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Index Rebuild vs. Coalesce vs. Shrink Space (Pigs – 3 Different Ones) February 8, 2008

Posted by Richard Foote in Oracle General, Oracle Indexes, Performance Tuning, Index Rebuild, Index Shrink, Index Coalesce.
31 comments

Previously, I discussed how an ALTER INDEX  … COALESCE is going to be less expensive in terms of using resources than an equivalent ALTER INDEX … SHRINK SPACE COMPACT (or ALTER INDEX … SHRINK SPACE) as the Coalesce doesn’t have to concern itself with ensuring all leaf blocks at the physical end of the index segment have all been moved to allow for the storage to be de-allocated from the index segment. If you just want to de-fragment an index and not necessarily reduce the overall space allocated to the segment, use Coalesce rather than the Shrink options as it’s cheaper.

But what about an ALTER INDEX … REBUILD, when, if ever, should it be used ?

Well the answer is as with most things Oracle, it depends.

Scenario One.

We have a table and the application deletes historical data but in a manner in which leaf blocks are not being entirely emptied. Basically, older stuff is removed, but it’s only removed in a random manner, from approximately the “earlier” 10% of the table. The index is sequenced which means only those leaf blocks in the “left-most” 10% of the index structure are impacted but all this deleted space is “deadwood” as new index entries are only being inserted into the “right-most” part of the index.

Note that basically 90% of the index is fine and very well utilised, it’s only 10% of the index that’s problematic. Of the problem 10% of leaf blocks, there’s plenty of free or deleted space, with many leaf blocks almost but not quite empty.

Coalesce (and indeed Shrink) will basically run through these 10% of fragmented leaf blocks and will merge the index row entries into as few leaf blocks as possible. With the 90% of blocks that are fine, Coalesce will basically read and then ignore them from any processing as there’s nothing that can be done for them.

Rebuild on the other hand will take an entirely different approach. It will (generally) read the entire existing index structure and will build a brand new, bright and shining index segment.  As part of this process, it will rebuild the entire index, it has no choice (assuming the index isn’t partitioned, but that’s another story) and will rebuild the 90% of the index that was actually perfect to begin with. Rebuilding 90% of something that doesn’t need rebuilding doesn’t sound particularly efficient and indeed it isn’t. As a result, the index rebuild will use substantially more resources and generate substantially more redo than an equivalent Coalesce (or Shrink Space).

Scenario Two.

We have an application that deletes data and it deletes data throughout the entire index structure. The deletes are significant with a substantial proportion of the overall rows having been deleted. Additionally, the table is not going to be repopulated with anything like the same volume of data or it won’t be repopulated for a substantial period of time. As such, all this deleted index space is “deadwood” as it’s not going to be used any time soon, if at all.

Now typically in this sort of scenario, it’s of course the table as much as the associated indexes that needs to be rebuilt. That’s a key point. However, maybe Full Table Scans are not an issue for this table so the wasted space in the table is not of urgent concern. Maybe the table in not in an ASSM tablespace or in a database that supports a Table Shrink command and maybe moving the table is not an immediate option due to availability concerns. For whatever reason (or lack of reason), the index needs to be de-fragmented.

Note it’s the entire index that’s problematic here and there could be portions of the index that have very few remaining index entries.

Now poor Coalesce (and indeed Shrink) has a bit of an issue here. They both merge index entries from two blocks into the one block where it can. However, if leaf blocks are really empty, these merged index entries may in turn be merged and moved again with index entries from yet another leaf block. And maybe yet again with another leaf block. And again and again … So a specific index entry may actually be moved into several different leaf blocks during the entire process. Each of these moves requires resources and generates redo and takes time.

Now the rebuild has an entirely different approach. As mentioned, it will basically (generally) read the entire exisiting index structure and will build a brand new one, but importantly as it does so will only have to locate a specific index entry once and once only. Also, as it’s the entire index structure that’s problematic, there’s no issue with fixing the entire index, as it’s all “broken”.

As a result of only having to deal with an existing index entry the once vs. the Coalesce which may relocate a specific index entry many times, the index rebuild is going to be substantially more efficient and potentially use significantly less resources and generate less redo.

This demo of the Differences between a Coalesce, Shrink Space and Rebuild shows when one out performs the other.

Basically, Coalesce is particularly efficient and uses less resources when the percentage of the overall index structure that’s problematic and fragmented is relatively small (less than approximately 20-25% of leaf blocks). Rebuild is particularly efficient when the percentage of the overall index structure that’s problematic and fragmented is relatively large and the average degree of fragmentation within an index leaf block is relatively high.  Note Pre 10g, an index needed to have at least 50% free space less pctfree in neighbouring leaf blocks for a Coalesce to be effective.

Now Rebuild (and Rebuild Online) potentially have locking implications that need to be considered although as we’ll see later, 11g has addressed some of these issues …

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