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Oracle 19c Automatic Indexing: Function-Based Indexes? Part II (If You Can See Me) February 5, 2021

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Function Based Indexes, Oracle, Oracle Blog, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle19c, Virtual Columns.
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In my previous post, I discussed how Automatic Indexing does not currently support creating an index based on a function or expression predicate, even if it’s an equality predicate. You must manually create the associated function-based index.

However, if you have access to the application, there’s a better strategy when frequently searching on a function-based predicate. That’s to create a Virtual Column and use this column in your searching criteria (as mentioned by Connor McDonald in this comment).

To illustrate, I’m going to drop the previously manually created function-based index and hence the associated hidden virtual column, as Oracle quite rightly doesn’t allow you to have two virtual columns based on the same expression in the same table.

SQL> drop index david_upper_name_i;

Index dropped.

Since Oracle 11g, Oracle has supported the use of Visible Virtual Columns, a column that doesn’t physically exist, but defines a function/expression that can be easily accessed and populated when queried.

I’ll next create a Virtual Column called UPPER_NAME that is defined not based on a Data Type, but on the result on the UPPER function on the previously defined NAME column:

SQL> alter table david add (upper_name as (upper(name)));

Table altered.

Regardless of size of table, this column is added virtually instantly (pun fully intended), as no data is physically stored in the table itself. I view it (yep, another pun) as a “mini-view”, that can be used to hide complexity from the developer, with the actual data derived at run-time when the column is accessed in an SQL.

After I generate fresh statistics:

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

PL/SQL procedure successfully completed.

SQL> select column_name, hidden_column, virtual_column, num_distinct, density, histogram from dba_tab_cols where table_name='DAVID';

COLUMN_NAME          HID VIR NUM_DISTINCT    DENSITY HISTOGRAM
-------------------- --- --- ------------ ---------- ---------------
NAME                 NO  NO      10000000          0 HYBRID
MORE_STUFF9          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF8          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF7          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF6          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF5          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF4          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF3          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF2          NO  NO             1  .00000005 FREQUENCY
MORE_STUFF10         NO  NO             1  .00000005 FREQUENCY
MORE_STUFF1          NO  NO             1  .00000005 FREQUENCY
ID                   NO  NO      10000000          0 HYBRID
CODE                 NO  NO         10000      .0001 HYBRID
UPPER_NAME           NO YES      10000000          0 HYBRID

Note how the UPPER_NAME virtual column is NOT hidden and now has up to date statistics.

We can now run this simplified query based on the new UPPER_NAME column, which does not need to include the potentially complex function expression:

SQL> select * from david where upper_name='DAVID BOWIE 42';

1 row selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 2426813604

-----------------------------------------------------------------------------------
| Id | Operation                 | Name  | Rows | Bytes | Cost (%CPU) | Time      |
-----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |       |    1 |   200 |    3349 (6) | 00:00:01  | 
|* 1 | TABLE ACCESS STORAGE FULL | DAVID |    1 |   200 |    3349 (6) | 00:00:01  |
-----------------------------------------------------------------------------------

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

1 - storage("UPPER_NAME"='DAVID BOWIE 42')
    filter("UPPER_NAME"='DAVID BOWIE 42')

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
     263469 consistent gets
     263452 physical reads
          0 redo size
       1328 bytes sent via SQL*Net to client
        375 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

If we look at portions of the subsequent Automatic Indexing report:

 

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates                             : 1
Indexes created (visible / invisible)        : 1 (1 / 0)
Space used (visible / invisible)             : 360.71 MB (360.71 MB / 0 B)
Indexes dropped                              : 0
SQL statements verified                      : 2
SQL statements improved (improvement factor) : 2 (263476.8x)
SQL plan baselines created                   : 0
Overall improvement factor                   : 263476.8x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

INDEX DETAILS
-------------------------------------------------------------------------------
The following indexes were created:
-------------------------------------------------------------------------------
---------------------------------------------------------------------------
| Owner | Table | Index                | Key        | Type   | Properties |
---------------------------------------------------------------------------
| BOWIE | DAVID | SYS_AI_4k4mkgkw049ht | UPPER_NAME | B-TREE | NONE       |
---------------------------------------------------------------------------
-------------------------------------------------------------------------------

VERIFICATION DETAILS
-------------------------------------------------------------------------------
The performance of the following statements improved:
-------------------------------------------------------------------------------
Parsing Schema Name : BOWIE
SQL ID              : 7tfqh3pu526mt
SQL Text            : select * from david where upper_name='DAVID BOWIE 42'
Improvement Factor  : 263484.7x

Execution Statistics:
-----------------------------
                        Original Plan                Auto Index Plan
                        ---------------------------- ----------------------------
Elapsed Time (s):       1471249                      1414
CPU Time (s):           300584                       986
Buffer Gets:            3161816                      4
Optimizer Cost:         3349                         4
Disk Reads:             3161432                      3
Direct Writes:          0                            0
Rows Processed:         12                           1
Executions:             12                           1

PLANS SECTION
--------------------------------------------------------------------------------
- Original
-----------------------------
Plan Hash Value : 2426813604

-----------------------------------------------------------------------------
| Id | Operation                 | Name  | Rows | Bytes | Cost | Time       |
-----------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |       |      |       | 3349 |            |
|  1 | TABLE ACCESS STORAGE FULL | DAVID |    1 |   200 | 3349 | 00:00:01   |
-----------------------------------------------------------------------------

Notes
-----
- dop = 1
- px_in_memory_imc = no
- px_in_memory = no
- cardinality_feedback = yes

- With Auto Indexes
-----------------------------
Plan Hash Value : 1447691372

-------------------------------------------------------------------------------------------------------
| Id  | Operation                            | Name                 | Rows | Bytes | Cost | Time      |
-------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                     |                      |    1 |   200 |    4 | 00:00:01  |
|   1 |  TABLE ACCESS BY INDEX ROWID BATCHED | DAVID                |    1 |   200 |    4 | 00:00:01  |
| * 2 |  INDEX RANGE SCAN                    | SYS_AI_4k4mkgkw049ht |    1 |       |    3 | 00:00:01  |
-------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
------------------------------------------
* 2 - access("UPPER_NAME"='DAVID BOWIE 42')

Notes
-----
- Dynamic sampling used for this statement ( level = 11 )

 

We see from the report that Automatic Indexing has now created the associated, implicitly created function-based index (SYS_AI_4k4mkgkw049ht) based on the virtual UPPER_NAME column:

SQL> select index_name, index_type, auto, constraint_index, visibility, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='DAVID';

INDEX_NAME           INDEX_TYPE                  AUT CON VISIBILIT STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
-------------------- --------------------------- --- --- --------- -------- ---------- ----------- -----------------
SYS_AI_4k4mkgkw049ht FUNCTION-BASED NORMAL       YES NO  VISIBLE   VALID      10000000       43104           2136839

SQL> select index_name, column_name, column_position
from user_ind_columns where table_name='DAVID' order by index_name, column_position;

INDEX_NAME           COLUMN_NAME          COLUMN_POSITION
-------------------- -------------------- ---------------
SYS_AI_4k4mkgkw049ht UPPER_NAME                         1

 

If we now re-run the SQL query:

SQL> select * from david where upper_name='DAVID BOWIE 4242';

1 row selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 1447691372

------------------------------------------------------------------------------------------------------------
| Id | Operation                            | Name                 | Rows | Bytes | Cost (%CPU) | Time     |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                     |                      |    1 |   200 |       4 (0) | 00:00:01 |
|  1 |  TABLE ACCESS BY INDEX ROWID BATCHED | DAVID                |    1 |   200 |       4 (0) | 00:00:01 |
|* 2 |   INDEX RANGE SCAN                   | SYS_AI_4k4mkgkw049ht |    1 |       |       3 (0) | 00:00:01 |
------------------------------------------------------------------------------------------------------------

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

2 - access("UPPER_NAME"='DAVID BOWIE 4242')

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
          5 consistent gets
          0 physical reads
          0 redo size
       1334 bytes sent via SQL*Net to client
        377 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

The CBO now uses the new Automatic Index to significantly improve the performance of the query.

So not only is using a user defined Virtual Column a cleaner solution with respect to the frequent use of a function-based expressions, but has the added advantage of being supported with Automatic Indexing.

Oracle 19c Automatic Indexing: Function-Based Indexes? (No Plan) February 4, 2021

Posted by Richard Foote in 19c, 19c New Features, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Function Based Indexes, Oracle, Oracle Cloud, Oracle General, Oracle Indexes, Oracle19c, Virtual Columns.
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I previously discussed how Automatic Indexing only currently supports Equality based predicates.

The question I have today is does Automatic Indexing support function-based indexes? Let’s take a look.

The below DAVID table has the key column NAME which is an effectively unique VARCHAR2 column:

SQL> create table david (id number, code number, name varchar2(42), more_stuff1 varchar2(42), more_stuff2 varchar2(42), more_stuff3 varchar2(42), more_stuff4 varchar2(42), more_stuff5 varchar2(42), more_stuff6 varchar2(42), more_stuff7 varchar2(42), more_stuff8 varchar2(42), more_stuff9 varchar2(42), more_stuff10 varchar2(42));

Table created.

SQL> insert into david select rownum, mod(rownum, 10000)+1, 'David Bowie '|| rownum, 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust', 'Ziggy Stardust' from dual connect by level <=10000000;

10000000 rows created.

SQL> commit;

Commit complete.

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

PL/SQL procedure successfully completed.

If we look at the current details of the table columns:

SQL> select column_name, num_distinct, density, histogram from dba_tab_cols where table_name='DAVID';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM
-------------------- ------------ ---------- ---------------
NAME                     10000000          0 HYBRID
MORE_STUFF9                     1  .00000005 FREQUENCY
MORE_STUFF8                     1  .00000005 FREQUENCY
MORE_STUFF7                     1  .00000005 FREQUENCY
MORE_STUFF6                     1  .00000005 FREQUENCY
MORE_STUFF5                     1  .00000005 FREQUENCY
MORE_STUFF4                     1  .00000005 FREQUENCY
MORE_STUFF3                     1  .00000005 FREQUENCY
MORE_STUFF2                     1  .00000005 FREQUENCY
MORE_STUFF10                    1  .00000005 FREQUENCY
MORE_STUFF1                     1  .00000005 FREQUENCY
ID                       10000000          0 HYBRID
CODE                        10000      .0001 HYBRID

We notice the same oddity of my previous post that all columns have histograms…

Let’s run the following query with an UPPER function-based predicate that returns only the one row:

SQL> select * from david where upper(name) = 'DAVID BOWIE 4242';

Execution Plan
----------------------------------------------------------
Plan hash value: 2426813604

-----------------------------------------------------------------------------------
| Id | Operation                 | Name  | Rows | Bytes | Cost (%CPU) | Time      |
-----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |       | 100K |   17M |    3350 (6) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | DAVID | 100K |   17M |    3350 (6) | 00:00:01  |
-----------------------------------------------------------------------------------

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

1 - storage(UPPER("NAME")='DAVID BOWIE 4242')
    filter(UPPER("NAME")='DAVID BOWIE 4242')

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
     263469 consistent gets
     263452 physical reads
          0 redo size
       1256 bytes sent via SQL*Net to client
        381 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

What does Automatic Indexing make of this scenario?

Basically, it does nothing. Currently, Automatic Indexing does NOT support such function-based indexes, even with equality based predicates (as of at least version 19.5.0.0.0). If we look at the next Automatic Indexing report:

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates           : 0
Indexes created            : 0
Space used                 : 0 B
Indexes dropped            : 0
SQL statements verified    : 2
SQL statements improved    : 0
SQL plan baselines created : 0
Overall improvement factor : 0x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

No such function-based index is ever created by Automatic Indexing:

SQL> select index_name, auto, constraint_index, visibility, compression, status, num_rows, leaf_blocks, clustering_factor from user_indexes where table_name='DAVID';

no rows selected

To improve the performance of this query, one has to manually create the necessary function-based index:

SQL> create index david_upper_name_i on david(upper(name));

Index created.

If we now re-run the query:

SQL> select name from david where upper(name) = 'DAVID BOWIE 4242';

Execution Plan
----------------------------------------------------------
Plan hash value: 2675555529

----------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name               | Rows  | Bytes | Cost (%CPU) | Time     |
----------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |                    |  100K | 4199K |    3175 (1) | 00:00:01 |
|  1 | TABLE ACCESS BY INDEX ROWID BATCHED | DAVID              |  100K | 4199K |    3175 (1) | 00:00:01 |
|* 2 | INDEX RANGE SCAN                    | DAVID_UPPER_NAME_I | 40000 |       |       3 (0) | 00:00:01 |
----------------------------------------------------------------------------------------------------------

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

2 - access(UPPER("NAME")='DAVID BOWIE 4242')

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

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

The query now uses the function-based index to significantly improve the performance of this query, with just 5 consistent gets.

Note however as with all function-based indexes, by default the estimated cardinality estimate and associated CBO costs are way off (100K rows are estimated, not the 1 row that is actually returned). This is due to the CBO having no real idea of the number and distribution of values coming out of the “black box” function-based predicate.

This is why Oracle automatically creates an hidden virtual column by which to store the necessary statistics associated to the function (in this case the SYS_NC00014$ column):

SQL> select column_name, num_distinct, density, histogram from dba_tab_cols where table_name='DAVID';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM
-------------------- ------------ ---------- ---------------
NAME                     10000000          0 HYBRID
MORE_STUFF9                     1  .00000005 FREQUENCY
MORE_STUFF8                     1  .00000005 FREQUENCY
MORE_STUFF7                     1  .00000005 FREQUENCY
MORE_STUFF6                     1  .00000005 FREQUENCY
MORE_STUFF5                     1  .00000005 FREQUENCY
MORE_STUFF4                     1  .00000005 FREQUENCY
MORE_STUFF3                     1  .00000005 FREQUENCY
MORE_STUFF2                     1  .00000005 FREQUENCY
MORE_STUFF10                    1  .00000005 FREQUENCY
MORE_STUFF1                     1  .00000005 FREQUENCY
ID                       10000000          0 HYBRID
CODE                        10000      .0001 HYBRID
SYS_NC00014$                                 NONE

But we need to first collect statistics on this hidden virtual column for the statistics to be populated:

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'DAVID', no_invalidate=> false, method_opt=> 'FOR ALL HIDDEN COLUMNS SIZE 1');

SQL> select column_name, num_distinct, density, histogram from dba_tab_cols where table_name='DAVID';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM
-------------------- ------------ ---------- ---------------
NAME                     10000000          0 HYBRID
MORE_STUFF9                     1  .00000005 FREQUENCY
MORE_STUFF8                     1  .00000005 FREQUENCY
MORE_STUFF7                     1  .00000005 FREQUENCY
MORE_STUFF6                     1  .00000005 FREQUENCY
MORE_STUFF5                     1  .00000005 FREQUENCY
MORE_STUFF4                     1  .00000005 FREQUENCY
MORE_STUFF3                     1  .00000005 FREQUENCY
MORE_STUFF2                     1  .00000005 FREQUENCY
MORE_STUFF10                    1  .00000005 FREQUENCY
MORE_STUFF1                     1  .00000005 FREQUENCY
ID                       10000000          0 HYBRID
CODE                        10000      .0001 HYBRID
SYS_NC00014$              9947366          0 HYBRID

Now the CBO has the necessary statistics by which to determine a much more accurate cardinality estimate for the function-based predicate and so potentially a more efficient execution plan:

SQL> select * from david where upper(name) = 'DAVID BOWIE 4242';

Execution Plan
----------------------------------------------------------
Plan hash value: 2675555529

----------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name               | Rows | Bytes | Cost (%CPU) | Time      |
----------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |                    |    1 |   200 |       4 (0) | 00:00:01  |
|  1 | TABLE ACCESS BY INDEX ROWID BATCHED | DAVID              |    1 |   200 |       4 (0) | 00:00:01  |
|* 2 | INDEX RANGE SCAN                    | DAVID_UPPER_NAME_I |    1 |       |       3 (0) | 00:00:01  |
----------------------------------------------------------------------------------------------------------

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

2 - access(UPPER("NAME")='DAVID BOWIE 4242')

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          1 recursive calls
          0 db block gets
          5 consistent gets
          0 physical reads
          0 redo size
       1256 bytes sent via SQL*Net to client
        381 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

With the virtual column statistics in place, the CBO now has the cardinality estimate of 1 and associated costs spot on, which is always a good thing.

This requirement to collect the necessary statistics on the associated virtual column created as a result of the function-based index to ensure the index is costed and used effectively is perhaps but one reason why function-based indexes are currently not supported by Automatic Indexing.

As always, this can always change in the future…

Oracle Database 19c Automatic Indexing: Invisible Indexes Oddity (Wild Eyed Boy From Freecloud) February 3, 2021

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Automatic Table Statistics, Autonomous Database, Autonomous Transaction Processing, CBO, Clustering Factor, Exadata, Histograms, Invisible Indexes, Oracle, Oracle Cloud, Oracle General, Oracle Indexes, Oracle Statistics, Oracle19c.
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There have been a couple of “oddities” in relation to both Oracle Autonomous Databases and Automatic Indexing behaviour that I’ve seen frequently enough now (on Oracle 19.5.0.0.0) to make it worth a quick blog article.

The following is a simple test case that highlights both these issues. I’ll begin with a basic table, that has the key column CODE with a selectivity that would likely make it too expensive to be accessed via an associated index.

SQL> create table pink_floyd (id number, code number, create_date date, name varchar2(42));

Table created.

SQL> insert into pink_floyd select rownum, ceil(dbms_random.value(0, 5000)), sysdate-mod(rownum, 50000)+1, 'Dark Side of the Moon' from dual connect by level <=10000000;

10000000 rows created.

SQL> commit;

Commit complete.

Importantly, I’ll next collect statistics on this table using all the default attributes, including allowing Oracle to decide the merits of any column histogram:

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

PL/SQL procedure successfully completed.

Note I’ve yet to run a single query against this table. And yet, if we look at the details of each of these columns:

SQL> select column_name, num_distinct, density, histogram from dba_tab_columns where table_name='PINK_FLOYD';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM
-------------------- ------------ ---------- ---------------
ID                        9705425          0 HYBRID
CODE                         4835     .00005 HYBRID
CREATE_DATE                 50357     .00002 HYBRID
NAME                            1 4.9639E-08 FREQUENCY

All the columns have a histogram !! This despite the columns not meeting either criteria normally required for a histogram, that the column be used in a SQL predicate AND for the column to have an uneven distribution of values.

None of these columns have yet to be used in a filtering predicate and none of these columns have a uneven distribution of values, even the CODE column as highlighted by looking at the minimum and maximum number of occurrences:

SQL> select min(code_count), max(code_count) from (select count(*) code_count from pink_floyd group by code);

MIN(CODE_COUNT) MAX(CODE_COUNT)
--------------- ---------------
           1845            2163

So it’s very odd for these histograms to be present.

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

SQL> select * from pink_floyd where code=42;

2012 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 1152280033

----------------------------------------------------------------------------------------
| Id | Operation                 | Name       | Rows | Bytes | Cost (%CPU) | Time      |
----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |            | 2068 | 82720 |    844 (11) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | PINK_FLOYD | 2068 | 82720 |    844 (11) | 00:00:01  |
----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42)
    filter("CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      63655 consistent gets
      63645 physical reads
          0 redo size
      38575 bytes sent via SQL*Net to client
        360 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
       2012 rows processed

The CBO currently has no choice but to use a FTS with no index currently present. But what will Automatic Indexing make of things? If we look at the next automatic indexing report:

 

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates                      : 2
Indexes created (visible / invisible) : 1 (0 / 1)
Space used (visible / invisible)      : 134.22 MB (0 B / 134.22 MB)
Indexes dropped                       : 0
SQL statements verified               : 1
SQL statements improved               : 0
SQL plan baselines created            : 0
Overall improvement factor            : 0x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

INDEX DETAILS
-------------------------------------------------------------------------------
The following indexes were created:
*: invisible
-------------------------------------------------------------------------------
----------------------------------------------------------------------------
| Owner | Table      | Index                  | Key  | Type   | Properties |
----------------------------------------------------------------------------
| BOWIE | PINK_FLOYD | * SYS_AI_dp2t0j12zux49 | CODE | B-TREE | NONE       |
----------------------------------------------------------------------------
-------------------------------------------------------------------------------

We notice that Oracle has created an Automatic Index, but it’s an INVISIBLE index !!

If we look at the details of this Automatic Index:

SQL> select index_name, auto, constraint_index, visibility, compression, status, num_rows, leaf_blocks, clustering_factor from user_indexes where table_name='PINK_FLOYD';

INDEX_NAME                AUT CON VISIBILIT COMPRESSION   STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
------------------------- --- --- --------- ------------- -------- ---------- ----------- -----------------
SYS_AI_dp2t0j12zux49      YES NO  INVISIBLE ADVANCED LOW  VALID      10000000       15369           9845256

The index is in an INVISIBLE/VALID state, not the usual INVISIBLE/UNUSABLE state for an index for which Automatic Indexing decides an index is not efficient enough to be implement.

This is NOT expected behaviour.

Usually INVISIBLE/VALID indexes are created when Automatic Indexing is in “REPORT ONLY” mode, although I have come across this scenario when statistics are stale or missing. But in this case, Automatic Indexing is in “IMPLEMENT” mode and the table has recently collected statistics, albeit with odd histograms present (hence why I think these issues to be related).

If we run the same query again:

SQL> select * from pink_floyd where code=42;

2012 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 1152280033

----------------------------------------------------------------------------------------
| Id | Operation                 | Name       | Rows | Bytes | Cost (%CPU) | Time      |
----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |            | 2068 | 82720 |    844 (11) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | PINK_FLOYD | 2068 | 82720 |    844 (11) | 00:00:01  |
----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42)
    filter("CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      63655 consistent gets
      63645 physical reads
          0 redo size
      38575 bytes sent via SQL*Net to client
        360 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
       2012 rows processed

The CBO has again no option but to use the FTS as Invisible indexes can not be considered by the CBO. However, it’s important to note that such an index would not be used by the CBO anyways as it would be deemed too expensive to use than the current FTS.

If you’re relying on Automatic Indexing and have it in Implement mode, I would recommend checking for any indexes in this INVISIBLE/VALID state as they’re an indication that something has very likely gone wrong…

Oracle Database 19c Automatic Indexing: Index Compression Update (New Morning) January 27, 2021

Posted by Richard Foote in 19c, 19c New Features, Advanced Index Compression, Autonomous Database, Autonomous Transaction Processing, AUTO_INDEX_COMPRESSION, Exadata, Index Column Order, Index Compression, Oracle, Oracle Blog, Oracle General, Oracle Indexes, Oracle19c.
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I was reminded in a recent comment by Rajeshwaran Jeyabal that I hadn’t updated my post on Automatic Indexing with Advanced Compression that’s in need of a couple of amendments.

Initially when Automatic Indexing was released, the ability to set Advanced Compression was NOT included in the official documentation, although the EXEC DBMS_AUTO_INDEX.CONFIGURE( ‘AUTO_INDEX_COMPRESSION‘ , ‘ON’); option was readily accessible. This has now been fixed and the associated doco on setting Advanced Compression for Automatic Indexes can be found here.

The other significant change is that Advanced Compression Low is now the default behaviour when Automatic Indexes are created in the Oracle ATP Autonomous Database Cloud environment. This makes sense in that if you have access to the Advanced Compression option, setting all indexes to Advanced Compression Low is the no-brainer setting as I’ve discussed previously. So several of my more recent posts show how Automatic Indexes have been created with Advanced Compression Low set.

What hasn’t changed however is how Automatic Indexing does NOT consider the efficiency of an index in relation to Index Compression when deciding how to order the columns within the index.

The default order of columns within an index (when other SQL predicates are not a consideration) is simply the order by which the columns appear within the table. Even though an index could be significantly smaller thanks to Index Compression if columns with more repeated values are ordered first within an index, this is not something Automatic Indexing currently considers.

The demo in my original piece still works exactly the same in the current 19c database versions of the ATP Autonomous Cloud environments. Manually created indexes can be significantly smaller if index columns are reordered or dropped entirely if they don’t provide filtering benefits.

When reading my blog, please do take note of the date of blog piece, especially in relation to Automatic Indexing. Things are only accurate as at time of publication and may change subsequently.

I thank Rajeshwaran for getting me to pull my finger out and update my blog accordingly…

Oracle 19c Automatic Indexing: Non-Equality Predicates Part II (Let’s Spend The Night Together) January 21, 2021

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Full Table Scans, Non-Equality Predicates, Oracle, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle19c, Performance Tuning.
1 comment so far

In my previous post in this series, I discussed out Automatic Indexing currently does not consider Non-Equality predicates. Automatic Indexing will index columns based only on Equality predicates.

So how does Oracle handle the scenario when an SQL has a mixture of both Equality and Non-Equality predicates?

I’ll begin by creating two very similar tables, but with the second table having a more selective CODE column:

SQL> create table pink_floyd (id number, code number, create_date date, name varchar2(42));

Table created.

SQL> insert into pink_floyd select rownum, ceil(dbms_random.value(0, 5000)), sysdate-mod(rownum, 50000)+1, 'Dark Side of the Moon'
from dual connect by level <=10000000;

10000000 rows created.

SQL> commit;

Commit complete.

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

PL/SQL procedure successfully completed.


SQL> create table pink_floyd1 (id number, code number, create_date date, name varchar2(42));

Table created.

SQL> insert into pink_floyd1 select rownum, ceil(dbms_random.value(0, 25000)), sysdate-mod(rownum, 50000)+1, 'Dark Side of the Moon'
from dual connect by level <=10000000;

10000000 rows created.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'PINK_FLOYD1');

PL/SQL procedure successfully completed.

 

So table PINK_FLOYD has 5,000 distinct CODE values, whereas table PINK_FLOYD1 has 25,000 distinct CODE values.

I’ll next run the following identical SQLs, which both use an Equality predicate on the CODE column and a Non-Equality predicate on the CREATE_DATE column. The CODE column provides some filtering (more so with the PINK_FLOYD1 table) but in combination with the CREATE_DATE column, results in the ultimate filtering with no rows returned:

 

SQL> select * from pink_floyd where code=42 and create_date> '19-JAN-2021';

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 1152280033

----------------------------------------------------------------------------------------
| Id | Operation                 | Name       | Rows | Bytes | Cost (%CPU) | Time      |
----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |            |    1 |    40 |    844 (11) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | PINK_FLOYD |    1 |    40 |    844 (11) | 00:00:01  |
----------------------------------------------------------------------------------------

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

1 - storage("CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-ddhh24:mi:ss') AND "CODE"=42)
     filter("CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-ddhh24:mi:ss') AND "CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      63660 consistent gets
      63649 physical reads
          0 redo size
        426 bytes sent via SQL*Net to client
        380 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          0 rows processed


SQL> select * from pink_floyd1 where code=42 and create_date> '19-JAN-2021';

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 564520720

-----------------------------------------------------------------------------------------
| Id | Operation                 | Name        | Rows | Bytes | Cost (%CPU) | Time      |
-----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |             |    1 |    41 |    856 (11) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | PINK_FLOYD1 |    1 |    41 |    856 (11) | 00:00:01  |
-----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42 AND "CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00','syyyy-mm-dd hh24:mi:ss'))
     filter("CODE"=42 AND "CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00','syyyy-mm-dd hh24:mi:ss'))

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      64424 consistent gets
      64413 physical reads
          0 redo size
        426 bytes sent via SQL*Net to client
        381 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          0 rows processed

 

So how does Automatic Indexing handle this scenario. If we look at the subsequent Automatic Indexing report (highlights only):

 

INDEX DETAILS
-------------------------------------------------------------------------------
The following indexes were created:
*: invisible
-------------------------------------------------------------------------------
-----------------------------------------------------------------------------
| Owner | Table       | Index                | Key  | Type   | Properties   |
-----------------------------------------------------------------------------
| BOWIE | PINK_FLOYD1 | SYS_AI_96snkmu4sk44g | CODE | B-TREE | NONE         |
-----------------------------------------------------------------------------
-------------------------------------------------------------------------------


-------------------------------------------------------------------------------
Parsing Schema Name : BOWIE
SQL ID              : 7wag3gbk0b3tm
SQL Text            : select * from pink_floyd1 where code=42 and create_date> '19-JAN-2021'
Improvement Factor  : 64442.3x

Execution Statistics:
-----------------------------
                      Original Plan                Auto Index Plan
                      ---------------------------- ----------------------------
Elapsed Time (s):     568513                       2771
CPU Time (s):         275534                       1874
Buffer Gets:          1031078                      406
Optimizer Cost:       856                          405
Disk Reads:           1030609                      3
Direct Writes:        0                            0
Rows Processed:       0                            0
Executions:           16                           1

PLANS SECTION
---------------------------------------------------------------------------------------------

- Original
-----------------------------
Plan Hash Value : 564520720

-----------------------------------------------------------------------------------
| Id | Operation                 | Name        | Rows | Bytes | Cost | Time       |
-----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |             |      |       |  856 |            |
|  1 | TABLE ACCESS STORAGE FULL | PINK_FLOYD1 |    1 |    41 |  856 | 00:00:01   |
-----------------------------------------------------------------------------------

Notes
-----
- dop = 1
- px_in_memory_imc = no
- px_in_memory = no

- With Auto Indexes
-----------------------------
Plan Hash Value : 2703636439

-------------------------------------------------------------------------------------------------------
| Id  | Operation                           | Name                 | Rows | Bytes | Cost | Time       |
-------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                    |                      |    1 |    41 |  405 | 00:00:01   |
| * 1 | TABLE ACCESS BY INDEX ROWID BATCHED | PINK_FLOYD1          |    1 |    41 |  405 | 00:00:01   |
| * 2 | INDEX RANGE SCAN                    | SYS_AI_96snkmu4sk44g |  403 |       |    3 | 00:00:01   |
-------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
------------------------------------------
* 1 - filter("CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))
* 2 - access("CODE"=42)

Notes
-----
- Dynamic sampling used for this statement ( level = 11 )

 

If we look at the definitions of all indexes currently on these tables:

SQL> select index_name, auto, visibility, compression, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='PINK_FLOYD';

INDEX_NAME                     AUT VISIBILIT COMPRESSION   STATUS   NUM_ROWS   LEAF_BLOCKS CLUSTERING_FACTOR
------------------------------ --- --------- ------------- -------- ---------- ----------- -----------------
SYS_AI_dp2t0j12zux49           YES INVISIBLE ADVANCED LOW  UNUSABLE   10000000       21702           4161898

SQL> select index_name, column_name, column_position from user_ind_columns where table_name='PINK_FLOYD';

INDEX_NAME                     COLUMN_NAME     COLUMN_POSITION
------------------------------ --------------- ---------------
SYS_AI_dp2t0j12zux49           CODE                          1


SQL> select index_name, auto, visibility, compression, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='PINK_FLOYD1';

INDEX_NAME                     AUT VISIBILIT COMPRESSION   STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
------------------------------ --- --------- ------------- -------- ---------- ----------- -----------------
SYS_AI_96snkmu4sk44g           YES VISIBLE   ADVANCED LOW  VALID      10000000       15400           9969473

SQL> select index_name, column_name, column_position from user_ind_columns where table_name='PINK_FLOYD1';

INDEX_NAME                     COLUMN_NAME     COLUMN_POSITION
------------------------------ --------------- ---------------
SYS_AI_96snkmu4sk44g           CODE                          1

 

In both cases, Automatic Indexing only created an index on the CODE column, as it was the only column with an Equality predicate.

However, the Automatic Index on the table PINK_FLOYD remained in an INVISIBLE/UNUSABLE. That’s because an index on only the CODE column was not efficient enough to improve the performance of the SQL, due to the filtering not being sufficient enough and because of the relatively poor Clustering Factor.

The index on the table PINK_FLOYD1 was eventually created as a VISIBLE/VALID index, as its better filtering was sufficient to actually improve the performance of the SQL.

So if we re-run the first query:

SQL> select * from pink_floyd where code=42 and create_date> '19-JAN-2021';

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 1152280033

----------------------------------------------------------------------------------------
| Id | Operation                 | Name       | Rows | Bytes | Cost (%CPU) | Time      |
----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |            |    1 |    40 |    844 (11) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | PINK_FLOYD |    1 |    40 |    844 (11) | 00:00:01  |
----------------------------------------------------------------------------------------

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

1 - storage("CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-ddhh24:mi:ss') AND "CODE"=42)
     filter("CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-ddhh24:mi:ss') AND "CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      63660 consistent gets
      63649 physical reads
          0 redo size
        426 bytes sent via SQL*Net to client
        380 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          0 rows processed

It continues to use a Full Table Scan.

If we re-run the second query:

 

SQL> select * from pink_floyd1 where code=42 and create_date> '19-JAN-2021';

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 2703636439

------------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name                 | Rows | Bytes | Cost (%CPU) | Time      |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |                      |    1 |    41 |     415 (0) | 00:00:01  |
|* 1 | TABLE ACCESS BY INDEX ROWID BATCHED | PINK_FLOYD1          |    1 |    41 |     415 (0) | 00:00:01  |
|* 2 | INDEX RANGE SCAN                    | SYS_AI_96snkmu4sk44g |  412 |       |       3 (0) | 00:00:01  |
------------------------------------------------------------------------------------------------------------

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

1 - filter("CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-dd hh24:mi:ss'))
2 - access("CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

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

 

If now uses the newly created Automatic Index, with an improved 406 Consistent Gets (down from the previous 64424 Consistent Gets with the FTS).

BUT if we were to manually create an index on BOTH CODE and CREATE_DATE columns:

SQL> create index pink_floyd1_code_create_date_i on pink_floyd1(code, create_date) compress advanced low;

Index created.

SQL> select * from pink_floyd1 where code=42 and create_date> '19-JAN-2021';

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 3366491378

----------------------------------------------------------------------------------------------------------------------
| Id | Operation                           | Name                           | Rows | Bytes | Cost (%CPU) | Time      |
----------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                    |                                |    1 |    41 |       4 (0) | 00:00:01  |
|  1 | TABLE ACCESS BY INDEX ROWID BATCHED | PINK_FLOYD1                    |    1 |    41 |       4 (0) | 00:00:01  |
|* 2 | INDEX RANGE SCAN                    | PINK_FLOYD1_CODE_CREATE_DATE_I |    1 |       |       3 (0) | 00:00:01  |
----------------------------------------------------------------------------------------------------------------------

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

2 - access("CODE"=42 AND "CREATE_DATE">TO_DATE(' 2021-01-19 00:00:00', 'syyyy-mm-dd hh24:mi:ss') AND
"CREATE_DATE" IS NOT NULL)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

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

 

Performance improves significantly further, by reducing Consistent Gets down to just 3.

So if you have SQL statements with a mixture of both Equality and Non-Equality predicates, you may encounter these 2 scenarios:

A potentially efficient index that is not created at all as the filtering on just the Equality based predicates are not sufficient to create a viable index, or

A potentially suboptimal Automatic Index that doesn’t contain useful filtering columns because they’re used in Non-Equality predicates…

Announcement: Both Of My Oracle Webinars Scheduled For February 2021 !! January 19, 2021

Posted by Richard Foote in Oracle, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Indexing Internals Webinar, Oracle Performance Diagnostics and Tuning Webinar, Richard Foote Seminars.
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I’m please to announce that both of my highly acclaimed webinars scheduled for February are now confirmed.

These webinars are a must for any Oracle DBA or Developer interested in designing, developing or maintaining high performance, highly scalable Oracle-based applications or databases.

However only a few places are currently available on each webinar with numbers very strictly limited, as I only run small classes to give every attendee the opportunity to get the most from the training experience.

Webinar details are as follows:

 

8-12 February 2021 (5pm-9pm AEDT) – Oracle Indexing Internals and Best Practices Webinar  (International Customers Only)

This seminar examines most available Oracle index structures/options and discusses in considerable detail how indexes function, how/when they should be used and how they should be maintained. It covers many useful tips and strategies to maximise the benefits of indexes on application/database performance and scalability, as well as in maximising Oracle database investments. Much of the material is exclusive to this seminar and is not generally available in Oracle documentation or in Oracle University courses.

 

23-26 February 2021 (5pm-9pm AEDT) – Oracle Performance Diagnostics and Tuning Webinar
(International Customers Only)

The seminar will detail how to maximise the performance of both Oracle databases and associated applications and how to diagnose and address any performance issues as quickly and effectively as possible. It also provides opportunity to have your own AWR reports analysed to identify performance issues.

 

You can also purchase tickets to both webinars at a special combo discount:

Both “Oracle Indexing Internals and Best Practices” and “Oracle Performance Diagnostics and Tuning” Webinars running in February 2021:   (International Customers Only)

 

Each webinar is $1,800 (AUS) individually and $3,000 (AUS) when both purchased in the combo package (the Buy Now functionality is available for International Customers Only).

Please Note: If based in Australia, please contact me (at richard@richardfooteconsulting.com) for a tax invoice that includes GST and instructions on how to pay.

 

Please contact me directly if you wish to pay via invoice and direct bank transfer or if you have any questions.

 

For full content details of the “Oracle Indexing Internals and Best Practices” Webinar: https://richardfooteconsulting.com/indexing-seminar/

For full content details of the “Oracle Performance Diagnostics and Tuning” Webinar: https://richardfooteconsulting.com/performance-tuning-seminar/

 

Hopefully you can take advantage of the opportunity to participate in this unique training experience (see here for some testimonials)…

Oracle 19c Automatic Indexing: Non-Equality Predicates Part I (Lucy Can’t Dance) January 14, 2021

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Database, Autonomous Transaction Processing, Exadata, Full Table Scans, Non-Equality Predicates, Oracle, Oracle Blog, Oracle Cloud, Oracle Indexes, Oracle19c.
4 comments

 

I’ve been waiting a while before posting a series on the various limitations associated with Automatic Indexing, in order to see how the feature matures over time.

The following have all been re-tested post 1 January 2021 on the Autonomous ATP Database Cloud service, using Oracle Database version 19.5.0.0.0.

In the Oracle Documentation (including version 21c), the only limitations with regard Automatic Indexing listed are the following:

  • Auto indexes are local B-tree indexes.
  • Auto indexes can be created for partitioned as well as non-partitioned tables.
  • Auto indexes cannot be created for temporary tables.

Well, as I discussed in the previous series on Automatic Indexing on Partitioned tables, we already saw how Oracle can actually also create Non-Partitioned (Global) indexes. So the limitation on Automatic Indexes being “local” indexes is not actually correct, even with 19c.

But are there other limitations that are not officially documented?

If you look at every example I’ve used previously with regard Automatic Indexing, they all feature Equality predicates. In the following examples, I’m going to run a series on Range Scan predicates that heavily filter and would benefit greatly from an index.

I first create a simple table with 10M rows:

SQL> create table ziggy1 (id number, code number, name varchar2(42));

Table created.

SQL> insert into ziggy1 select rownum, mod(rownum, 1000000)+1, 'David Bowie' from dual connect by level <= 10000000;

10000000 rows created.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats(ownname=>null, tabname=>'ZIGGY1');

PL/SQL procedure successfully completed.

 

I then run the following range scan queries several times that each return only a few rows:

SQL> select * from ziggy1 where id between 42 and 50;

9 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 4062853157

------------------------------------------------------------------------------------
| Id | Operation                 | Name   | Rows | Bytes | Cost (%CPU) | Time      |
------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |        |    8 |   184 |    538 (14) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | ZIGGY1 |    8 |   184 |    538 (14) | 00:00:01  |
------------------------------------------------------------------------------------

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

1 - storage("ID"<=50 AND "ID">=42)
    filter("ID"<=50 AND "ID">=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      39436 consistent gets
      39425 physical reads
          0 redo size
        596 bytes sent via SQL*Net to client
        369 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          9 rows processed


SQL> select * from ziggy1 where id < 0;

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 4062853157

------------------------------------------------------------------------------------
| Id | Operation                 | Name   | Rows | Bytes | Cost (%CPU) | Time      |
------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |        |    1 |    23 |    538 (14) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | ZIGGY1 |    1 |    23 |    538 (14) | 00:00:01  |
------------------------------------------------------------------------------------

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

1 - storage("ID"<0)
    filter("ID"<0)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      39436 consistent gets
      39425 physical reads
          0 redo size
        364 bytes sent via SQL*Net to client
        344 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          0 rows processed

SQL> select * from ziggy1 where id > 100000000000;

no rows selected

Execution Plan
----------------------------------------------------------
Plan hash value: 4062853157

------------------------------------------------------------------------------------
| Id | Operation                 | Name   | Rows | Bytes | Cost (%CPU) | Time      |
------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |        |    1 |    23 |    538 (14) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | ZIGGY1 |    1 |    23 |    538 (14) | 00:00:01  |
------------------------------------------------------------------------------------

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

1 - storage("ID">100000000000)
    filter("ID">100000000000)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      39436 consistent gets
      39425 physical reads
          0 redo size
        364 bytes sent via SQL*Net to client
        355 bytes received via SQL*Net from client
          1 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          0 rows processed

If we look at the subsequent Automatic Indexing report:

SQL> select dbms_auto_index.report_last_activity() report from dual;

REPORT
--------------------------------------------------------------------------------
GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start              : 13-JAN-2021 11:55:37
Activity end                : 13-JAN-2021 11:56:20
Executions completed        : 1
Executions interrupted      : 0
Executions with fatal error : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates           : 0
Indexes created            : 0
Space used                 : 0 B
Indexes dropped            : 0
SQL statements verified    : 3
SQL statements improved    : 0
SQL plan baselines created : 0
Overall improvement factor : 0x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

We notice NO Automatic Indexes were created.

We can run these queries endlessly and Automatic Indexing will never create associated Automatic Indexes:

SQL> select index_name, auto, constraint_index, visibility from user_indexes where table_name='ZIGGY1';

no rows selected

These queries are doomed to perform Full Table Scans unless indexes are manually created:

SQL> select * from ziggy1 where id between 42 and 50;

9 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 4062853157

------------------------------------------------------------------------------------
| Id | Operation                 | Name   | Rows | Bytes | Cost (%CPU) | Time      |
------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |        |    8 |   184 |    538 (14) | 00:00:01  |
|* 1 | TABLE ACCESS STORAGE FULL | ZIGGY1 |    8 |   184 |    538 (14) | 00:00:01  |
------------------------------------------------------------------------------------

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

1 - storage("ID"<=50 AND "ID">=42)
    filter("ID"<=50 AND "ID">=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      39436 consistent gets
      39425 physical reads
          0 redo size
        596 bytes sent via SQL*Net to client
        369 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          9 rows processed

 

Currently Automatic Indexes do not support Non-Equality predicates. Automatic Indexes are only created based on Equality-based predicates.

Obviously, Automatic Indexing is a fabulous feature and this might all change in the future. But with Non-Equality predicates so prevalent in SQL, it’s vital to note this current limitation when using and relying on Automatic Indexing…

Oracle 19c Automatic Indexing: Indexing Partitioned Tables Part II (Neighbourhood Threat) January 13, 2021

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Transaction Processing, CBO, Exadata, Local Indexes, Oracle, Oracle Cloud, Oracle General, Oracle Indexes, Oracle19c, Partitioned Indexes, Partitioning.
4 comments

In my first post on Automatic Indexing on Partitioned Tables, I discussed how Automatic Indexing (AI) can now create a Non-Partitioned index if deemed the most effective indexing structure (this wasn’t supported when AI was initially released). A Non-Partitioned index is indeed likely the most efficient indexing structure if the underlying table has many partitions and associated SQL equality predicates only reference non-partition key columns. A Non-Partitioned index ensure Oracle only needs to scan the single index structure and not all the partitions of a Local index.

But what if SQLs do reference the column by which the underlying table is partitioned?

The following SQL has an equality filtering predicate on the RELEASE_DATE column, the column by which the BIG_BOWIE1 table is partitioned:

SQL> SELECT * FROM big_bowie1 where release_date = to_date('2013-12-30 22:15:25', 'syyyy-mm-dd hh24:mi:ss');

no rows selected

If we look at the subsequent AI report:

INDEX DETAILS
-------------------------------------------------------------------------------
The following indexes were created:
*: invisible
-------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------
| Owner | Table      | Index                | Key          | Type   | Properties |
------------------------------------------------------------------------------------------------
| BOWIE | BIG_BOWIE1 | SYS_AI_14gpurjp8m76s | RELEASE_DATE | B-TREE | LOCAL      |
------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------

 

We notice that Automatic Indexing has in this instance created a Local Index.

If we look further down the AI report:

-------------------------------------------------------------------------------
Parsing Schema Name : BOWIE
SQL ID              : 4mm3mbkk38pa8
SQL Text            : SELECT * FROM big_bowie1 where release_date = to_date('2013-12-30 22:15:25', 'syyyy-mm-dd hh24:mi:ss')
Improvement Factor  : 8339x

Execution Statistics:
-----------------------------
                  Original Plan                Auto Index Plan
                  ---------------------------- ----------------------------
Elapsed Time (s): 146957                       71
CPU Time (s):     146124                       71
Buffer Gets:      16678                        3
Optimizer Cost:   162                          4
Disk Reads:       0                            0
Direct Writes:    0                            0
Rows Processed:   0                            0
Executions:       2                            1

PLANS SECTION
---------------------------------------------------------------------------------------------

- Original
-----------------------------
Plan Hash Value : 4031749531

-----------------------------------------------------------------------------------
| Id | Operation                 | Name       | Rows | Bytes | Cost | Time        |
-----------------------------------------------------------------------------------
| 0  | SELECT STATEMENT          |            |      |       |  162 |             |
| 1  | PARTITION RANGE SINGLE    |            | 3602 | 93652 |  162 | 00:00:01    |
| 2  | TABLE ACCESS STORAGE FULL | BIG_BOWIE1 | 3602 | 93652 |  162 | 00:00:01    |
-----------------------------------------------------------------------------------

Notes
-----
- dop = 1
- px_in_memory_imc = no
- px_in_memory = no

- With Auto Indexes
-----------------------------
Plan Hash Value : 4049653350

--------------------------------------------------------------------------------------------------------------
| Id  | Operation                                 | Name                 | Rows | Bytes | Cost | Time        |
--------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                          |                      |    3 |    78 |    4 | 00:00:01    |
|   1 | PARTITION RANGE SINGLE                    |                      |    3 |    78 |    4 | 00:00:01    |
|   2 | TABLE ACCESS BY LOCAL INDEX ROWID BATCHED | BIG_BOWIE1           |    3 |    78 |    4 | 00:00:01    |
| * 3 | INDEX RANGE SCAN                          | SYS_AI_14gpurjp8m76s |    1 |       |    3 | 00:00:01    |
--------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
------------------------------------------
* 3 - access("RELEASE_DATE"=TO_DATE(' 2013-12-30 22:15:25', 'syyyy-mm-dd hh24:mi:ss'))

Notes
-----
- Dynamic sampling used for this statement ( level = 11 )

 

We can see Automatic Indexing has created the index because it provides an average Improvement Factor of 8339x. As the necessary indexed column(s) matches the table partitioning key, it makes sense for the associated index be a Local index as Oracle is certain which specific index partition to visit based on the value of the equality predicate.

If we look at the details of this new AI:

SQL> select index_name, auto, constraint_index, visibility, compression, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='BIG_BOWIE1';

INDEX_NAME                     AUT CON VISIBILIT COMPRESSION   STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
------------------------------ --- --- --------- ------------- -------- ---------- ----------- -----------------
SYS_AI_14gpurjp8m76s           YES NO  VISIBLE   ADVANCED LOW  N/A        20000000       30742          19941449
SYS_AI_8armv0hqq73fa           YES NO  VISIBLE   ADVANCED LOW  VALID      20000000       42697          19995451

SQL> select index_name, column_name, column_position from user_ind_columns where table_name='BIG_BOWIE1' order by index_name, column_position;

INDEX_NAME                     COLUMN_NAME     COLUMN_POSITION
------------------------------ --------------- ---------------
SYS_AI_14gpurjp8m76s           RELEASE_DATE                  1
SYS_AI_8armv0hqq73fa           TOTAL_SALES                   1

SQL> SELECT index_name, partitioning_type, partition_count, locality FROM user_part_indexes WHERE table_name = 'BIG_BOWIE1';

INDEX_NAME                     PARTITION PARTITION_COUNT LOCALI
------------------------------ --------- --------------- ------
SYS_AI_14gpurjp8m76s           RANGE                   8 LOCAL

SQL> select index_name, partition_name, status, compression from user_ind_partitions
where index_name in (select index_name from user_indexes where table_name='BIG_BOWIE1')
order by partition_position;

INDEX_NAME           PARTITION_NAME       STATUS   COMPRESSION
-------------------- -------------------- -------- -------------
SYS_AI_14gpurjp8m76s ALBUMS_2013          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2014          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2015          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2016          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2017          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2018          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2019          USABLE   ADVANCED LOW
SYS_AI_14gpurjp8m76s ALBUMS_2020          USABLE   ADVANCED LOW

 

We can see that indeed, a Visible, Usable, Local index was created by Automatic Indexing.

So depending on the column(s) within the index, Automatic Indexing can potentially create either a Local or Non-Partitioned index when indexing a partitioned table.

Oracle 19c Automatic Indexing: Currently Broken In Autonomous ATP Databases Part II (Fix You) January 12, 2021

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Database, Autonomous Transaction Processing, Oracle, Oracle General, Oracle Indexes.
2 comments

 

Firstly, thank you for all those who contacted me regarding the issue with Oracle Automatic Indexing (AI) having stopped working within the Autonomous ATP Database Cloud service. It appears this issue was indeed widely spread and impacted numerous (if not all) Autonomous ATP Database Cloud services.

This was all possibly due to (unpublished) bug 32151108 that results in a STOPPED AI task status due to No Data Found exception.

The good news is that this all appears to now be fixed (at least in the Sydney Data Centre from at least 12th January 2021). I logged on for the first time in some weeks yesterday, where the AI tasks were again running successfully and creating the necessary indexes. As the cloud service had been stopped, upon restarting the database, the AI tasks had to address the significant backlog of SQL statements that had built up and needed to be actioned.

In the coming days, I’ll run a number of tests to confirm that all indeed is now well.

On Twitter Tanel Poder made the following pertinent comment:

The quality of support org & maintenance is even more important when consuming the entire DB platform as a service, with no access to OS, internals and patching yourself…

I couldn’t agree more.

Oracle 19c Automatic Indexing: Currently Broken In Autonomous ATP Databases? (What In The World) December 17, 2020

Posted by Richard Foote in 19c, Automatic Indexing, Autonomous Transaction Processing, Oracle Indexes.
1 comment so far

 

I’ve been playing with the free tier Oracle Autonomous Databases for quite some time, but unfortunately in recent times, I’ve hit a bit of a snag. The Automatic Index capability appears to be currently broken…

The Automatic Indexing task appears to have stopped running, yes even with the AUTO_INDEX_MODE set to “IMPLEMENT” and with a range of SQL workloads in badly need of new indexes.

I even terminated and created a new Autonomous ATP environment and once all set for Automatic Indexing (by setting AUTO_INDEX_MODE to ‘IMPLEMENT’, AUTO_INDEX_SCHEMA to a number of schemas and running index deficient SQL workloads), still no go, with the Automatic Indexing tasks no longer running.

My environments are specifically the always free Autonomous ATP environments running 19c from the Sydney data centre. 21c is not yet available in Sydney, but 19c is meant to be the stable recommended environment, so…

Note: As it’s the Autonomous Database environments, the ADMIN power user only has restricted privileges and can’t manually run procedures such as dbms_auto_index_internal.task_proc().

I’ve had a look through MOS and was unable to find anything of use.

I’ve communicated with a couple of folks and they also seem to be having similar issues.

If anyone else is having problems running Automatic Indexing in the Autonomous Database environments or have suggestions on how to address these issues, would love to hear from you.

 

UPDATE: This issue has now been fixed, see Part II for the details.

Oracle 19c Automatic Indexing: Indexing Partitioned Tables Part I (Conversation Piece) October 14, 2020

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Index Access Path, Local Indexes, Oracle, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle19c, Partitioned Indexes, Partitioning, Performance Tuning.
1 comment so far

In this little series, I’m going to discuss how Automatic Indexing works in relation to Partitioning.

I’ve discussed Indexing and Partitioning many times previously and how Oracle has various options when indexing a partitioned table:

  • Non-Partitioned Index
  • Globally Partitioned Index
  • Locally Partitioned Index

So the question(s) are how does Automatic Indexing handle scenarios with partitioned objects?

A very important point to make at the start is that based on my research, the answer has already changed significantly since Automatic Indexing was first released. So it’s important to understand that Automatic Indexing is an ever evolving capability, that will advance and improve as time goes on.

I’ll focus on how the feature currently works (as of Oracle Database 19.5), but will mention previously identified behaviour as a reference on how things can easily change.

In my first simple little example, I’m just going to create a range-partitioned table, partitioned based on RELEASE_DATE, with a partition for each year’s worth of data:

SQL> CREATE TABLE big_bowie1(id number, album_id number, country_id number, release_date date,
total_sales number) PARTITION BY RANGE (release_date)
(PARTITION ALBUMS_2013 VALUES LESS THAN (TO_DATE('01-JAN-2014', 'DD-MON-YYYY')),
PARTITION ALBUMS_2014 VALUES LESS THAN (TO_DATE('01-JAN-2015', 'DD-MON-YYYY')),
PARTITION ALBUMS_2015 VALUES LESS THAN (TO_DATE('01-JAN-2016', 'DD-MON-YYYY')),
PARTITION ALBUMS_2016 VALUES LESS THAN (TO_DATE('01-JAN-2017', 'DD-MON-YYYY')),
PARTITION ALBUMS_2017 VALUES LESS THAN (TO_DATE('01-JAN-2018', 'DD-MON-YYYY')),
PARTITION ALBUMS_2018 VALUES LESS THAN (TO_DATE('01-JAN-2019', 'DD-MON-YYYY')),
PARTITION ALBUMS_2019 VALUES LESS THAN (TO_DATE('01-JAN-2020', 'DD-MON-YYYY')),
PARTITION ALBUMS_2020 VALUES LESS THAN (MAXVALUE));

Table created.

 

I’ll now add about 8 years worth of data:

SQL> INSERT INTO big_bowie1 SELECT rownum, mod(rownum,5000)+1, mod(rownum,100)+1, sysdate-mod(rownum,2800),
ceil(dbms_random.value(1,500000)) FROM dual CONNECT BY LEVEL <= 10000000;

10000000 rows created.

SQL> COMMIT;

Commit complete.

 

As discussed previously, I’ll importantly collect statistics:

SQL> exec dbms_stats.gather_table_stats(ownname=> null, tabname=> 'BIG_BOWIE1');

PL/SQL procedure successfully completed.

 

I’ll now run the following very selective query based the TOTAL_SALES column that is NOT part of the partitioning key:

 

SQL> SELECT * FROM big_bowie1 WHERE total_sales = 42;

19 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 2468051548

---------------------------------------------------------------------------------------------------------
| Id | Operation                | Name       | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop     |
---------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT         |            |   20 |   520 |    643 (15)| 00:00:01 |       |           |
|  1 | PARTITION RANGE ALL      |            |   20 |   520 |    643 (15)| 00:00:01 |     1 |         8 |
|* 2 | TABLE ACCESS STORAGE FULL| BIG_BOWIE1 |   20 |   520 |    643 (15)| 00:00:01 |     1 |         8 |
---------------------------------------------------------------------------------------------------------

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

2 - storage("TOTAL_SALES"=42)
    filter("TOTAL_SALES"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      44014 consistent gets
       9516 physical reads
          0 redo size
       1107 bytes sent via SQL*Net to client
        369 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
         19 rows processed

 

Without an index in place, the CBO has no choice but to use a FTS. But what will Automatic Indexing make of things?

If we look at the next Automatic Indexing report:

 

SQL> select dbms_auto_index.report_last_activity() from dual;

GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start              : 13-OCT-2020 01:47:48
Activity end                : 13-OCT-2020 02:59:48
Executions completed        : 1
Executions interrupted      : 0
Executions with fatal error : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates                             : 1
Indexes created (visible / invisible)        : 1 (1 / 0)
Space used (visible / invisible)             : 184.55 MB (184.55 MB / 0 B)
Indexes dropped                              : 0
SQL statements verified                      : 2
SQL statements improved (improvement factor) : 1 (44119.6x)
SQL plan baselines created                   : 0
Overall improvement factor                   : 25135.8x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

INDEX DETAILS
-------------------------------------------------------------------------------
The following indexes were created:
*: invisible
-------------------------------------------------------------------------------
---------------------------------------------------------------------------------
| Owner | Table      | Index                | Key         | Type   | Properties |
---------------------------------------------------------------------------------
| BOWIE | BIG_BOWIE1 | SYS_AI_2zt7rg40mxa4n | TOTAL_SALES | B-TREE | NONE       |
---------------------------------------------------------------------------------
-------------------------------------------------------------------------------

VERIFICATION DETAILS
-------------------------------------------------------------------------------
The performance of the following statements improved:
-------------------------------------------------------------------------------
Parsing Schema Name : BOWIE
SQL ID              : chwm2gubm8fx9
SQL Text            : SELECT * FROM big_bowie1 WHERE total_sales = 42
Improvement Factor  : 44119.6x

Execution Statistics:
-----------------------------
                     Original Plan                Auto Index Plan
                     ---------------------------- ----------------------------
Elapsed Time (s):    4387193                      1173
CPU Time (s):        2599423                      1037
Buffer Gets:         749507                       22
Optimizer Cost:      643                          22
Disk Reads:          470976                       2
Direct Writes:       0                            0
Rows Processed:      323                          19
Executions:          17                           1

PLANS SECTION
---------------------------------------------------------------------------------------------

- Original
-----------------------------
Plan Hash Value : 2468051548

-----------------------------------------------------------------------------------
| Id | Operation                 | Name       | Rows | Bytes | Cost | Time        |
-----------------------------------------------------------------------------------
|  0 | SELECT STATEMENT          |            |      |       |  643 |             |
|  1 | PARTITION RANGE ALL       |            |   20 |   520 |  643 | 00:00:01    |
|  2 | TABLE ACCESS STORAGE FULL | BIG_BOWIE1 |   20 |   520 |  643 | 00:00:01    |
-----------------------------------------------------------------------------------

Notes
-----
- dop = 1
- px_in_memory_imc = no
- px_in_memory = no

- With Auto Indexes
-----------------------------
Plan Hash Value : 937174207

--------------------------------------------------------------------------------------------------------------
| Id  | Operation                                  | Name                 | Rows | Bytes | Cost | Time       |
--------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                           |                      |   19 |   494 |   22 | 00:00:01   |
|   1 | TABLE ACCESS BY GLOBAL INDEX ROWID BATCHED | BIG_BOWIE1           |   19 |   494 |   22 | 00:00:01   |
| * 2 | INDEX RANGE SCAN                           | SYS_AI_2zt7rg40mxa4n |   19 |       |    3 | 00:00:01   |
--------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
------------------------------------------
* 2 - access("TOTAL_SALES"=42)

Notes
-----
- Dynamic sampling used for this statement ( level = 11 )

 

We notice a couple of interesting points.

Firstly, yes Automatic Indexing has created an index based on the TOTAL_SALES column (SYS_AI_2zt7rg40mxa4n) as it improves performance by a reported 44119.6x.

Note also that the Automatic Index is a Non-Partitioned (Global) Index. From a performance perspective, this is the most efficient index to create to improve the performance of this query as the CBO only has the one index structure to navigate (vs. a LOCAL index that would require having to navigate down all 8 index structures for each table partition.

If we look at the index details:

SQL> SELECT index_name, partitioned, auto, visibility, status FROM user_indexes
WHERE table_name = 'BIG_BOWIE1';

INDEX_NAME                     PAR AUT VISIBILIT STATUS
------------------------------ --- --- --------- --------
SYS_AI_2zt7rg40mxa4n           NO  YES VISIBLE   VALID

 

We notice that this is indeed a Non-Partitioned Index, that is both VISIBLE and VALID and so can be potentially used by any database session.

If we now re-run the query:

SQL> SELECT * FROM big_bowie1 WHERE total_sales = 42;

19 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 937174207

-----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                                 | Name                 | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop    |
-----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                          |                      |   20 |   520 |      23 (0)| 00:00:01 |       |          |
|  1 | TABLE ACCESS BY GLOBAL INDEX ROWID BATCHED| BIG_BOWIE1           |   20 |   520 |      23 (0)| 00:00:01 | ROWID | ROWID    |
|* 2 | INDEX RANGE SCAN                          | SYS_AI_2zt7rg40mxa4n |   20 |       |       3 (0)| 00:00:01 |       |          |
-----------------------------------------------------------------------------------------------------------------------------------

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

2 - access("TOTAL_SALES"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
         23 consistent gets
          0 physical reads
          0 redo size
       1166 bytes sent via SQL*Net to client
        369 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
         19 rows processed

 

We can see the query now uses the newly created Automatic Index and is indeed more efficient, performing now just 23 consistent gets (previously 44014 consistent gets).

 

However, this was NOT previous behaviour.

The documentation previously mentioned that only LOCAL indexes are used when indexing partitioned tables.

If we run the same demo on Oracle Database 19.3, we get the following report:

 

GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start              : 14-OCT-2020 13:12:07
Activity end                : 14-OCT-2020 14:24:07
Executions completed        : 1
Executions interrupted      : 0
Executions with fatal error : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates                             : 1
Indexes created (visible / invisible)        : 1 (1 / 0)
Space used (visible / invisible)             : 192.94 MB (192.94 MB / 0 B)
Indexes dropped                              : 0
SQL statements verified                      : 1
SQL statements improved (improvement factor) : 1 (1950.5x)
SQL plan baselines created                   : 0
Overall improvement factor                   : 1950.5x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

INDEX DETAILS
-------------------------------------------------------------------------------
The following indexes were created:
*: invisible
-------------------------------------------------------------------------------
---------------------------------------------------------------------------------
| Owner | Table      | Index                | Key         | Type   | Properties |
---------------------------------------------------------------------------------
| BOWIE | BIG_BOWIE1 | SYS_AI_8armv0hqq73fa | TOTAL_SALES | B-TREE | LOCAL      |
---------------------------------------------------------------------------------
-------------------------------------------------------------------------------

VERIFICATION DETAILS
-------------------------------------------------------------------------------
The performance of the following statements improved:
-------------------------------------------------------------------------------
Parsing Schema Name : BOWIE
SQL ID              : 2pp8ypramw30s
SQL Text            : SELECT * FROM big_bowie1 WHERE total_sales = 42
Improvement Factor  : 1950.5x

Execution Statistics:
-----------------------------
                     Original Plan                Auto Index Plan
                     ---------------------------- ----------------------------
Elapsed Time (s):    6996973                      27327
CPU Time (s):        6704215                      12819
Buffer Gets:         815306                       49
Optimizer Cost:      12793                        28
Disk Reads:          2                            40
Direct Writes:       0                            0
Rows Processed:      475                          25
Executions:          19                           1

PLANS SECTION
---------------------------------------------------------------------------------------------

- Original
-----------------------------
Plan Hash Value : 4294056405

-----------------------------------------------------------------------------
| Id | Operation          | Name       | Rows | Bytes | Cost  | Time        |
-----------------------------------------------------------------------------
| 0 | SELECT STATEMENT    |            |      |       | 12793 |             |
| 1 | PARTITION RANGE ALL |            |   20 |   520 | 12793 | 00:00:01    |
| 2 | TABLE ACCESS FULL   | BIG_BOWIE1 |   20 |   520 | 12793 | 00:00:01    |
-----------------------------------------------------------------------------

- With Auto Indexes
-----------------------------
Plan Hash Value : 3781269341

--------------------------------------------------------------------------------------------------------------
|  Id | Operation                                 | Name                 | Rows | Bytes | Cost | Time        |
--------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                          |                      |   25 |   650 |   28 | 00:00:01    |
|   1 | PARTITION RANGE ALL                       |                      |   25 |   650 |   28 | 00:00:01    |
|   2 | TABLE ACCESS BY LOCAL INDEX ROWID BATCHED | BIG_BOWIE1           |   25 |   650 |   28 | 00:00:01    |
| * 3 | INDEX RANGE SCAN                          | SYS_AI_8armv0hqq73fa |   25 |       |   17 | 00:00:01    |
--------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
------------------------------------------
* 3 - access("TOTAL_SALES"=42)

Notes
-----
- Dynamic sampling used for this statement ( level = 11 )

 

As we can see, in this scenario, the newly created Automatic Index has a “Property” of LOCAL.

If we look at its index details:

 

SQL> SELECT index_name, partitioned, auto, visibility, status FROM user_indexes
WHERE table_name = 'BIG_BOWIE1';

INDEX_NAME                     PAR AUT VISIBILIT STATUS
------------------------------ --- --- --------- --------
SYS_AI_8armv0hqq73fa           YES YES VISIBLE   N/A

SQL> SELECT index_name, partitioning_type, partition_count, locality FROM user_part_indexes
WHERE table_name = 'BIG_BOWIE1';

INDEX_NAME                     PARTITION PARTITION_COUNT LOCALI
------------------------------ --------- --------------- ------
SYS_AI_8armv0hqq73fa           RANGE                   8 LOCAL

 

We can see how a Local Index was previously created.

As such if we re-run an equivalent query:

SQL> SELECT * FROM big_bowie1 WHERE total_sales = 42;

25 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 3781269341

-----------------------------------------------------------------------------------------------------------------------------------
| Id | Operation                                | Name                 | Rows | Bytes | Cost (%CPU)| Time     | Pstart| Pstop     |
-----------------------------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                         |                      |   20 |   520 |      26 (0)| 00:00:01 |       |           |
|  1 | PARTITION RANGE ALL                      |                      |   20 |   520 |      26 (0)| 00:00:01 |     1 |         8 |
|  2 | TABLE ACCESS BY LOCAL INDEX ROWID BATCHED| BIG_BOWIE1           |   20 |   520 |      26 (0)| 00:00:01 |     1 |         8 |
|* 3 | INDEX RANGE SCAN                         | SYS_AI_8armv0hqq73fa |   20 |       |      17 (0)| 00:00:01 |     1 |         8 |
-----------------------------------------------------------------------------------------------------------------------------------

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

3 - access("TOTAL_SALES"=42)

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
         50 consistent gets
          0 physical reads
          0 redo size
       1555 bytes sent via SQL*Net to client
        409 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
         25 rows processed

 

Although the query is returning 6 more rows (as with the random number generation, has a slightly different data set), it’s more expensive proportionally now having to perform 50 consistent gets as it now has to read 8 index structures rather than just the one.

So (IMHO), Automatic Indexing has improved here, creating a more efficient index structure than previously. So always bear in mind that Automatic Indexing is an evolving beast, improving and adapting as time moves on.

However, note the compromise here is that by having an effectively Global index structure, there may be some additional issues depending on any subsequent structural changes to the table.

More on Automatic Indexing and Partitioning in my next post…

Oracle 19c Automatic Indexing: Indexing With Stale Statistics Part III (Do Anything You Say) October 8, 2020

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Full Table Scans, Index Access Path, Index statistics, Oracle, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Statistics, Performance Tuning, Stale Statistics.
2 comments

In Part I of this series, we saw how Automatic Indexing will not create a viable Automatic Index if there are stale or missing statistics on the underlining segments. In Part II we saw how these SQL statements effectively become blacklisted and when segment statistics are subsequently collected, Automatic Indexing will still not create viable Automatic Indexes when the SQL statements are re-run.

So how do we get Automatic Indexing to now kick in and create necessary indexes on these problematic SQLs?

As I’ve discussed previously in relation to blacklisted SQLs, we need to run a NEW SQL statement that hasn’t been blacklist that will result in a necessary index to be created. An easy way to do this is just to include a new comment within the previous SQL to give the SQL a new signature.

If we now run the following “new” SQL statement (identical to the problematic SQL but with a comment embedded):

SQL> select /* new */ * from bowie_stale where code=42;

        ID       CODE NAME
---------- ---------- ------------------------------------------
   1000041         42 David Bowie
   6000041         42 David Bowie
        41         42 David Bowie
   3000041         42 David Bowie
   7000041         42 David Bowie
   8000041         42 David Bowie
   4000041         42 David Bowie
   9000041         42 David Bowie
   5000041         42 David Bowie
   2000041         42 David Bowie

 

If we now wait to see what the next Automatic Indexing task makes of things:

 

SQL> select dbms_auto_index.report_last_activity('text', 'ALL', 'ALL' ) report from dual;

REPORT
--------------------------------------------------------------------------------
GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start              : 07-JUL-2020 06:34:49
Activity end                : 07-JUL-2020 06:35:54
Executions completed        : 1
Executions interrupted      : 0
Executions with fatal error : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates                             : 0
Indexes created (visible / invisible)        : 1 (1 / 0)
Space used (visible / invisible)             : 142.61 MB (142.61 MB / 0 B)
Indexes dropped                              : 0
SQL statements verified                      : 1
SQL statements improved (improvement factor) : 1 (19787.7x)
SQL plan baselines created                   : 0
Overall improvement factor                   : 19787.7x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

INDEX DETAILS
-------------------------------------------------------------------------------
1. The following indexes were created:
*: invisible
-------------------------------------------------------------------------------
---------------------------------------------------------------------------
| Owner | Table       | Index                | Key  | Type   | Properties |
---------------------------------------------------------------------------
| BOWIE | BOWIE_STALE | SYS_AI_300kk2unp8tr0 | CODE | B-TREE | NONE       |
---------------------------------------------------------------------------
-------------------------------------------------------------------------------

 

We see that the index on the CODE column (SYS_AI_300kk2unp8tr0) has now been created.

Further down the report:

 

VERIFICATION DETAILS
-------------------------------------------------------------------------------
The performance of the following statements improved:
-------------------------------------------------------------------------------
Parsing Schema Name : BOWIE
SQL ID              : du6psd0xmzpg5
SQL Text            : select /* new */ * from bowie_stale where code=42
Improvement Factor  : 19787.7x

Execution Statistics:
-----------------------------
                  Original Plan Auto           Index Plan
                  ---------------------------- ----------------------------
Elapsed Time (s): 137261                       2620
CPU Time (s):     84621                        1769
Buffer Gets:      277028                       13
Optimizer Cost:   544                          13
Disk Reads:       275947                       2
Direct Writes:    0                            0
Rows Processed:   70                           10
Executions:       7                            1

 

A new index was indeed created because of this new SQL statement, with a performance improvement of 19787.7x.

Further down the report to the Plans Section:

 

PLANS SECTION
---------------------------------------------------------------------------------------------

- Original
-----------------------------
Plan Hash Value : 65903426

-----------------------------------------------------------------------------------
| Id | Operation                | Name        | Rows | Bytes | Cost | Time        |
-----------------------------------------------------------------------------------
| 0 | SELECT STATEMENT          |             |      |       |  544 |             |
| 1 | TABLE ACCESS STORAGE FULL | BOWIE_STALE |   10 |   230 |  544 | 00:00:01    |
-----------------------------------------------------------------------------------

Notes
-----
- dop = 1
- px_in_memory_imc = no
- px_in_memory = no

- With Auto Indexes
-----------------------------
Plan Hash Value : 2558864466

-------------------------------------------------------------------------------------------------------
| Id  | Operation                           | Name                 | Rows | Bytes | Cost | Time       |
-------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                    |                      |   10 |   230 |   13 | 00:00:01   |
|   1 | TABLE ACCESS BY INDEX ROWID BATCHED | BOWIE_STALE          |   10 |   230 |   13 | 00:00:01   |
| * 2 | INDEX RANGE SCAN                    | SYS_AI_300kk2unp8tr0 |   10 |       |    3 | 00:00:01   |
-------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
------------------------------------------
* 2 - access("CODE"=42)

Notes
-----
- Dynamic sampling used for this statement ( level = 11 )

 

We can see that the new plan using the new Automatic Index with a much lower CBO cost.

If we now look at the status of this index:

SQL> select index_name, auto, constraint_index, visibility, compression, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='BOWIE_STALE';

INDEX_NAME                     AUT CON VISIBILIT COMPRESSION   STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
------------------------------ --- --- --------- ------------- -------- ---------- ----------- -----------------
BOWIE_STALE_PK                 NO  YES VISIBLE   DISABLED      VALID      10000000       20164             59110
SYS_AI_300kk2unp8tr0           YES NO  VISIBLE   ADVANCED LOW  VALID      10000000       16891          10000000

 

We see that the index is now both VISIBLE and VALID (previously, it was INVISIBLE and UNUSABLE).

As such, the Automatic Index can now potentially be used by any SQL, including the previous problematic query.

So with a viable index now in place, if we re-run the initial problematic query:

SQL> select * from bowie_stale where code=42;

10 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 2558864466

------------------------------------------------------------------------------------------------------------
| Id | Operation                          | Name                 | Rows | Bytes | Cost (%CPU)| Time        |
------------------------------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT                   |                      |   10 |   230 |      14 (0)| 00:00:01    |
|  1 | TABLE ACCESS BY INDEX ROWID BATCHED| BOWIE_STALE          |   10 |   230 |      14 (0)| 00:00:01    |
|* 2 | INDEX RANGE SCAN                   | SYS_AI_300kk2unp8tr0 |   10 |       |       3 (0)| 00:00:01    |
------------------------------------------------------------------------------------------------------------

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

2 - access("CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

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

 

We see that finally, the SQL uses the new Automatic Index and is indeed much more efficient as a result, with just 14 consistent gets required (when previously it was 39430 consistent gets).

So if ever you come across the scenario where an SQL does not have an Automatic Index created when clearly it should, it could be that it has been blacklisted and needs a different SQL to actually generate the necessary index.

To avoid some of these issues, make sure you do not have stale or missing statistics when reliant on Automatic Indexing. The new High Frequency Statistics Collection capability to designed to specifically avoid such a scenario.

Oracle 19c Automatic Indexing: Indexing With Stale Statistics Part II (Survive) October 7, 2020

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Full Table Scans, Index Internals, Index statistics, Oracle, Oracle General, Oracle Indexes, Oracle Statistics, Oracle19c, Performance Tuning, Stale Statistics.
1 comment so far

 

 

In my previous post, I discussed how having stale statistics, usually a bad idea, is especially problematic with regard Automatic Indexes as it usually results in viable automatic indexes only being created in an UNUSABLE/INVISIBLE state.

If we were to now to collect the missing statistics:

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

PL/SQL procedure successfully completed.

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

TABLE_NAME             NUM_ROWS     BLOCKS LAST_ANAL
-------------------- ---------- ---------- ---------
BOWIE_STALE            10000000      39677 06-JUL-20

SQL> select column_name, num_distinct, density, histogram, last_analyzed from user_tab_cols
where table_name='BOWIE_STALE';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM       LAST_ANAL
-------------------- ------------ ---------- --------------- ---------
ID                       10000000          0 HYBRID          06-JUL-20
CODE                       971092    .000001 HYBRID          06-JUL-20
NAME                            1 4.9416E-08 FREQUENCY       06-JUL-20

 

If we now repeatedly re-run the problematic query many times:

 

SQL> select * from bowie_stale where code=42;

10 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 65903426

-----------------------------------------------------------------------------------------
| Id | Operation                | Name        | Rows | Bytes | Cost (%CPU)|  Time       |
-----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT         |             |   10 |   230 |    544 (14)|  00:00:01   |
|* 1 | TABLE ACCESS STORAGE FULL| BOWIE_STALE |   10 |   230 |    544 (14)|  00:00:01   |
-----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42)
    filter("CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      39430 consistent gets
      39421 physical reads
          0 redo size
        610 bytes sent via SQL*Net to client
        361 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
         10 rows processed

 

 

The CBO is forced to use the FTS as the current Automatic Index is in an UNUSABLE/INVISIBLE state.

If we wait for the next Automatic Indexing reporting period:

 

SQL> select dbms_auto_index.report_last_activity('text', 'ALL', 'ALL' ) report from dual;

REPORT
--------------------------------------------------------------------------------
GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start              : 06-JUL-2020 05:12:42
Activity end                : 06-JUL-2020 05:13:34
Executions completed        : 1
Executions interrupted      : 0
Executions with fatal error : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates           : 0
Indexes created            : 0
Space used                 : 0 B
Indexes dropped            : 0
SQL statements verified    : 0
SQL statements improved    : 0
SQL plan baselines created : 0
Overall improvement factor : 0x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes   : 0
Space used       : 0 B
Unusable indexes : 0
-------------------------------------------------------------------------------

 

We notice that the Automatic Indexing process has nothing to report. Even though the problematic query is repeatedly executed, the SQL is now effectively on a blacklist and is not re-considered by the Automatic Indexing process.

If we look at the index details on the table:

 

SQL> select index_name, auto, constraint_index, visibility, compression, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='BOWIE_STALE';

INDEX_NAME             AUT CON VISIBILIT COMPRESSION   STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
---------------------- --- --- --------- ------------- -------- ---------- ----------- -----------------
BOWIE_STALE_PK         NO  YES VISIBLE   DISABLED      VALID      10000000       20164             59110
SYS_AI_300kk2unp8tr0   YES NO  INVISIBLE ADVANCED LOW  UNUSABLE   10000000       23058           4147514 

 

So the Automatic Index (SYS_AI_300kk2unp8tr0) is still UNUSABLE and INVISIBLE and can not be used by the CBO.

NOTE: In earlier patches of Oracle Database 19c (I’m using version 19.5.0.0.0 in this demo), I identified some scenarios after stale statistics when indexes were created in but in a VALID/INVISIBLE state, such that they could still not be used by the CBO in general database sessions.

If we simply re-run the same queries again from the time when the dependant object statistics were stale, any SQL is just ignored by the Automatic Indexing process.

As such, if we now subsequently re-run the problematic query again:

SQL> select * from bowie_stale where code=42;

10 rows selected.

Execution Plan
----------------------------------------------------------
Plan hash value: 65903426

-----------------------------------------------------------------------------------------
| Id | Operation                | Name        | Rows | Bytes | Cost (%CPU)| Time        |
-----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT         |             |   10 |   230 |    544 (14)| 00:00:01    |
|* 1 | TABLE ACCESS STORAGE FULL| BOWIE_STALE |   10 |   230 |    544 (14)| 00:00:01    |
-----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42)
    filter("CODE"=42)

Note
-----
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
      39430 consistent gets
      39421 physical reads
          0 redo size
        610 bytes sent via SQL*Net to client
        361 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
         10 rows processed

 

Again, the CBO has no choice here with no viable VALID/VISIBLE index present but to perform a FTS, even though its getting the cardinality estimates spot on since statistics gathering.

 

In Part III I’ll discuss how to get this query to finally use the Automatic Index and improve its performance, although if you’re a regular reader of the blog you should already know the solution…

Oracle 19c Automatic Indexing: Indexing With Stale Statistics Part I (Dead Against It) October 6, 2020

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, CBO, Exadata, Exadata X8, Full Table Scans, High Frequency Statistics Collection, Index Access Path, Index statistics, Oracle, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Performance Tuning, Stale Statistics, Unusable Indexes.
5 comments

A “golden rule” when working with Automatic Indexing is that things don’t work properly if there are stale statistics on the dependant objects. Stale statistics can of course be problematic but they can be particularly troublesome when dealing with Automatic Indexing.

In the Oracle Autonomous Database environments, this issue is addressed somewhat by the new High Frequency Statistics Collection capability, which helps to automatically collect stale statistics on a regular basis. However, in on-prem Exadata environments where this can more easily be turned off or collected less frequently, it’s a potential issue worth consideration.

I’ll start with a simple little table, with a CODE column that has lots of distinct values:

SQL> create table bowie_stale (id number constraint bowie_stale_pk primary key, code number, name varchar2(42));

Table created.

SQL> insert into bowie_stale select rownum, mod(rownum, 1000000)+1, 'David Bowie' from dual connect by level <= 10000000;

10000000 rows created.

SQL> commit;

Commit complete.

Importantly, I don’t collect statistics on this newly populated table…

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

TABLE_NAME        NUM_ROWS     BLOCKS LAST_ANAL
--------------- ---------- ---------- ---------
BOWIE_STALE

SQL> select column_name, num_distinct, density, histogram, last_analyzed from user_tab_cols
where table_name='BOWIE_STALE';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM       LAST_ANAL
-------------------- ------------ ---------- --------------- ---------
ID                                           NONE
CODE                                         NONE
NAME                                         NONE

If we now run the following query a number of times while there are no statistics on the table:

SQL> select * from bowie_stale where code=42;

10 rows selected.

Execution Plan

-----------------------------------------------------------------------------------------
| Id | Operation                | Name        | Rows | Bytes | Cost (%CPU)| Time        |
-----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT         |             |  437 | 21413 |    553 (16)| 00:00:01    |
|* 1 | TABLE ACCESS STORAGE FULL| BOWIE_STALE |  437 | 21413 |    553 (16)| 00:00:01    |
-----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42)
    filter("CODE"=42)

Note
-----
- dynamic statistics used: dynamic sampling (level=2)
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          6  recursive calls
          0  db block gets
      39026  consistent gets
          0  physical reads
          0  redo size
        867  bytes sent via SQL*Net to client
        588  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
         10  rows processed

 

The CBO has no choice but to use a FTS as I don’t yet have an index on the CODE column.

If I now wait for the next Automatic Indexing task to kick in AND if there are still NO statistics on the table:

 

SQL> select dbms_auto_index.report_last_activity('text', 'ALL', 'ALL' ) report from dual;

REPORT

--------------------------------------------------------------------------------
GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start               : 05-JUL-2020 06:36:31
Activity end                 : 05-JUL-2020 06:37:07
Executions completed         : 1
Executions interrupted       : 0
Executions with fatal error  : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates            : 1
Indexes created             : 0
Space used                  : 0 B
Indexes dropped             : 0
SQL statements verified     : 0
SQL statements improved     : 0
SQL plan baselines created  : 0
Overall improvement factor  : 0x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes    : 0
Space used        : 0 B
Unusable indexes  : 0

 

You can see that there was the one index candidate BUT no Automatic Index appears to have been created.

Assuming there are still no statistics:

 

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

TABLE_NAME                       NUM_ROWS    BLOCKS  LAST_ANAL
------------------------------ ---------- ---------- ---------
BOWIE_STALE

SQL> select column_name, num_distinct, density, histogram, last_analyzed from user_tab_cols
where table_name='BOWIE_STALE2';

COLUMN_NAME          NUM_DISTINCT    DENSITY HISTOGRAM       LAST_ANAL
-------------------- ------------ ---------- --------------- ---------
ID                                           NONE
CODE                                         NONE
NAME                                         NONE

 

If we look now at what indexes exist on the table:

SQL> select index_name, auto, constraint_index, visibility, compression, status, num_rows, leaf_blocks, clustering_factor
from user_indexes where table_name='BOWIE_STALE';

INDEX_NAME                     AUT CON VISIBILIT COMPRESSION   STATUS     NUM_ROWS LEAF_BLOCKS CLUSTERING_FACTOR
------------------------------ --- --- --------- ------------- -------- ---------- ----------- -----------------
BOWIE_STALE_PK                 NO  YES VISIBLE   DISABLED      VALID
SYS_AI_300kk2unp8tr0           YES NO  INVISIBLE DISABLED      UNUSABLE          0           0                 0

SQL> select index_name, column_name, column_position from user_ind_columns
where table_name='BOWIE_STALE2' order by index_name, column_position;

INDEX_NAME                     COLUMN_NAME          COLUMN_POSITION
------------------------------ -------------------- ---------------
BOWIE_STALE_PK                 ID                                 1
SYS_AI_300kk2unp8tr0           CODE                               1

 

We notice there is now an Automatic Index BUT it remains in an UNUSABLE/INVISIBLE state. This means the index can’t be used by the CBO.

So if we now re-run the SQL query again:

 

SQL> select * from bowie_stale where code=42;

10 rows selected.

Execution Plan

-----------------------------------------------------------------------------------------
| Id | Operation                | Name        | Rows | Bytes | Cost (%CPU)| Time        |
-----------------------------------------------------------------------------------------
|  0 | SELECT STATEMENT         |             |  437 | 21413 |    553 (16)| 00:00:01    |
|* 1 | TABLE ACCESS STORAGE FULL| BOWIE_STALE |  437 | 21413 |    553 (16)| 00:00:01    |
-----------------------------------------------------------------------------------------

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

1 - storage("CODE"=42)
    filter("CODE"=42)

Note
-----
- dynamic statistics used: dynamic sampling (level=2)
- automatic DOP: Computed Degree of Parallelism is 1

Statistics
----------------------------------------------------------
          6  recursive calls
          0  db block gets
      39026  consistent gets
          0  physical reads
          0  redo size
        867  bytes sent via SQL*Net to client
        588  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
         10  rows processed

 

The CBO has no choice still but to use the FTS.

In Part II, we’ll see that once we get into this scenario, it can be a tad problematic to get ourselves out of it and get the Automatic Index created as we would like…

Oracle 19c Automatic Indexing: Data Skew Fixed By Baselines Part II (Sound And Vision) September 28, 2020

Posted by Richard Foote in 19c, 19c New Features, Automatic Indexing, Autonomous Data Warehouse, Autonomous Database, Autonomous Transaction Processing, Baselines, CBO, Data Skew, Exadata, Explain Plan For Index, Full Table Scans, Histograms, Index Access Path, Index statistics, Oracle, Oracle Blog, Oracle Cloud, Oracle Cost Based Optimizer, Oracle General, Oracle Indexes, Oracle Statistics, Oracle19c, Performance Tuning.
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In my previous post, I discussed how the Automatic Indexing task by using Dynamic Sampling Level=11 can correctly determine the correct query cardinality estimates and assume the CBO will likewise determine the correct cardinality estimate and NOT use an index if it would cause performance to regress.

However, if other database sessions DON’T use Dynamic Sampling at the same Level=11 and hence NOT determine correct cardinality estimates, newly created Automatic Indexes might get used by the CBO inappropriately and result inefficient execution plans.

Likewise, with incorrect CBO cardinality estimates, it might also be possible for newly created Automatic Indexes to NOT be used when they should be (as I’ve discussed previously).

These are potential issues if the Dynamic Sampling value differs between the Automatic Indexing task and other database sessions.

One potential way to make things more consistent and see how the Automatic Indexing behaves if it detects an execution plan where the CBO would use an Automatic Index that causes performance regression, is to disable Dynamic Sampling within the Automatic Indexing task.

This can be easily achieved by using the following hint which effectively disables Dynamic Sampling with the previous problematic query:

SQL> select /*+ dynamic_sampling(0) */ * from space_oddity where code in (190000, 170000, 150000, 130000, 110000, 90000, 70000, 50000, 30000, 10000);

1000011 rows selected.

Execution Plan
----------------------------------------------------------------------------------
| Id  | Operation         | Name         | Rows  | Bytes | Cost (%CPU)| Time     |
----------------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |              |  1005K|   135M| 11411   (1)| 00:00:01 |
|*  1 |  TABLE ACCESS FULL| SPACE_ODDITY |  1005K|   135M| 11411   (1)| 00:00:01 |
----------------------------------------------------------------------------------

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

1 - filter("CODE"=10000 OR "CODE"=30000 OR "CODE"=50000 OR
           "CODE"=70000 OR "CODE"=90000 OR "CODE"=110000 OR "CODE"=130000 OR
           "CODE"=150000 OR "CODE"=170000 OR "CODE"=190000)

Statistics
----------------------------------------------------------
          0  recursive calls
          0  db block gets
      41169  consistent gets
          0  physical reads
          0  redo size
   13535504  bytes sent via SQL*Net to client
       2705  bytes received via SQL*Net from client
        202  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
    1000011  rows processed

 

The query currently has good cardinality estimates (1005K vs 1000011 rows returned) only because we currently have histograms in place for the CODE column. As such, the query correctly uses a FTS.

However, if we now remove the histogram on the CODE column:

SQL> exec dbms_stats.gather_table_stats(null, 'SPACE_ODDITY', method_opt=> 'FOR ALL COLUMNS SIZE 1’);

PL/SQL procedure successfully completed.

 

There is no way for the CBO to now determine the correct cardinality estimate because of the skewed data and missing histograms.

So what does the Automatic Indexing tasks make of things now. If we look at the next activity report:

 

SQL> select dbms_auto_index.report_last_activity() report from dual;

REPORT
--------------------------------------------------------------------------------
GENERAL INFORMATION
-------------------------------------------------------------------------------
Activity start               : 18-AUG-2020 16:42:33
Activity end                 : 18-AUG-2020 16:43:06
Executions completed         : 1
Executions interrupted       : 0
Executions with fatal error  : 0
-------------------------------------------------------------------------------

SUMMARY (AUTO INDEXES)
-------------------------------------------------------------------------------
Index candidates                             : 0
Indexes created                              : 0
Space used                                   : 0 B
Indexes dropped                              : 0
SQL statements verified                      : 1
SQL statements improved                      : 0
SQL plan baselines created (SQL statements)  : 1 (1)
Overall improvement factor                   : 0x
-------------------------------------------------------------------------------

SUMMARY (MANUAL INDEXES)
-------------------------------------------------------------------------------
Unused indexes    : 0
Space used        : 0 B
Unusable indexes  : 0

We can see that it has verified this one new statement and has created 1 new SQL Plan Baseline as a result.

If we look at the Verification Details part of this report:

 

VERIFICATION DETAILS
-------------------------------------------------------------------------------
-------------------------------------------------------------------------------
The following SQL plan baselines were created:
-------------------------------------------------------------------------------
Parsing Schema Name     : BOWIE
SQL ID                  : 3yz8unzhhvnuz
SQL Text                : select /*+ dynamic_sampling(0) */ * from
space_oddity where code in (190000, 170000, 150000,
130000, 110000, 90000, 70000, 50000, 30000, 10000)
SQL Signature           : 3910785437403172730
SQL Handle              : SQL_3645e6a2952fcf7a
SQL Plan Baselines (1)  : SQL_PLAN_3cjg6naakzmvu198c05b9

We can see Automatic Indexing has created a new SQL Plan Baseline for our query with Dynamic Sampling set to 0 thanks to the hint.

Basically, the Automatic Indexing task has found a new query and determined the CBO would be inclined to use the index, because it now incorrectly assumes few rows are to be returned. It makes the poor cardinality estimate because there are currently no histograms in place AND because it can’t now use Dynamic Sampling to get a more accurate picture of things on the fly because it has been disabled with the dynamic_sampling(0) hint.

Using an Automatic Index over the current FTS plan would make the performance of the SQL regress.

Therefore, to protect the current FTS plan, Automatic Indexing has created a SQL Plan Baseline that effectively forces the CBO to use the current, more efficient FTS plan.

This can be confirmed by looking at the DBA_AUTO_INDEX_VERIFICATIONS view:

 

SQL> select execution_name, original_buffer_gets, auto_index_buffer_gets, status
from dba_auto_index_verifications where sql_id = '3yz8unzhhvnuz';

EXECUTION_NAME             ORIGINAL_BUFFER_GETS AUTO_INDEX_BUFFER_GETS STATUS
-------------------------- -------------------- ---------------------- ---------
SYS_AI_2020-08-18/16:42:33                41169                 410291 REGRESSED

 

If we now re-run the SQL again (noting we still don’t have histograms on the CODE column):

SQL> select /*+ dynamic_sampling(0) */ * from space_oddity where code in (190000, 170000, 150000, 130000, 110000, 90000, 70000, 50000, 30000, 10000);

1000011 rows selected.

Execution Plan
----------------------------------------------------------------------------------
| Id  | Operation         | Name         | Rows  | Bytes | Cost (%CPU)| Time     |
----------------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |              |    32 |  4512 | 11425   (2)| 00:00:01 |
|*  1 |  TABLE ACCESS FULL| SPACE_ODDITY |    32 |  4512 | 11425   (2)| 00:00:01 |
----------------------------------------------------------------------------------

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

1 - filter("CODE"=10000 OR "CODE"=30000 OR "CODE"=50000 OR
           "CODE"=70000 OR "CODE"=90000 OR "CODE"=110000 OR "CODE"=130000 OR
           "CODE"=150000 OR "CODE"=170000 OR "CODE"=190000)

Hint Report (identified by operation id / Query Block Name / Object Alias):

Total hints for statement: 1 (U - Unused (1))
---------------------------------------------------------------------------
1 -  SEL$1
U -  dynamic_sampling(0) / rejected by IGNORE_OPTIM_EMBEDDED_HINTS

Note
-----

- SQL plan baseline "SQL_PLAN_3cjg6naakzmvu198c05b9" used for this statement

Statistics
----------------------------------------------------------
          9  recursive calls
          4  db block gets
      41170  consistent gets
          0  physical reads
          0  redo size
   13535504  bytes sent via SQL*Net to client
       2705  bytes received via SQL*Net from client
        202  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
    1000011  rows processed

 

We can see the CBO is forced to use the SQL Plan Baseline “SQL_PLAN_3cjg6naakzmvu198c05b9” as created by the Automatic Indexing task to ensure the more efficient FTS is used and not the available Automatic Index.

So Automatic Indexing CAN create SQL PLan Baselines to protect SQL from performance regressions caused by inappropriate use of Automatic Indexes BUT it’s really hard and difficult for it to do this effectively if the Automatic Indexing tasks and other database sessions have differing Dynamic Sampling settings as it does by default…