HashJoin builds an in-memory hash table of the smaller of its two inputs, and then reads the larger input and probes the in-memory hash table to find matches, which are written to a work table. If the smaller input does not fit into memory, HashJoin partitions both inputs into smaller work tables. These smaller work tables are processed recursively until the smaller input fits into memory.
HashJoin has the best performance if the smaller input fits into memory, regardless of the size of the larger input. In general, the optimizer chooses hash join if one of the inputs is expected to be substantially smaller than the other.
If HashJoin executes in an environment where there is not enough cache memory to hold all the rows that have a particular value of the join attributes, then it is not able to complete. In this case, HashJoin discards the interim results and an indexed-based NestedLoopsJoin is used instead. All of the rows of the smaller table are read and used to probe the work table to find matches. This indexed-based strategy is significantly slower than other join methods, and the optimizer avoids generating access plans using a hash join if it detects that a low memory situation may occur during query execution.
The amount of memory that can be used by a HashJoin operator is dependent upon the multiprogramming level of the server, and the number of active connections. See Threading in SQL Anywhere, and Setting the database server's multiprogramming level.
When the nested loops strategy is needed due to low memory, a performance counter is incremented. You can read this monitor with the QueryLowMemoryStrategy database or connection property, or in the Query: Low Memory Strategies counter in the Windows Performance Monitor.
In low memory conditions, HashJoin is disabled on Windows Mobile.
The Windows Performance Monitor may not be available on Windows Mobile.
For more information, see QueryLowMemoryStrategy in Connection-level properties, and Setting the database server's multiprogramming level.
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