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Oracle histograms for join predicates

Oracle Database Tips by Donald Burleson


 

Note:  See "Introduction to Histograms", " skewonly", "all about histograms" and "Oracle Cardinality and histograms" for more details on using Oracle histograms to improve execution plans.

 

I've noted in this OTN article how valuable "histograms" are for improving the efficiency of Oracle SQL execution plans.

 

It's well established that histograms are very useful for helping the optimizer choose between a full-scan and and index-scan, and we also see evidence that histograms help Oracle figure out inter-table join cardinality (the amount of "baggage" that Oracle must carry between table joins).  The presence of histograms helps the CBO determine the optimal table join order.

 

In a treatise titled "Histograms for join predicates" the author explains the problem and how to use histograms as a solution.  The thrust of the argument is that histograms will help detect "skew" in table join columns (STATE_NAME) when using synthetic keys (STATE#).  Aldridge shares his conclusions:

To sum up, here are the solutions I thought of:

  1. Partition or subpartition the fact table on STATE#. (preferred option)
  2. Create a summary table with partitioning or subpartitoning on STATE#. (uses most space and slows data load, but very flexible and powerful)
  3. Create a function-based index on fact to perform the lookup, and query that value instead. (a bit flaky, but it works without major system impact)
  4. Rebuild the fact table based on the STATE_NAME instead. (still limited in multi-level hierarchies)

 

If you like Oracle tuning, you may enjoy the new book "Oracle Tuning: The Definitive Reference", over 900 pages of BC's favorite tuning tips & scripts. 

You can buy it direct from the publisher for 30%-off and get instant access to the code depot of Oracle tuning scripts.


 

 

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