Benefits of Partition-Wise Joins

Partition-wise joins offer benefits described in the following topics:

Reduction of Communications Overhead

When executed in parallel, partition-wise joins reduce communications overhead. This is because, in the default case, parallel execution of a join operation by a set of parallel execution servers requires the redistribution of each table on the join column into disjoint subsets of rows. These disjoint subsets of rows are then joined pair-wise by a single parallel execution server.

The database can avoid redistributing the partitions because the two tables are partitioned on the join column. This functionality enables each parallel execution server to join a pair of matching partitions. This improved performance from using parallel execution is even more noticeable in Oracle Real Application Clusters configurations with internode parallel execution.

Partition-wise joins dramatically reduce interconnect traffic. Using this feature is key for large decision support systems (DSS) configurations that use Oracle Real Application Clusters. Currently, most Oracle Real Application Clusters platforms, such as massively parallel processing (MPP) and symmetric multiprocessing (SMP) clusters, provide limited interconnect bandwidths compared to their processing powers. Ideally, interconnect bandwidth should be comparable to disk bandwidth, but this is seldom the case. Consequently, most join operations in Oracle Real Application Clusters experience high interconnect latencies without parallel execution of partition-wise joins.

Reduction of Memory Requirements

Partition-wise joins require less memory than the equivalent join operation of the complete data set of the tables being joined. For serial joins, the join is performed at the same time on a pair of matching partitions. If data is evenly distributed across partitions, then the memory requirement is divided by the number of partitions and there is no skew to the data distribution among the parallel servers.

For parallel joins, memory requirements depend on the number of partition pairs that are joined in parallel. For example, if the degree of parallelism is 20 and the number of partitions is 100, then 5 times less memory is required because only 20 joins of two partitions each are performed at the same time. The fact that partition-wise joins require less memory has a direct beneficial effect on performance. For example, the join probably does not need to write blocks to disk during the build phase of a hash join.