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Don Burleson Blog 







Oracle bloom filter hashing

Oracle Tips by Burleson Consulting
October 7,  2008

WIP - Not Yet completed

Oracle has recently made an important change to an internal algorithm for performing hash joins, replacing their old method with a "bloom filter" hash join.

For those who are new to computer science, a "hash" is the transformation of a symbolic key value into a "address", a fixed location in RAM or disk.  Just as your home address uniquely identified where you live, a memory address has all of the information required to locate a unique place on RAM or Disk.

Hashing algorithms are a very fast way to store Oracle information, and a hash can convent a symbolic key into a disk address in as little as 50 microseconds.  This makes Oracle 10g sorted hash clusters a very fast way to store information, but hashing is also used for other important Oracle operations such as joining rows within the SQL optimizer.  Hashing is used for:

  • Row identification (sorted hash clusters)
  • Joining tables (the hash join)

One of the problems with Oracle's older hashing algorithm was that it did not deal well with large sets.  For example, an Oracle hash join was great for joining a small table to a large table, but large table joins were more efficient with nested loop joins.  The new bloom filter hashing algorithm may change that.

In a bloom filter hash, the problem is large sets is overcome.

Rampant TechPress author Steve Callan has a great description of the Oracle hashing with bloom filters.  In the paper ?General Purpose Hash Function Algorithms,? we see a good definition of the bloom filer hash:

A Bloom filter allows for the state of existence of a very large set of possible type values to be represented with a much smaller piece of memory.

This is achieved through the use of multiple distinct hash functions and also by allowing the result of a query for the existence of a particular type to have a certain amount of error.

This error can be controlled by varying the size of the table used for the Bloom filter and also by varying the number of hash functions.

While the internal machinations of Oracle remain a well-guarded proprietary secret, this new bloom filter hash may have a profound impact on overall Oracle performance as larger sets can now bypass nested loop processing in favor of a hash join.




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