGGY_CODE13_I created.

SQL> create index ziggy_code14_i on ziggy(code14);

Index ZIGGY_CODE14_I created.

SQL> create index ziggy_code15_i on ziggy(code15);

Index ZIGGY_CODE15_I created.

SQL> create index ziggy_code16_i on ziggy(code16);

Index ZIGGY_CODE16_I created.

SQL> create index ziggy_code17_i on ziggy(code17);

Index ZIGGY_CODE17_I created.

SQL> create index ziggy_code18_i on ziggy(code18);

Index ZIGGY_CODE18_I created.

SQL> create index ziggy_code19_i on ziggy(code19);

Index ZIGGY_CODE19_I created.

SQL> create index ziggy_code20_i on ziggy(code20);

Index ZIGGY_CODE20_I created.

Let’s take note of the size of the table and its associated indexes:

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt
from user_tables where table_name='ZIGGY';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
ZIGGY              200000      3268              60          857            113            0

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes 
where table_name='ZIGGY';

       INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_________________ _________ ______________ ____________________
ZIGGY_CODE20_I            1            473                 3250
ZIGGY_ID_I                1            473                 3250
ZIGGY_CODE1_I             1            473                 3250
ZIGGY_CODE2_I             1            473                 3250
ZIGGY_CODE3_I             1            473                 3250
ZIGGY_CODE4_I             1            473                 3250
ZIGGY_CODE5_I             1            473                 3250
ZIGGY_CODE6_I             1            473                 3250
ZIGGY_CODE7_I             1            473                 3250
ZIGGY_CODE8_I             1            473                 3250
ZIGGY_CODE9_I             1            473                 3250
ZIGGY_CODE10_I            1            473                 3250
ZIGGY_CODE11_I            1            473                 3250
ZIGGY_CODE12_I            1            473                 3250
ZIGGY_CODE13_I            1            473                 3250
ZIGGY_CODE14_I            1            473                 3250
ZIGGY_CODE15_I            1            473                 3250
ZIGGY_CODE16_I            1            473                 3250
ZIGGY_CODE17_I            1            473                 3250
ZIGGY_CODE18_I            1            473                 3250
ZIGGY_CODE19_I            1            473                 3250

We next perform an update on the table that will increase the row size sufficiently to result in a bunch of migrated rows:

SQL> update ziggy set name='THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.
Elapsed: 00:00:07.716

I’ll then perform a COMMIT and look at differences in the table statistics:

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY');

PL/SQL procedure successfully completed.

SQL> analyze table ziggy compute statistics;

Table ZIGGY analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt 
from user_tables where table_name='ZIGGY';

   TABLE_NAME   NUM_ROWS     BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
ZIGGY              200000      4906              86          415            170        56186

 

We can see that there are indeed a bunch of migrated/chained rows, some 56186 of them.

We also notice that the size of the table has increased to 4906 blocks (previously is was 3268). This increase is in large part due to the increased size of the NAME column value, but also partly due to the storage allocated to pointers that are stored in the original block to denote the new location of the migrated rows (as discussed previously here).

If we look at the current state of the indexes:

SQL> select index_name, blevel, leaf_blocks, clustering_factor 
from user_indexes where table_name='ZIGGY';

       INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_________________ _________ ______________ ____________________
ZIGGY_CODE7_I             1            473                 3250
ZIGGY_CODE8_I             1            473                 3250
ZIGGY_CODE9_I             1            473                 3250
ZIGGY_CODE10_I            1            473                 3250
ZIGGY_CODE11_I            1            473                 3250
ZIGGY_CODE12_I            1            473                 3250
ZIGGY_CODE13_I            1            473                 3250
ZIGGY_CODE14_I            1            473                 3250
ZIGGY_CODE15_I            1            473                 3250
ZIGGY_CODE16_I            1            473                 3250
ZIGGY_CODE17_I            1            473                 3250
ZIGGY_CODE18_I            1            473                 3250
ZIGGY_CODE19_I            1            473                 3250
ZIGGY_CODE20_I            1            473                 3250
ZIGGY_ID_I                1            473                 3250
ZIGGY_CODE1_I             1            473                 3250
ZIGGY_CODE2_I             1            473                 3250
ZIGGY_CODE3_I             1            473                 3250
ZIGGY_CODE4_I             1            473                 3250
ZIGGY_CODE5_I             1            473                 3250
ZIGGY_CODE6_I             1            473                 3250

We notice that the indexes remain unchanged. As the table does NOT have ENABLE ROW MOVEMENT set, the indexes are NOT updated at all as part of the migrated row process (thus the same behaviour as non-autonomous database environments).

However, if I perform the same demo but instead perform a ROLLBACK of the transaction rather than the commit:

SQL> rollback;

Rollback complete.

Elapsed: 00:00:06.919

Note that the rollback takes 00:00:06.919 to complete.

If we now look at the size of the table and corresponding indexes:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY');

PL/SQL procedure successfully completed.

SQL> analyze table ziggy compute statistics;

Table ZIGGY analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt 
from user_tables where table_name='ZIGGY';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
ZIGGY              200000      4906              86         2899            113            0

We notice that the size of the table has increased to be the same 4906 blocks as when we performed the commit. The extra storage remains allocated even after the rollback operation.

That’s because Oracle does NOT deallocate any additional storage that might have been consumed during the original transaction. We notice that the AVG_SPACE has increased substantially as a result (now 2899, previously it was just 857).

If we look at the current state of the indexes after the rollback:

SQL> select index_name, blevel, leaf_blocks, clustering_factor 
from user_indexes where table_name='ZIGGY';

       INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
_________________ _________ ______________ ____________________
ZIGGY_CODE20_I            1            473                 3250
ZIGGY_ID_I                1            473                 3250
ZIGGY_CODE1_I             1            473                 3250
ZIGGY_CODE2_I             1            473                 3250
ZIGGY_CODE3_I             1            473                 3250
ZIGGY_CODE4_I             1            473                 3250
ZIGGY_CODE5_I             1            473                 3250
ZIGGY_CODE6_I             1            473                 3250
ZIGGY_CODE7_I             1            473                 3250
ZIGGY_CODE8_I             1            473                 3250
ZIGGY_CODE9_I             1            473                 3250
ZIGGY_CODE10_I            1            473                 3250
ZIGGY_CODE11_I            1            473                 3250
ZIGGY_CODE12_I            1            473                 3250
ZIGGY_CODE13_I            1            473                 3250
ZIGGY_CODE14_I            1            473                 3250
ZIGGY_CODE15_I            1            473                 3250
ZIGGY_CODE16_I            1            473                 3250
ZIGGY_CODE17_I            1            473                 3250
ZIGGY_CODE18_I            1            473                 3250
ZIGGY_CODE19_I            1            473                 3250

We notice that all the indexes again remain unchanged. As the indexes are not updated during the transaction, this is of course to be expected.

 

Let’s now repeat the same demo, but this time on a table with ENABLE ROW MOVEMENT set:

SQL> create table ziggy2(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, code11 number, code12 number, code13 number, code14 number, code15 number, code16 number, code17 number, code18 number, code19 number, code20 number, name varchar2(142)) PCTFREE 0 ENABLE ROW MOVEMENT;

Table ZIGGY2 created.

SQL> insert into ziggy2 SELECT rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, rownum, 'BOWIE' FROM dual CONNECT BY LEVEL <= 200000;

200,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY2');

PL/SQL procedure successfully completed.

SQL> analyze table ziggy2 compute statistics;

Table ZIGGY2 analyzed.

SQL> create index ziggy2_id_i on ziggy2(id);

Index ZIGGY2_ID_I created.

SQL> create index ziggy2_code1_i on ziggy2(code1);

Index ZIGGY2_CODE1_I created.

SQL> create index ziggy2_code2_i on ziggy2(code2);

Index ZIGGY2_CODE2_I created.

SQL> create index ziggy2_code3_i on ziggy2(code3);

Index ZIGGY2_CODE3_I created.

SQL> create index ziggy2_code4_i on ziggy2(code4);

Index ZIGGY2_CODE4_I created.

SQL> create index ziggy2_code5_i on ziggy2(code5);

Index ZIGGY2_CODE5_I created.

SQL> create index ziggy2_code6_i on ziggy2(code6);

Index ZIGGY2_CODE6_I created.

SQL> create index ziggy2_code7_i on ziggy2(code7);

Index ZIGGY2_CODE7_I created.

SQL> create index ziggy2_code8_i on ziggy2(code8);

Index ZIGGY2_CODE8_I created.

SQL> create index ziggy2_code9_i on ziggy2(code9);

Index ZIGGY2_CODE9_I created.

SQL> create index ziggy2_code10_i on ziggy2(code10);

Index ZIGGY2_CODE10_I created.

SQL> create index ziggy2_code11_i on ziggy2(code11);

Index ZIGGY2_CODE11_I created.

SQL> create index ziggy2_code12_i on ziggy2(code12);

Index ZIGGY2_CODE12_I created.

SQL> create index ziggy2_code13_i on ziggy2(code13);

Index ZIGGY2_CODE13_I created.

SQL> create index ziggy2_code14_i on ziggy2(code14);

Index ZIGGY2_CODE14_I created.

SQL> create index ziggy2_code15_i on ziggy2(code15);

Index ZIGGY2_CODE15_I created.

SQL> create index ziggy2_code16_i on ziggy2(code16);

Index ZIGGY2_CODE16_I created.

SQL> create index ziggy2_code17_i on ziggy2(code17);

Index ZIGGY2_CODE17_I created.

SQL> create index ziggy2_code18_i on ziggy2(code18);

Index ZIGGY2_CODE18_I created.

SQL> create index ziggy2_code19_i on ziggy2(code19);

Index ZIGGY2_CODE19_I created.

SQL> create index ziggy2_code20_i on ziggy2(code20);

Index ZIGGY2_CODE20_I created.

 

The table and indexes all have the same initial size as the previous example:

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt
from user_tables where table_name='ZIGGY2';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
ZIGGY2             200000      3268              60          857            113            0

SQL> select index_name, blevel, leaf_blocks, clustering_factor from user_indexes 
where table_name='ZIGGY2';

        INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
__________________ _________ ______________ ____________________
ZIGGY2_ID_I                1            473                 3250
ZIGGY2_CODE1_I             1            473                 3250
ZIGGY2_CODE2_I             1            473                 3250
ZIGGY2_CODE3_I             1            473                 3250
ZIGGY2_CODE4_I             1            473                 3250
ZIGGY2_CODE5_I             1            473                 3250
ZIGGY2_CODE6_I             1            473                 3250
ZIGGY2_CODE7_I             1            473                 3250
ZIGGY2_CODE8_I             1            473                 3250
ZIGGY2_CODE9_I             1            473                 3250
ZIGGY2_CODE10_I            1            473                 3250
ZIGGY2_CODE11_I            1            473                 3250
ZIGGY2_CODE12_I            1            473                 3250
ZIGGY2_CODE13_I            1            473                 3250
ZIGGY2_CODE14_I            1            473                 3250
ZIGGY2_CODE15_I            1            473                 3250
ZIGGY2_CODE16_I            1            473                 3250
ZIGGY2_CODE17_I            1            473                 3250
ZIGGY2_CODE18_I            1            473                 3250
ZIGGY2_CODE19_I            1            473                 3250
ZIGGY2_CODE20_I            1            473                 3250

 

If we now perform the same Update followed by the commit:

SQL> update ziggy2 set name='THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS';

200,000 rows updated.
Elapsed: 00:00:33.390

SQL> commit;

Commit complete.

If we look at the current size of the table after the update:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY2');

PL/SQL procedure successfully completed.

SQL> analyze table ziggy2 compute statistics;

Table ZIGGY2 analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt 
from user_tables where table_name='ZIGGY2';

   TABLE_NAME    NUM_ROWS   BLOCKS     EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
ZIGGY2             200000      4654              82          367            169            0

We notice it has increased to 4654 blocks (previously 3268). But the table is not quite as large in size as in the first demo, where the table grew to 4906 blocks (so 252 fewer blocks).

The increase in table size is now due entirely as a result in the increased NAME column values, as Oracle has not had to consume any storage for pointers in the original table blocks to denote a new location of the rows, as the ROWIDs are now updated in the indexes on the fly.

So this is a positive, a DECREASE in the comparative size of table after such updates that migrate rows.

And of course, there are no migrated/chained rows.

But if we look at the index statistics after the commit:

SQL> select index_name, blevel, leaf_blocks, clustering_factor 
from user_indexes where table_name='ZIGGY2';

        INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
__________________ _________ ______________ ____________________
ZIGGY2_ID_I                2            945               109061
ZIGGY2_CODE1_I             2            945               109061
ZIGGY2_CODE2_I             2            945               109061
ZIGGY2_CODE3_I             2            945               109061
ZIGGY2_CODE4_I             2            945               109061
ZIGGY2_CODE5_I             2            945               109061
ZIGGY2_CODE6_I             2            945               109061
ZIGGY2_CODE7_I             2            945               109061
ZIGGY2_CODE8_I             2            945               109061
ZIGGY2_CODE9_I             2            945               109061
ZIGGY2_CODE10_I            2            945               109061
ZIGGY2_CODE11_I            2            945               109061
ZIGGY2_CODE12_I            2            945               109061
ZIGGY2_CODE13_I            2            945               109061
ZIGGY2_CODE14_I            2            945               109061
ZIGGY2_CODE15_I            2            945               109061
ZIGGY2_CODE16_I            2            945               109061
ZIGGY2_CODE17_I            2            945               109061
ZIGGY2_CODE18_I            2            945               109061
ZIGGY2_CODE19_I            2            945               109061
ZIGGY2_CODE20_I            2            945               109061

 

We notice that ALL the indexes have significantly increased in size and now have 945 leaf blocks (previously it was just 473 leaf blocks). Additionally as a result of this increase in index size, the BLEVEL of the indexes has also increased and are now 2 (previously it was 1).

Here’s the thing. As I’ve discussed many times before, when Oracle performs an “Update” of an index entry, this is actually implemented as a Delete/Insert operation. By changing the ROWID of an index entry, Oracle first deletes the original index entry and inserts a new index entry with the new ROWID. So the previous index entry remains (with the space likely eventually reused by another new index entry in the future).

So these “on the fly” updates of the indexes to keep the ROWIDs current due to row migrations increases the likelihood of index block splits and the subsequent increase in index storage allocations.

In very rare, extreme cases (and this demo is indeed an extreme case as I’m updating all rows in my table), this extra index storage could potentially result in an increase in the index BLEVEL.

However, in most scenarios, this increase in index storage is likely to be moderate and result in extra index storage that will eventually be consumed by subsequent new rows anyways.

If instead of the commit operation, we instead performed a rollback:

SQL> rollback;

Rollback complete.

Elapsed: 00:00:36.639

We notice that the rollback takes considerably longer at 00:00:36.639 (previously in the first demo, it was just 00:00:06.919).

As the ROWIDs are now all updated on the fly on all the corresponding indexes, there’s that much more data that needs to be rolled back within these indexes.

If we look at the current size of the table after the rollback:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY2');

PL/SQL procedure successfully completed.

SQL> analyze table ziggy2 compute statistics;

Table ZIGGY2 analyzed.

SQL> select table_name, num_rows, blocks, empty_blocks, avg_space, avg_row_len, chain_cnt
from user_tables where table_name='ZIGGY2';

   TABLE_NAME    NUM_ROWS    BLOCKS    EMPTY_BLOCKS    AVG_SPACE    AVG_ROW_LEN    CHAIN_CNT
_____________ ___________ _________ _______________ ____________ ______________ ____________
ZIGGY2             200000      4654              82         2823            113            0

We notice it has increased to the same 4654 blocks as with the commit. The extra storage remains allocated even after the rollback operation.

That’s again because Oracle does NOT deallocate any additional storage that might have been consumed during the original transaction. We notice that the AVG_SPACE has again increased substantially as a result (now 2823, previously it was just 857).

If we look at the current state of the indexes after the rollback:

 

SQL> select index_name, blevel, leaf_blocks, clustering_factor 
from user_indexes where table_name='ZIGGY2';

        INDEX_NAME    BLEVEL    LEAF_BLOCKS    CLUSTERING_FACTOR
__________________ _________ ______________ ____________________
ZIGGY2_ID_I                2            945                 3250
ZIGGY2_CODE1_I             2            945                 3250
ZIGGY2_CODE2_I             2            945                 3250
ZIGGY2_CODE3_I             2            945                 3250
ZIGGY2_CODE4_I             2            945                 3250
ZIGGY2_CODE5_I             2            945                 3250
ZIGGY2_CODE6_I             2            945                 3250
ZIGGY2_CODE7_I             2            945                 3250
ZIGGY2_CODE8_I             2            945                 3250
ZIGGY2_CODE9_I             2            945                 3250
ZIGGY2_CODE10_I            2            945                 3250
ZIGGY2_CODE11_I            2            945                 3250
ZIGGY2_CODE12_I            2            945                 3250
ZIGGY2_CODE13_I            2            945                 3250
ZIGGY2_CODE14_I            2            945                 3250
ZIGGY2_CODE15_I            2            945                 3250
ZIGGY2_CODE16_I            2            945                 3250
ZIGGY2_CODE17_I            2            945                 3250
ZIGGY2_CODE18_I            2            945                 3250
ZIGGY2_CODE19_I            2            945                 3250
ZIGGY2_CODE20_I            2            945                 3250

We notice that they all remain at their increased size of 945 leaf blocks and with the Blevel of 2.

Again, when Oracle performs the rollback, Oracle does NOT undo all the index block splits and leaves all the additional storage allocated to the indexes.

So, just a word of caution.

Updating all the ROWIDs on the fly when a row migrates does not come for free. There’s additional resources that need to be consumed during these updates AND there is a potential issue with indexes having to perform additional index block splits and consume additional storage (at least immediately) after such operations.

If you have applications that makes bulk changes to data that can result in rollbacks, again, it’s just worth noting the extra storage that may be consumed as a result (until the additional data is finally added to the table).

Yes, index rebuilds can be performed to reduce the subsequent size of these inflated indexes.

BUT, for those of you with sharp eyes, you might also have noted another potential issue with this new behaviour, which I’ll discuss in my next post… ūüôā

Advantages To Updating ROWID When Rows Migrate (“Fantastic Voyage”) February 13, 2023

Posted by Richard Foote in 19c, Autonomous Database, Autonomous Transaction Processing, Changing ROWID, Migrated Rows, Oracle, Oracle Blog, Oracle Cloud, Oracle General, Oracle Statistics, Performance Tuning, ROWID.
1 comment so far

In my last post, I discussed how with Oracle Autonomous Databases, when a row migrates and the ENABLE ROW MOVEMENT clause is specified for a table (be it Partitioned or Non-Partitioned), the ROWID of such rows are now updated on the fly. In non-autonomous database environments, such ROWIDs would NOT be updated, with a pointer in the previous table blocks pointing to the new physical location of the migrated row (as I previously discussed here).

So what’s the advantage of this new behaviour? Why might Oracle have made this change?

Well, the obvious benefit is that subsequent index scans that need to access migrated rows will have ROWIDs that directly point to the new, correct physical location of the row. Previously, indexes still had ROWIDs that reference the original row location and an additional table block access was required to access the row in its new physical location.

To illustrate this reduction in table block accesses, I’ll run a simple SQL that reads all 10,000 rows via an index from the BOWIE table that did not have the ENABLE ROW MOVEMENT clause when most rows were updated with significantly increased row sizes (as created in my previous post):

SQL> select /*+ index (bowie) */ * from bowie where id between 1 and 10000;

10,000 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID 5gum0cs9pb3zf, child number 0
-------------------------------------
select /*+ index (bowie) */ * from bowie where id between 1 and 10000

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers  |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |            |      1 |        |  10000 |00:00:00.03 |    18866 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED| BOWIE      |      1 |  10000 |  10000 |00:00:00.03 |    18866 |
|* 2 |   INDEX RANGE SCAN                  | BOWIE_ID_I |      1 |  10000 |  10000 |00:00:00.01 |      688 |
------------------------------------------------------------------------------------------------------------

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=10000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          9 CPU used by this session
          9 CPU used when call started
         13 DB time
     136499 RM usage
        707 Requests to/from client
        706 SQL*Net roundtrips to/from client
      19508 buffer is not pinned count
      10216 buffer is pinned count
       5273 bytes received via SQL*Net from client
     201460 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
      18866 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
      18866 consistent gets from cache
      18865 consistent gets pin
      18865 consistent gets pin (fastpath)
          1 cursor authentications
          2 execute count
          2 global enqueue gets sync
          2 global enqueue releases
          1 index range scans
  154550272 logical read bytes from cache
      18865 no work - consistent read gets
        721 non-idle wait count
          1 non-idle wait time
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
          1 parse time cpu
         20 process last non-idle time
      18866 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
      10000 table fetch by rowid
       9059 table fetch continued row
        707 user calls

I’m using a SQLcl connection to my autonomous database here to more easily list a bunch of useful statistics.

The 2 statistics I just want to highlight are the number of consistent gets (18866) and the number of table fetch continued rows (9059).

If we compare this with the exactly same SQL on the exact same data, but this time on the BOWIE2 table that did have ENABLE ROW MOVEMENT enabled and thus had the ROWIDs updated on the fly when most of its rows migrated:

SQL> select /*+ index (bowie2) */ * from bowie2 where id between 1 and 10000;

10,000 rows selected.

PLAN_TABLE_OUTPUT
________________________________________________________________________________________________________________
SQL_ID c346wwr8f4hfu, child number 0
-------------------------------------
select /*+ index (bowie2) */ * from bowie2 where id between 1 and 10000

Plan hash value: 3243780227

-------------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers  |
-------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |             |      1 |        |  10000 |00:00:00.02 |     4443 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED| BOWIE2      |      1 |  10000 |  10000 |00:00:00.02 |     4443 |
|* 2 |   INDEX RANGE SCAN                  | BOWIE2_ID_I |      1 |  10000 |  10000 |00:00:00.01 |      710 |
-------------------------------------------------------------------------------------------------------------

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=10000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          8 CPU used by this session
          8 CPU used when call started
         13 DB time
        340 OS Involuntary context switches
       2532 OS Page reclaims
         14 OS System time used
         45 OS User time used
       2425 OS Voluntary context switches
     188462 RM usage
        707 Requests to/from client
        706 SQL*Net roundtrips to/from client
       2244 Server Data Segments In
       2244 Server Data Segments Out
      62270 Server Elapsed Time (msec) Last Data Sent
   35307000 Server Time (usec) Busy Sending Data
       2596 Server Time (usec) Round Trip Time
         72 Server Time (usec) Round Trip Time Variance
     869824 Server Total Bytes Acked
      40188 Server Total Bytes Received
       5063 buffer is not pinned count
      15602 buffer is pinned count
       5274 bytes received via SQL*Net from client
     201450 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       4443 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
       4443 consistent gets from cache
       4442 consistent gets pin
       4442 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
   36397056 logical read bytes from cache
       4442 no work - consistent read gets
        720 non-idle wait count
          5 non-idle wait time
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
        173 process last non-idle time
         14 session cursor cache count
          1 session cursor cache hits
       4443 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
      10000 table fetch by rowid
        707 user calls

In this case, the number of consistent gets (4443) is much less than the previous 18866 and there are no table fetch continued row listed.

Now just a couple of points to make here.

Firstly, this is a tiny table and so the actual overall benefits here are relatively trivial, especially considering this all sits on an Exadata platform, where much of this data is effectively cached.

But as the saying goes, data may be updated once but accessed 10s of 1000s of times and so tiny savings can be considerable if SQLs are executed very frequently and/or tables are much larger and so less well cached within the database or the Exadata storage cells as a result.

You can determine if there’s potentially a migrated row problem by checking out CHAIN_CNT after analyzing a table:

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> analyze table bowie2 compute statistics;

Table BOWIE2 analyzed.

SQL> select table_name, chain_cnt from user_tables where table_name in ('BOWIE', 'BOWIE2');

   TABLE_NAME    CHAIN_CNT
_____________ ____________
BOWIE                 9059
BOWIE2                   0

 

Note that CHAIN_CNT can also be a result of large rows that simply can’t fit within a data block, so you need to know your data to fully appreciate this figure. In this scenario, all 9059 chained rows are indeed associated with the migration of rows when the row length was substantially increased by an UPDATE statement.

A method of addressing ROWIDs that still point to the original table block following a row migration, is to reorganise the table (which can now be performed ONLINE):

SQL> alter table bowie move online;

Table BOWIE altered.

SQL> analyze table bowie compute statistics;

Table BOWIE analyzed.

SQL> select table_name, chain_cnt from user_tables where table_name in ('BOWIE', 'BOWIE2');

   TABLE_NAME    CHAIN_CNT
_____________ ____________
BOWIE2                   0
BOWIE                    0

As we can see, there are no longer any Chained Rows associated with the previously migrated rows.

This will now reduce the consistent gets and the overall overheads associated with accessing these previously migrated (chained) rows via an index, as we can now directly access their current table blocks via the correct ROWIDs.

If we now re-run the first SQL:

SQL> select /*+ index (bowie) */ * from bowie where id between 1 and 10000;

10,000 rows selected.

PLAN_TABLE_OUTPUT
_______________________________________________________________________________________________________________
SQL_ID 5gum0cs9pb3zf, child number 0
-------------------------------------
select /*+ index (bowie) */ * from bowie where id between 1 and 10000

Plan hash value: 1405654398

------------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name       | Starts | E-Rows | A-Rows | A-Time     | Buffers  |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |            |      1 |        |  10000 |00:00:00.02 |     2677 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED| BOWIE      |      1 |  10000 |  10000 |00:00:00.02 |     2677 |
|* 2 |   INDEX RANGE SCAN                  | BOWIE_ID_I |      1 |  10000 |  10000 |00:00:00.01 |      688 |
------------------------------------------------------------------------------------------------------------

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________
Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID">=1 AND "ID"<=10000)

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

Statistics
-----------------------------------------------------------
          4 CPU used by this session
          4 CPU used when call started
       1850 Cached Commit SCN referenced
          5 DB time
     150963 RM usage
        707 Requests to/from client
        706 SQL*Net roundtrips to/from client
       3319 buffer is not pinned count
      17346 buffer is pinned count
       5273 bytes received via SQL*Net from client
     201475 bytes sent via SQL*Net to client
          2 calls to get snapshot scn: kcmgss
          2 calls to kcmgcs
       2677 consistent gets
          1 consistent gets examination
          1 consistent gets examination (fastpath)
       2677 consistent gets from cache
       2676 consistent gets pin
       2676 consistent gets pin (fastpath)
          2 execute count
          1 index range scans
   21929984 logical read bytes from cache
       2676 no work - consistent read gets
        720 non-idle wait count
          2 non-idle wait time
          2 opened cursors cumulative
          1 opened cursors current
          2 parse count (total)
         15 process last non-idle time
          1 session cursor cache count
          1 session cursor cache hits
       2677 session logical reads
          1 sorts (memory)
       2024 sorts (rows)
      10000 table fetch by rowid
        707 user calls

The consistent gets has gone way down to just 2677, down from the previous 18866…

In my next post, I’ll highlight some of the disadvantages with this new approached on how autonomous databases handle migrated rows in relation to now maintaining ROWIDs on the fly (and the discerning reader might even find a clue or two within this very post)… ūüôā

When Does A ROWID Change? Part V (“The Wedding”) February 7, 2023

Posted by Richard Foote in 19c, 19c New Features, Autonomous Database, Autonomous Transaction Processing, Changing ROWID, Index Internals, Oracle, Oracle Cloud, Oracle General, Oracle Indexes, Richard's Blog, ROWID.
6 comments

It’s been a busy period. First Christmas, then the wedding of my beautiful daughter, then a nice get-a-way to get over the wedding of my beautiful daughter, and then a busy period with work.

But now I’m back ūüôā

In this series on when does a ROWID change, I previously discussed how a row is generally ‚Äúmigrated‚ÄĚ, but the ROWID remains unchanged, when a row is updated such that it can no longer fit within its current block. Hence the general rule has always been that the ROWID of a row does not change (although I also previously discussed various exceptions to this general rule).

However, things change in an Oracle Autonomous Database, when looking at the behaviour of the ROWID after a row migrates…

To illustrate, I’m going to run a similar demo as previously, but this time within (one of my free) Transaction Processing Autonomous Databases. I start by creating and populating a basic table, with the PCTFREE set to 0 to ensure my data blocks are initially nicely filled:

SQL> create table bowie (id number, name varchar2(142)) pctfree 0;

Table BOWIE created.

SQL> insert into bowie select rownum, 'BOWIE' from dual connect by level <=10000;

10,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

SQL> create index bowie_id_i on bowie(id);

Index BOWIE_ID_I created.

 

Let’s just take note of a few random ROWID values:

SQL> select id, rowid from bowie where id in (42, 424, 4242) order by id;

     ID                 ROWID
_______ _____________________
     42 AAApUqAAAAACKD/AAp
    424 AAApUqAAAAACKD/AGn
   4242 AAApUqAAAAACKGEAHF

 

I’ll next update the rows with the NAME column value that is significantly larger than previously, to force the migration of many of my existing rows:

SQL> update bowie set name='THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS';

10,000 rows updated.

SQL> commit;

Commit complete.

 

If we now look at the ROWID of these same rows:

SQL> select id, rowid from bowie where id in (42, 424, 4242) order by id;

     ID                 ROWID
_______ _____________________
     42 AAApUqAAAAACKD/AAp
    424 AAApUqAAAAACKD/AGn
   4242 AAApUqAAAAACKGEAHF

 

We notice that they have NOT changed.

So the default behaviour in an Autonomous Database is as it has always been, that even though rows are migrated, it does NOT change the resultant ROWIDs.

This is an important point if you do NOT want your ROWIDs to change when a row is migrated (in the example perhaps that you have applications that explicitly use stored ROWIDs and are dependant on them not changing).

I’ll next run the same demo again, but with one key difference. This time, I’m explicitly setting ENABLE ROW MOVEMENT in the creation of my non-partitioned table:

 

SQL> create table bowie2 (id number, name varchar2(142)) pctfree 0 enable row movement;

Table BOWIE2 created.

SQL> insert into bowie2 select rownum, 'BOWIE' from dual connect by level <=10000;

10,000 rows inserted.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE2');

PL/SQL procedure successfully completed.

SQL> create index bowie2_id_i on bowie2(id);

Index BOWIE2_ID_I created.

 

Let’s again have a look at the current ROWID of a few random rows:

SQL> select id, rowid from bowie2 where id in (42, 424, 4242) order by id;

     ID                 ROWID
_______ _____________________
     42 AAApUxAAAAACKIfAAp
    424 AAApUxAAAAACKIfAGn
   4242 AAApUxAAAAACKIkAHF

 

Let’s now perform the same update as before, forcing the migration of rows in the table:

SQL> update bowie2 set name='THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS';

10,000 rows updated.

SQL> commit;

Commit complete.

 

Now, as I discussed previously, in a non-autonomous environment, on a non-partitioned table, ENABLE ROW MOVEMENT would have no impact in this scenario and the ROWIDs would NOT have changed for any of these migrated rows.

But if we look at the ROWIDs in this autonomous database environment:

SQL> select id, rowid from bowie2 where id in (42, 424, 4242) order by id;

     ID                 ROWID
_______ _____________________
     42 AAApUxAAAAACKJqABX
    424 AAApUxAAAAACKJuAAJ
   4242 AAApUxAAAAACKMJABN

We can see that they have all indeed changed.

When a row migrates in an autonomous database environment AND we set the ENABLE ROW MOVEMENT on a non-partitioned table, the ROWIDs are indeed updated on the fly.

If we had an application that relied on these ROWIDs not changing:

SQL> select id from bowie2 where rowid in ('AAApUxAAAAACKIfAAp', 'AAApUxAAAAACKIfAGn', 'AAApUxAAAAACKIkAHF');

no rows selected

Well, the results would be “disappointing” (or downright disastrous if they then happen to select completed different rows)…

However, if we use an indexed key to fetched the required rows:

SQL> select * from bowie2 where id in (42, 424, 4242);

     ID                                                             NAME
_______ ________________________________________________________________
     42 THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS
    424 THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS
   4242 THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS

PLAN_TABLE_OUTPUT
_________________________________________________________________________________________________________________
SQL_ID atz1zbtyptu6n, child number 0
-------------------------------------
select * from bowie2 where id in (42, 424, 4242)

Plan hash value: 1734578469

--------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name        | Starts | E-Rows | A-Rows | A-Time     | Buffers  |
--------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |             |      1 |        |      3 |00:00:00.01 |        8 |
|  1 |  INLIST ITERATOR                     |             |      1 |        |      3 |00:00:00.01 |        8 |
|  2 |   TABLE ACCESS BY INDEX ROWID BATCHED| BOWIE2      |      3 |      3 |      3 |00:00:00.01 |        8 |
|* 3 |    INDEX RANGE SCAN                  | BOWIE2_ID_I |      3 |      3 |      3 |00:00:00.01 |        5 |
--------------------------------------------------------------------------------------------------------------

PLAN_TABLE_OUTPUT
_____________________________________________________________________________________________________

Predicate Information (identified by operation id):
---------------------------------------------------

   3 - access(("ID"=42 OR "ID"=424 OR "ID"=4242))

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of no expensive parallel operation

 

They thankfully have indeed been correctly updated within the index and can successfully access the required rows.

So the decision is entirely yours. If you want to keep to the existing behaviour in relation to the non-changing of ROWIDs of migrated rows, do NOT set ENABLE ROW MOVEMENT on the tables in the autonomous database environments.

If you do want to adopt this new behaviour, then simply set ENABLE ROW MOVEMENT.

I’ll discuss the advantages and disadvantages of this new behaviour in future posts…

When Does A ROWID Change? Part IV (“Mass Production”) December 21, 2022

Posted by Richard Foote in Attribute Clustering, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, Changing ROWID, Clustering Factor, Data Clustering, Flashback, Move Partitions, Oracle, Oracle Blog, Oracle Cloud, Oracle General, Oracle Indexes, Partitioning, Richard's Blog, ROWID.
1 comment so far

In Part II in this series, I discussed how the update of the partitioned key column of a row that results in the row being moved to a different partition, will result in the ROWID of such rows changing.

However, there a quite a number of other user initiated actions in which ROWIDs can easily change (as indeed discussed in Connor McDonald’s video on this subject).

Some of these include:

  • Moving a table or partition, as this results in the segment being reorganised, with all associated rows being physically relocated and their associated ROWIDs changing
  • Altering a non-partitioned table such that it be now be partitioned, which again results in the physical relocation of all rows and their ROWIDs changing (which BTW, can potentially occur on a Autonomous Database without any user intervention)
  • Altering the partitioning strategy of a partitioned table, again changes the physical location of all rows
  • Hybrid Columnar Compression (HCC), which by packing rows more tightly, can more likely result in the physical relocation of a row during subsequent DML statements
  • Altering a table to Shrink Space, which attempts to move rows between table blocks to pack rows more tightly, again potentially resulting in rows physically moving and the changing of their associated ROWIDs
  • Flashback of a table, which results in rows being deleted and inserted and hence the change of their associated ROWIDs

I’ll illustrate an example of all this, with one of the key reasons why you may want to re-organise a table (and implicitly change all the ROWIDs of a table).

I’ll start by creating and populating a simple little table, with a CODE column that has very poorly clustered data:

SQL> create table bowie (id number, code number, name varchar2(42));

Table created.

SQL> insert into bowie select rownum, mod(rownum, 500), 'DAVID BOWIE' from dual connect by level <=1000000;

1000000 rows created.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

Let’s now create an index on this CODE column:

SQL> create index bowie_code_i on bowie(code);

Index created.

We take note of the ROWIDs of a few random rows:

SQL> select id, rowid from bowie where id in (42, 4242, 424242) order by id;

        ID ROWID
---------- ------------------
        42 AAASn1AAMAAAgB2AAp
      4242 AAASn1AAMAAAgCHACL
    424242 AAASn1AAMAAAgbtAAJ

If we run a simple query with a predicate based on the CODE column:

SQL> select * from bowie where code=42;

2000 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 1845943507

---------------------------------------------------------------------------
| Id  | Operation          | Name  | Rows | Bytes | Cost (%CPU)| Time     |
---------------------------------------------------------------------------
|   0 | SELECT STATEMENT   |       | 2000 | 42000 |    1004 (2)| 00:00:01 |
| * 1 |  TABLE ACCESS FULL | BOWIE | 2000 | 42000 |    1004 (2)| 00:00:01 |
---------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter("CODE"=42)

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
       3596 consistent gets
          0 physical reads
          0 redo size
      20757 bytes sent via SQL*Net to client
         52 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
       2000 rows processed

We notice the CBO has chosen to ignore the index and use a FTS instead, even though only 2000 rows in a 1M row table (just 0.2%) are returned.

Why?

Because the clustering of the CODE data is terrible, with the required values littered throughout the table. If we look at the Clustering Factor of the index:

SQL> select index_name, leaf_blocks, clustering_factor from user_indexes where index_name='BOWIE_CODE_I';

INDEX_NAME   LEAF_BLOCKS CLUSTERING_FACTOR
------------ ----------- -----------------
BOWIE_CODE_I        2063           1000000

We notice the index has the worst possible Clustering Factor value of 1000000.

So to improve the performance of this (say critical) query, we can add a Clustering Attribute to this table based on the CODE column and then reorganise the table:

SQL> alter table bowie add clustering by linear order (code);

Table altered.

SQL> alter table bowie move online;

Table altered.

If we now look at the Clustering Factor of the index:

SQL> select index_name, leaf_blocks, clustering_factor from user_indexes where index_name='BOWIE_CODE_I';

INDEX_NAME   LEAF_BLOCKS CLUSTERING_FACTOR
------------ ----------- -----------------
BOWIE_CODE_I        2063              3568

We can see it has substantially improved, down to just 3568 from the previous 1000000 value, as the data is now perfectly clustered based on the CODE column.

If we now re-run the query:

SQL> select * from bowie where code=42;

2000 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 853003755

----------------------------------------------------------------------------------------------------
| Id  | Operation                            | Name         | Rows | Bytes | Cost (%CPU)| Time     |
----------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                     |              | 2000 | 42000 |      15 (0)| 00:00:01 |
|   1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE        | 2000 | 42000 |      15 (0)| 00:00:01 |
| * 2 |   INDEX RANGE SCAN                   | BOWIE_CODE_I | 2000 |       |       7 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("CODE"=42) 

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
         17 consistent gets
          0 physical reads
          0 redo size
      50735 bytes sent via SQL*Net to client
         52 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
       2000 rows processed

The CBO now choses to use the index and the query is much more efficient as a result (consistent gets down to just 17 from the previous 3596).

So all is now much better, except for any application that was reliant on using ROWIDs to fetch the data, as all ROWIDs have now changed:

SQL> select id, rowid from bowie where id in (42, 4242, 424242) order by id;

        ID ROWID
---------- ------------------
        42 AAASn6AAMAAAACvAEf
      4242 AAASn6AAMAAAiRaAA4
    424242 AAASn6AAMAAAiRWAEQ

So there are many ways in which the ROWID of a row can potentially change.

And now there’s another key manner in which a ROWID can very easily change in Oracle Autonomous Database environments, as I’ll next discuss…

When Does A ROWID Change? Part III (“Arriving Somewhere But Not Here”) December 13, 2022

Posted by Richard Foote in Autonomous Database, Changing ROWID, Index Internals, Local Indexes, Oracle, Oracle Blog, Oracle Cloud, Oracle General, Oracle Indexes, Oracle Indexing Internals Webinar, Partitioning, Performance Tuning, Richard's Blog, ROWID, Secondary Indexes.
2 comments

In Part II of this series, I discussed how updating the Partitioned Key of a row from a Partitioned table will result in the row physically moving and the associated ROWID changing.

One of the reasons why changing the ROWID has historically has not been the default behaviour and requires the explicit setting of the ENABLE ROW MOVEMENT clause for Partitioned tables is because changing a ROWID comes at a cost. The cost being not only having to delete and re-insert the row within the table, but also delete and re-insert the associated index entry for each corresponding index on the table.

To illustrate, I’m going to create and populate another simple little Partitioned Table:

SQL> CREATE TABLE big_bowie2(id number, code1 number, code2 number, code3 number, code4 number, code5 number, code6 number, code7 number, code8 number, code9 number, code10 number, release_date date, name varchar2(42)) PARTITION BY RANGE (release_date)
(PARTITION ALBUMS_2021 VALUES LESS THAN (TO_DATE('01-JAN-2022', 'DD-MON-YYYY')),
PARTITION ALBUMS_2022 VALUES LESS THAN (MAXVALUE)) ENABLE ROW MOVEMENT;

Table created.

SQL> INSERT INTO big_bowie2 SELECT rownum, mod(rownum,1000), mod(rownum,1000), mod(rownum,1000), mod(rownum,100
ownum,1000), mod(rownum,1000), mod(rownum,1000), mod(rownum,1000), mod(rownum,1000), mod(rownum,1000), sysdate-
m,500), 'DAVID BOWIE' FROM dual CONNECT BY LEVEL <= 10000;

10000 rows created.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=> null, tabname=> 'BIG_BOWIE2');

PL/SQL procedure successfully completed.

I’m now going to create a number of basic Global indexes on this table:

SQL> create index big_bowie2_id_i on big_bowie2(id);

Index created.

SQL> create index big_bowie2_code1_i on big_bowie2(code1);

Index created.

SQL> create index big_bowie2_code2_i on big_bowie2(code2);

Index created.

SQL> create index big_bowie2_code3_i on big_bowie2(code3);

Index created.

SQL> create index big_bowie2_code4_i on big_bowie2(code4);

Index created.

SQL> create index big_bowie2_code5_i on big_bowie2(code5);

Index created.

SQL> create index big_bowie2_code6_i on big_bowie2(code6);

Index created.

SQL> create index big_bowie2_code7_i on big_bowie2(code7);

Index created.

SQL> create index big_bowie2_code8_i on big_bowie2(code8);

Index created.

SQL> create index big_bowie2_code9_i on big_bowie2(code9);

Index created.

SQL> create index big_bowie2_code10_i on big_bowie2(code10);

Index created.

If I run a simple single row UPDATE that updates a non-indexed, non-partitioned key column:

SQL> update big_bowie2 set name='ZIGGY STARDUST' where id=424;

1 row updated.

Execution Plan
----------------------------------------------------------
Plan hash value: 3590621923

-------------------------------------------------------------------------------------
| Id | Operation          | Name            | Rows | Bytes | Cost (%CPU) | Time     |
-------------------------------------------------------------------------------------
|  0 | UPDATE STATEMENT   |                 |    1 |    16 |       2 (0) | 00:00:01 |
|  1 |  UPDATE            | BIG_BOWIE2      |      |       |             |          |
|* 2 |   INDEX RANGE SCAN | BIG_BOWIE2_ID_I |    1 |    16 |       1 (0) | 00:00:01 |
-------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID"=424)

Statistics
----------------------------------------------------------
          1 recursive calls
          1 db block gets
          2 consistent gets
          0 physical reads
        328 redo size
        204 bytes sent via SQL*Net to client
         41 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

We can see that the number of db block gets is just 1 and consistent gets just 2, as only the one table block needs to be updated and easily accessed via the index on the ID column.

If we now run a single row update of an indexed column:

SQL> update big_bowie2 set code1=42 where id = 424;

1 row updated.

Execution Plan
----------------------------------------------------------
Plan hash value: 3590621923

-------------------------------------------------------------------------------------
| Id | Operation          | Name            | Rows | Bytes | Cost (%CPU) | Time     |
-------------------------------------------------------------------------------------
|  0 | UPDATE STATEMENT   |                 |    1 |     8 |       2 (0) | 00:00:01 |
|  1 |  UPDATE            | BIG_BOWIE2      |      |       |             |          |
|* 2 |   INDEX RANGE SCAN | BIG_BOWIE2_ID_I |    1 |     8 |       1 (0) | 00:00:01 |
-------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID"=424)

Statistics
----------------------------------------------------------
          1 recursive calls
          5 db block gets
          2 consistent gets
          1 physical reads
        948 redo size
        204 bytes sent via SQL*Net to client
         41 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          1 sorts (memory)
          0 sorts (disk)
          1 rows processed

We can see that the number of db block gets increases to 5, as not only does the table block have to be updated but so also do the associated index blocks.

If we now finally run a single row update on the partitioned table’s partition key column that results in the row having to physically move to another partition:

SQL> update big_bowie2 set release_date='06-DEC-22' where id = 424;

1 row updated.

Execution Plan
----------------------------------------------------------
Plan hash value: 3590621923

-------------------------------------------------------------------------------------
| Id | Operation          | Name            | Rows | Bytes | Cost (%CPU) | Time     |
-------------------------------------------------------------------------------------
|  0 | UPDATE STATEMENT   |                 |    1 |    64 |       2 (0) | 00:00:01 |
|  1 |  UPDATE            | BIG_BOWIE2      |      |       |             |          |
|* 2 |   INDEX RANGE SCAN | BIG_BOWIE2_ID_I |    1 |    64 |       1 (0) | 00:00:01 |
-------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID"=424)

Statistics
----------------------------------------------------------
          1 recursive calls
         49 db block gets
          3 consistent gets
          0 physical reads
       5996 redo size
        204 bytes sent via SQL*Net to client
         41 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
         11 sorts (memory)
          0 sorts (disk)
          1 rows processed

We see that the number of db block gets jumps significantly to 49, as all the corresponding indexes require their associated index entries to be likewise deleted/re-inserted in order to change all their ROWIDs.

So this additional cost of updating the indexes has been a cost that Oracle has traditionally attempted to avoid, by generally not changing the ROWID when performing an update of a row.

Of course, the update of a Partitioned Key column is not the only manner in which ROWIDs have previously easily changed as we’ll see in Part IV…

UPDATE: As my buddie Martin Widlake makes in this comment. it’s also well worth mentioning the increase in associated redo (as redo is an excellent measurement of “work” the Oracle Database has to perform), if Oracle has to change the ROWID of a row and make the necessary changes to all its corresponding indexes. In the example above, the redo increases significantly from 328 bytes to 5996 bytes, when Oracle has to move the row to another partition and so update the ROWID on the 11 indexes. More on all this when I discuss the changes implemented with the current Autonomous Databases…

When Does A ROWID Change? Part II (“You’ve Got A Habit Of Leaving”) December 9, 2022

Posted by Richard Foote in Autonomous Database, CBO, Changing ROWID, Global Indexes, Multiple Indexes, Oracle, Oracle 21c, Oracle Blog, Oracle Cloud, Oracle General, Partitioning, Performance Tuning, Richard's Blog, ROWID.
3 comments

In my previous post, I discussed how a row is generally “migrated”, but the ROWID remains unchanged, when a row is updated such that it can no longer fit into its current block. Hence the general rule has always been that the ROWID of a row does not change.

However, even before the changes now present with Oracle Autonomous Databases (to be discussed in future posts), there has always been (since Oracle 8) one classic scenario when this “ROWID never changes after an update” rule has not been true.

To illustrate, I’m going to create and populate a basic little Range-based Partitioned table, with the RELEASE_DATE column being the partitioned column:

SQL> CREATE TABLE big_bowie(id number, release_date date, name varchar2(42)) PARTITION BY RANGE (release_date)
(PARTITION ALBUMS_2021 VALUES LESS THAN (TO_DATE('01-JAN-2022', 'DD-MON-YYYY')),
PARTITION ALBUMS_2022 VALUES LESS THAN (MAXVALUE));

Table created.

SQL> INSERT INTO big_bowie SELECT rownum, sysdate-mod(rownum,500), 'DAVID BOWIE' FROM dual CONNECT BY LEVEL <= 10000;

10000 rows created.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=> null, tabname=> 'BIG_BOWIE');

PL/SQL procedure successfully completed.

Let’s look at the current ROWIDs of a few random rows:

SQL> select id, release_date, rowid from big_bowie where id in (424, 444, 482) order by id;

        ID RELEASE_D ROWID
---------- --------- ------------------
       424 08-OCT-21 AAASe9AAMAAAAj7ABU
       444 18-SEP-21 AAASe9AAMAAAAj7ABo
       482 11-AUG-21 AAASe9AAMAAAAj7ACO

I’m now going to try and update for these rows, the partitioned column value, such that they would now logically belong in the other partition:

SQL> update big_bowie set release_date='06-DEC-22' where id in (424, 444, 482);
update big_bowie set release_date='06-DEC-22' where id in (424, 444, 482)
*
ERROR at line 1:
ORA-14402: updating partition key column would cause a partition change

I now get a very key and important error. By default, Oracle does not allow you to update a row if it results in the row having to physically move to a different partition.

I suspect there are at least 3 good reasons for this default restriction.

One is to protect the business integrity of the data, where it might just not make any business sense for a row to be updated in this manner.

The second is that it protects any applications out there that explicitly uses ROWIDs and relies on the ROWIDs not suddenly changing behind the scenes.

And finally, it protects perhaps valuable database resources and ensures that the database does not have to incur any additional workloads, that would be necessary if such an operation were to proceed.

But we have the ability and control to override this default behaviour in the following manner with the ENABLE ROW MOVEMENT clause:

SQL> alter table big_bowie enable row movement;

Table altered.

If we now try and update these rows again:

SQL> update big_bowie set release_date='06-DEC-22' where id in (424, 444, 482);

3 rows updated.

SQL> commit;

Commit complete.

The updates are now successful.

As these rows no longer logically belong in the previous partition, they have to be physically moved to its new partition. This is effectively implemented by deleting the rows from the previous partition and then re-inserting them in the new partition segment.

If we now look the ROWIDs of these updated rows:

SQL> select id, release_date, rowid from big_bowie where id in (424, 444, 482) order by id;

        ID RELEASE_D ROWID
---------- --------- ------------------
       424 06-DEC-22 AAASe+AAMAAAATQABR
       444 06-DEC-22 AAASe+AAMAAAATQABS
       482 06-DEC-22 AAASe+AAMAAAATQABT

We notice that they now all have different ROWIDs, because they indeed now all exist in a different physical location.

In my next post, I’ll highlight but one obvious disadvantage and consequence of allowing rows to be physically moved in this manner…

When Does A ROWID Change? Part I (“Fearless”) December 7, 2022

Posted by Richard Foote in Autonomous Database, Block Dumps, Changing ROWID, Oracle, Oracle Blog, Oracle Cloud, Oracle General, Oracle Indexes, Oracle Table Internals, Oracle19c, Pink Floyd, Richard's Blog, ROWID.
7 comments

Recently, my mate Connor McDonald caused a tad of a storm when he disclosed that the once sacred, (almost) unchangeable ROWID can now indeed potentially easily change, without the DBA doing a thing.

You can watch his excellent video on the subject here.

As the humble ROWID is a critical component of any index, I thought it worthwhile to have a deep dive discussion on when a ROWID can and can’t change and some of the key changes that have been introduced within Oracle’s Autonomous database environments.

If you’re a developer who explicitly uses the ROWID in your applications, you might want to pay extra attention to these changes.

I thought I’ll begin first though by discussing how the ROWID currently doesn’t generally change…

The ROWID is basically just a pointer stored in indexes that effectively points to the physical location of a row within a table that’s associated with the specific indexed key. It consists of the Data Object ID (if it’s a Global Index associated to a Partitioned Table, as the Relative File ID is no longer a unique value and so needs this to determine the appropriate tablespace), a Relative File ID, a Data Block ID within the Relative File and the Row Location ID within the Data Block.

Now although it has never been a completely risk free approach to manually store and directly use these ROWIDs to fetch a row from a table, it’s a technique that has been frequently used by developers for 3 very good reasons.

The first reason is that it’s one of the most efficient ways to fetch a required row, because the database can go directly to the physical location and directly access the required row, without having to even read a single index block.

The second reason is because it has always been fully supported by Oracle to do so, with the required syntax well documented. Indeed, Oracle APEX includes the base functionality to store and access rows directly via their associated ROWIDs.

The third reason is because it’s generally well understood that the ROWID doesn’t change, except for a very few (generally) well known scenarios, and so using the ROWID to access data within an application is viewed as being reasonable safe.

When a row is inserted into a table, each corresponding index on the table (generally) has a new index entry also inserted, including its associated ROWID. Now, if the row never moves from its current physical location, there is no need to ever worry about the ROWID subsequently changing.

So the big question is, when can a row physically move AND the associated ROWID change?

Logically, a scenario that springs to mind is when a row is updated and made bigger and there’s no longer room within the current data block to store the larger row. Does the row move to another block with sufficient free space and result in the ROWID to change?

To check out this scenario, I’ll create and populate a basic table, with PCTFREE set to 0, so once the blocks within the table are filled, there is precious little space for rows to subsequently grow:

SQL> create table bowie (id number, name varchar2(142)) pctfree 0 enable row movement;

Table created.

SQL> insert into bowie select rownum, 'BOWIE' from dual connect by level <=10000;

10000 rows created.

SQL> commit;

Commit complete.

SQL> create index bowie_id_i on bowie(id);

Index created.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'BOWIE');

PL/SQL procedure successfully completed.

 

For good measure, I’ve also included the ENABLE ROW MOVEMENT clause, which is usually associated with Partitioned Tables (as I’ll discuss in Part II in this series).

Let’s have a look at the ROWIDs of a few random rows:

SQL> select id, rowid from bowie where id in (42, 424, 4242) order by id;

ID         ROWID
---------- ------------------
42         AAASe4AAMAAAACHAAp
424        AAASe4AAMAAAACHAGn
4242       AAASe4AAMAAAACNAHV

If we look at a partial block dump of one of the table blocks:

tab 0, row 0, @0x1312
tl: 12 fb: --H-FL-- lb: 0x1 cc: 2
col 0: [ 2] c1 02
col 1: [ 5] 42 4f 57 49 45
tab 0, row 1, @0x131e
tl: 12 fb: --H-FL-- lb: 0x1 cc: 2
col 0: [ 2] c1 03
col 1: [ 5] 42 4f 57 49 45
tab 0, row 2, @0x132a
tl: 12 fb: --H-FL-- lb: 0x1 cc: 2
col 0: [ 2] c1 04
col 1: [ 5] 42 4f 57 49 45
tab 0, row 3, @0x1336
tl: 12 fb: --H-FL-- lb: 0x1 cc: 2
col 0: [ 2] c1 05
col 1: [ 5] 42 4f 57 49 45
tab 0, row 4, @0x1342
tl: 12 fb: --H-FL-- lb: 0x1 cc: 2
col 0: [ 2] c1 06
col 1: [ 5] 42 4f 57 49 45

The above partial block dump shows the first 5 rows within the block, with the contents of the 2 table columns listed (in hex format).

If we access a row via an index:

SQL> select * from bowie where id=42;

ID         NAME
---------- --------------------------------------------------------------
42         THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS

Execution Plan
--------------------------------------------------------------------------------------------------
|  Id | Operation                            | Name       | Rows | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                     |            |    1 |    66 |       2 (0)| 00:00:01 |
|   1 |  TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE      |    1 |    66 |       2 (0)| 00:00:01 |
| * 2 |   INDEX RANGE SCAN                   | BOWIE_ID_I |    1 |       |       1 (0)| 00:00:01 |
--------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("ID"=42)

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
          4 consistent gets
          0 physical reads
          0 redo size
        702 bytes sent via SQL*Net to client
         52 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

We can see in this example that Oracle requires 4 consistent gets, 3 of which are accesses to the index.

If we access this table via its ROWID:

SQL> select * from bowie where rowid='AAASe4AAMAAAACHAAp';

ID         NAME
---------- --------------------------------------------------------------
42         THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS

Execution Plan
------------------------------------------------------------------------------------
| Id | Operation                   | Name  | Rows | Bytes | Cost (%CPU) | Time     |
------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT            |       |    1 |    10 |       1 (0) | 00:00:01 |
|  1 |  TABLE ACCESS BY USER ROWID | BOWIE |    1 |    10 |       1 (0) | 00:00:01 |
------------------------------------------------------------------------------------

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
          1 consistent gets
          0 physical reads
          0 redo size
        698 bytes sent via SQL*Net to client
         52 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

We can see that this only requires just the 1 consistent get (vs. 4 when using the index) to access the row.

So we can see the appeal of using the ROWID to access a row.

If we now update the rows within the table and make them substantially larger so they can no longer fit within the currently filled blocks:

SQL> update bowie set name='THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS';

10000 rows updated.

SQL> commit;

Commit complete.

And now look again at the ROWIDs of these selected rows:

SQL> select id, rowid from bowie where id in (42, 424, 4242) order by id;

ID         ROWID
---------- ------------------
42         AAASe4AAMAAAACHAAp
424        AAASe4AAMAAAACHAGn
4242       AAASe4AAMAAAACNAHV

We notice that the ROWIDs all remain the same.

This has always historically been the behaviour here. If we update a row and the updated row can no longer fit within the current block, the row “migrates” to another table block with sufficient free space. BUT the associated ROWIDs do NOT change and the associated indexes are NOT updated.

Rather, the row data within the updated table is replaced with a “pointer”, that points to the new physical location of the migrated row. The advantage here being that Oracle only has to update the table with this new pointer, rather having to update the associated ROWIDs of all the (possibly many) associated indexes (noting that such an update would actually result in a delete followed by a re-insert of each index entry).

The disadvantage of course is that to now access this migrated row via an index requires an extra hop, to first read the initial table block and then to follow the pointer and access the actual block that now contains the row. Note if this row is forced to be migrated again because it grows again and can’t be housed in the current block, this pointer in the initial block is updated to reflect the newer location, so at least there is only ever the one extra hop.

If we look at a new partial block dump of the previously accessed block:

tab 0, row 0, @0x1f8f
tl: 9 fb: --H----- lb: 0x2 cc: 0
nrid: 0x030000bf.4b
tab 0, row 1, @0x1f86
tl: 9 fb: --H----- lb: 0x2 cc: 0
nrid: 0x030000bf.4c
tab 0, row 2, @0x1f7d
tl: 9 fb: --H----- lb: 0x2 cc: 0
nrid: 0x030000bf.4d
tab 0, row 3, @0x1f74
tl: 9 fb: --H----- lb: 0x2 cc: 0
nrid: 0x030000bf.4e
tab 0, row 4, @0x1f6b
tl: 9 fb: --H----- lb: 0x2 cc: 0
nrid: 0x030000b8.0

We notice that the rows with their 2 columns have been replaced with a logical nrid pointer (consisting of a relative block address and row location within the block), that effectively points to the new physical location of the row.

Note we can still use the same, unchanged ROWID to access the same table rows:

SQL> select * from bowie where rowid='AAASe4AAMAAAACHAAp';

ID         NAME
---------- --------------------------------------------------------------
42         THE RISE AND FALL OF ZIGGY STARDUST AND THE SPIDERS FROM MARS

Execution Plan
------------------------------------------------------------------------------------
| Id | Operation                   | Name  | Rows | Bytes | Cost (%CPU) | Time     |
------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT            |       |    1 |    10 |       1 (0) | 00:00:01 |
|  1 |  TABLE ACCESS BY USER ROWID | BOWIE |    1 |    10 |       1 (0) | 00:00:01 |
------------------------------------------------------------------------------------

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
          2 consistent gets
          0 physical reads
          0 redo size
        698 bytes sent via SQL*Net to client
         52 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

This ROWID access still works fine, except it has now increased to 2 consistent gets, one to access the initial block referenced by the ROWID and the extra consistent get to follow the pointer and access the new physical location of the row.

So historically, we haven’t had to worry about updates changing the ROWID of a row (except perhaps at looking at reducing the number of these migrated rows).

Well, except for one clear example as I’ll discuss in Part II

‚ÄúHidden‚ÄĚ Efficiencies of Non-Partitioned Indexes on Partitioned Tables Part II (Aladdin Sane) October 9, 2018

Posted by Richard Foote in Global Indexes, Index Internals, Local Indexes, Oracle Indexes, Partitioned Indexes, Partitioning, ROWID.
2 comments

aladdin sane

In Part I of this series, I highlighted how a Non-Partitioned Global Index on a Partitioned Table is able to effectively perform “Partition Pruning” by reading only the associated index entries to access just the table blocks of interest from relevant table partitions when the table partitioned keys are specified in an SQL Predicate.

Understanding how Oracle achieves this is key (pun fully intended) in understanding the associated advantages of Global Indexes.

Back in time before Oracle introduced Partitioning (pre-Oracle 8 days), the 6 byte ROWID was safely made up of the following components:

  • File Number
  • Block Number
  • Row Number

to uniquely determine the location of any given row.

If we look at a partial block dump of a leaf block from the index based on the Non-Partitioned table:

Leaf block dump
===============
header address 1881436260=0x70247064
kdxcolev 0
KDXCOLEV Flags = – – –
kdxcolok 0
kdxcoopc 0x80: opcode=0: iot flags=— is converted=Y
kdxconco 2
kdxcosdc 0
kdxconro 513
kdxcofbo 1062=0x426
kdxcofeo 1880=0x758
kdxcoavs 818
kdxlespl 0
kdxlende 0
kdxlenxt 29387269=0x1c06a05
kdxleprv 0=0x0
kdxledsz 0
kdxlebksz 8036
row#0[8024] flag: ——-, lock: 0, len=12
col 0; len 2; (2): c1 02
col 1; len 6; (6): 01 c0 1d 68 00 18
row#1[8012] flag: ——-, lock: 0, len=12
col 0; len 2; (2): c1 02
col 1; len 6; (6): 01 c0 24 c8 00 c1
row#2[8000] flag: ——-, lock: 0, len=12
col 0; len 2; (2): c1 02
col 1; len 6; (6): 01 c0 3a 1c 00 96

We notice that the ROWID for each index entry is the standard 6 bytes in size.

With the introduction of Oracle 8 and the Partitioning Option, the File Number was no longer unique, with this number of files (approx. 1K) now possible not for the database at large, but for each Tablespace (thus making Oracle able to cater for very large databases with there now being the option for so many more data files in a database).

This means for a Partitioned Table in which each table partition (or sub-partition) could potentially reside in different tablespaces, the associated file number (RELATIVE_FNO) within the ROWID is no longer unique. Therefore, for Global Indexes in which index entries span across all table partitions, the ROWID is extended to include the 4 byte Data Object Id. A specific object can only live in one tablespace and if Oracle knows the tablespace, Oracle can determine which specific file number the ROWID is referencing. So an extended ROWID is consists of:

  • Data Object Id
  • File Number
  • Block Number
  • Row Number

If we look at a partial block dump of a leaf block from the index based on the Partitioned table:

Leaf block dump
===============
header address 1881436260=0x70247064
kdxcolev 0
KDXCOLEV Flags = – – –
kdxcolok 0
kdxcoopc 0x80: opcode=0: iot flags=— is converted=Y
kdxconco 2
kdxcosdc 0
kdxconro 399
kdxcofbo 834=0x342
kdxcofeo 1652=0x674
kdxcoavs 818
kdxlespl 0
kdxlende 0
kdxlenxt 29385221=0x1c06205
kdxleprv 0=0x0
kdxledsz 0
kdxlebksz 8036
row#0[8020] flag: ——-, lock: 0, len=16
col 0; len 2; (2): c1 02
col 1; len 10; (10): 00 01 57 4a 01 c0 5e cf 00 cc
row#1[8004] flag: ——-, lock: 0, len=16
col 0; len 2; (2): c1 02
col 1; len 10; (10): 00 01 57 4a 01 c0 5f 74 00 e7
row#2[7988] flag: ——-, lock: 0, len=16
col 0; len 2; (2): c1 02
col 1; len 10; (10): 00 01 57 4b 01 c0 5c 32 00 c9

We notice that the ROWID for each index entry is now the extended 10 bytes in size as it includes the Data Object Id.

Storing the Data Object Id as part of the ROWID has various advantages, such as being able to asynchronously maintain index entries following table partition operations such as dropping a table partition (as discussed previously here).

However the key advantage of storing the Data Object Id as part of the ROWID is that this enables Oracle when using Global Indexes to automatically perform “Partition Pruning” (the ability to access only those partitions that can possibly contain data of interest), when the table partition key is specified in an SQL predicate.

When the table partition key is specified in an SQL predicate, Oracle can determine which table partitions can only contain such data and then only access the table blocks via the index ROWIDs that have corresponding Data Object Ids of interest. This is how in the example in Part I Oracle was able to only access just the table block that belongs in the table partition of interest, effectively performing predicate filtering at the index level, without unnecessarily having to access the table blocks at all from partitions that are not of interest.

This enables Global Indexes to have almost Local Index like performance in scenarios where the table partition key is specified in SQL predicates. Local Indexes do have the advantage of potentially having a reduced BLEVEL in that if you have say 100 table partitions, each Local Index would only have to be approx. 1/100 the size of the single, Non-Partitioned Index (although Global Indexes can in turn be partitioned if individual index size were problematic, even if the table were not partitioned). Additionally, Local Indexes don’t have to concern themselves with having to read through unnecessary index entries if index entries associated with a specific subset of table partitions were only of interest.

However, Global Indexes have a key performance advantage over Local Indexes which I’ll discussed in Part III.

 

IOT Secondary Indexes – The Logical ROWID Guess Component Part II (Move On) May 8, 2012

Posted by Richard Foote in Index Block Size, Index Organized Tables, IOT, ROWID, Secondary Indexes.
7 comments

Having mentioned a couple of dangers associated with IOT Secondary Indexes, thought I might discuss a couple of their nicer attributes.

In the previous post, we saw how 50-50 index block splits on the ALBUM_SALES_IOT IOT¬†table caused rows to move to new leaf blocks, resulting in a degradation in the PCT_DIRECT_ACCESS value of the associated ALBUM_SALES_IOT_TOTAL_SALES_I secondary index, which in turn resulted in poorer performance when using this index. We had to rebuild the secondary¬†index (or update block references)¬†to make all the “guess” components accurate and the index efficient¬†again and so point to the correct locations within the parent IOT.

So, if you have 50-50 block splits occurring in your IOT, this will degrade the efficiency of the associated IOT Secondary indexes over time.

However, if you don’t have 50-50 block splits and the entries in the IOT don’t move from leaf block to leaf block, then this will not be an issue. Remembering of course that many Primary Key values are based on a sequence which monotonically increases and results in 90-10 block splits rather than 50-50 block splits. ¬†90-10 block splits don’t move data around, Oracle leaves the full blocks alone and simply adds a new block in the¬†IOT Btree¬†structure¬†into which new values are added. Therefore, with IOT data¬†not moving around, the “guess” component of the logical ROWIDS remain valid and don’t go stale over time and so the associated secondary indexes remain nice and efficient.

If we look at the current state of the ALBUM_SALES_IOT_TOTAL_SALES_I secondary index:

SQL> SELECT index_name, pct_direct_access, iot_redundant_pkey_elim  FROM dba_indexes WHERE index_name = 'ALBUM_SALES_IOT_TOTAL_SALES_I';

INDEX_NAME                     PCT_DIRECT_ACCESS IOT
------------------------------ ----------------- ---
ALBUM_SALES_IOT_TOTAL_SALES_I                100 NO

We notice the PCT_DIRECT_ACCESS is currently nice and efficient at 100%.

If we now add a bunch of new rows into the IOT, but this time with PK values that monotonically increase:

SQL> BEGIN
  2    FOR i IN 5001..10000 LOOP
  3      FOR c IN 201..300 LOOP
  4        INSERT INTO album_sales_iot VALUES(i,c,ceil(dbms_random.value(1,5000000)), 'Yet more new rows');
  5      END LOOP;
  6    END LOOP;
  7    COMMIT;
  8  END;
  9  /

PL/SQL procedure successfully completed.

And collect fresh statistics:

SQL> exec dbms_stats.gather_table_stats(ownname=>'BOWIE', tabname=>'ALBUM_SALES_IOT', estimate_percent=>null, cascade=>true, method_opt=> 'FOR ALL COLUMNS SIZE 1');

PL/SQL procedure successfully completed.

SQL> SELECT index_name, pct_direct_access, iot_redundant_pkey_elim  FROM dba_indexes WHERE index_name = 'ALBUM_SALES_IOT_TOTAL_SALES_I';

INDEX_NAME                     PCT_DIRECT_ACCESS IOT
------------------------------ ----------------- ---
ALBUM_SALES_IOT_TOTAL_SALES_I                100 NO

We notice that the PCT_DIRECT_ACCESS value remains unchanged. So, no 50-50 block split, no PCT_DIRECT_ACCESS degradation with regard the secondary indexes.

OK, another nice feature with IOT Secondary Indexes.

With¬†a “normal” Heap table, if we were to MOVE and reorganise the table, all associated indexes become invalid as the Move results in all the rows being relocated and the indexes are not maintained during this process (as this would add considerably to the overhead in the Move process). All associated indexes have to be rebuilt after the Move operation completes, which is both expensive and adds considerably to the¬†availability¬†issues associated¬†with the whole table reorg process as the table is locked during the Move¬†operation. In short, moving a heap table is an expensive and an availability unfriendly process.

As this little demo illustrates, moving a heap table results in all indexes becoming unusable:

SQL> create table radiohead (id number constraint radiohead_pk primary key, code number, name varchar2(30));

Table created.

SQL> create index code_i on radiohead(code);

Index created.

SQL> insert into radiohead select rownum, rownum, 'OK COMPUTER' from dual connect by level <= 100000;

100000 rows created.

SQL> commit;

Commit complete.

SQL> select index_name, status from dba_indexes where table_name = 'RADIOHEAD';

INDEX_NAME                     STATUS
------------------------------ --------
RADIOHEAD_PK                   VALID
CODE_I                         VALID

SQL> alter table radiohead move;

Table altered.

SQL> select index_name, status from dba_indexes where table_name = 'RADIOHEAD';

INDEX_NAME                     STATUS
------------------------------ --------
RADIOHEAD_PK                   UNUSABLE
CODE_I                         UNUSABLE

However, moving an IOT has a number of advantages over a heap table.

Firstly, as it’s an index structure, it can be reorganised and rebuilt in much the same way as we can rebuild any btree¬†index.¬†Remembering, an index can be rebuilt “online” (on Enterprise Edition), overcoming many of the locking issues associated with moving heap tables.

Additionally, although the physical locations of all the rows in the IOT change following a Move operation, the PK values¬† themselves don’t change. Therefore, although the PCT_DIRECT_ACCESS value becomes 0, the indexes themselves are still¬†Valid and usable¬†as the PK component can still be used to access the relevant data.

So the syntax to move an IOT table can be expanded to be performed “Online” and all the secondary indexes will remain “Valid”:

SQL> select index_name, status, PCT_DIRECT_ACCESS from dba_indexes where table_name = 'ALBUM_SALES_IOT';

INDEX_NAME                     STATUS   PCT_DIRECT_ACCESS
------------------------------ -------- -----------------
ALBUM_SALES_IOT_PK             VALID                    0
ALBUM_SALES_IOT_TOTAL_SALES_I  VALID                  100
ALBUM_SALES_IOT_COUNTRY_ID_I   VALID                  100

SQL> alter table album_sales_iot move online;

Table altered.

SQL> select index_name, status, PCT_DIRECT_ACCESS from dba_indexes where table_name = 'ALBUM_SALES_IOT';

INDEX_NAME                     STATUS   PCT_DIRECT_ACCESS
------------------------------ -------- -----------------
ALBUM_SALES_IOT_PK             VALID                    0
ALBUM_SALES_IOT_TOTAL_SALES_I  VALID                    0
ALBUM_SALES_IOT_COUNTRY_ID_I   VALID                    0

So although the PCT_DIRECT_ACCESS values for the secondary indexes has gone down to 0, making them less efficient as a result, they do at least remain valid and usable by the CBO:

SQL> select * from album_sales_iot where total_sales between 424242 and 424343;

26 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 1433198708

---------------------------------------------------------------------------------------------------
| Id  | Operation         | Name                          | Rows  | Bytes | Cost (%CPU)| Time     |
---------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |                               |    33 |   858 |    68   (0)| 00:00:01 |
|*  1 |  INDEX UNIQUE SCAN| ALBUM_SALES_IOT_PK            |    33 |   858 |    68   (0)| 00:00:01 |
|*  2 |   INDEX RANGE SCAN| ALBUM_SALES_IOT_TOTAL_SALES_I |    33 |       |     3   (0)| 00:00:01 |
---------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------

   1 - access("TOTAL_SALES">=424242 AND "TOTAL_SALES"<=424343)
   2 - access("TOTAL_SALES">=424242 AND "TOTAL_SALES"<=424343)
Statistics
----------------------------------------------------------
          1  recursive calls
          0  db block gets
         83  consistent gets
         53  physical reads
          0  redo size
       1655  bytes sent via SQL*Net to client
        534  bytes received via SQL*Net from client
          3  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
         26  rows processed

The secondary index is still used by the CBO, although at 83 consistent gets in this example, it’s not as efficient as it could be.

The rebuild of the secondary index can be performed subsequently to repair the stale guesses and improve the efficiency of the index as desired:

SQL> alter index album_sales_iot_total_sales_i rebuild online;

Index altered.

SQL> select index_name, status, PCT_DIRECT_ACCESS from dba_indexes where table_name = 'ALBUM_SALES_IOT';

INDEX_NAME                     STATUS   PCT_DIRECT_ACCESS
------------------------------ -------- -----------------
ALBUM_SALES_IOT_PK             VALID                    0
ALBUM_SALES_IOT_TOTAL_SALES_I  VALID                  100
ALBUM_SALES_IOT_COUNTRY_ID_I   VALID                    0
SQL> select * from album_sales_iot where total_sales between 424242 and 424343;

26 rows selected.
Execution Plan
----------------------------------------------------------
Plan hash value: 1433198708

---------------------------------------------------------------------------------------------------
| Id  | Operation         | Name                          | Rows  | Bytes | Cost (%CPU)| Time     |
---------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |                               |    33 |   858 |    36   (0)| 00:00:01 |
|*  1 |  INDEX UNIQUE SCAN| ALBUM_SALES_IOT_PK            |    33 |   858 |    36   (0)| 00:00:01 |
|*  2 |   INDEX RANGE SCAN| ALBUM_SALES_IOT_TOTAL_SALES_I |    33 |       |     3   (0)| 00:00:01 |
---------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------

   1 - access("TOTAL_SALES">=424242 AND "TOTAL_SALES"<=424343)
   2 - access("TOTAL_SALES">=424242 AND "TOTAL_SALES"<=424343)
Statistics
----------------------------------------------------------
          1  recursive calls
          0  db block gets
         31  consistent gets
          0  physical reads
          0  redo size
       1655  bytes sent via SQL*Net to client
        534  bytes received via SQL*Net from client
          3  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
         26  rows processed

Following the rebuild of the secondary index and getting the PCT_DIRECT_ACCESS back to 100%, the example query is now more efficient, with a reduction of consistent gets down from 83 to just 31.

So IOTs can be less problematic to reorganise and if 90-10 block splits are performed, the impact on the secondary indexes is minimised.