Question

What performance advantages can be gained by partitioning a table?

Answer 1

Partitioning can provide tremendous benefit to a wide variety of applications by improving performance, manageability, and availability. It is not unusual for partitioning to greatly improve the performance of certain queries or maintenance operations. Moreover, partitioning can greatly simplify common administration tasks.

performance advantages can be gained by partitioning a table:

By limiting the amount of data to be examined or operated on, and by providing data distribution for parallel execution, partitioning provides multiple performance benefits. Partitioning features include:

Partition Pruning

Partition pruning is the simplest and also the most substantial means to improve performance using partitioning. Partition pruning can often improve query performance by several orders of magnitude. For example, suppose an application contains an Orders table containing a historical record of orders, and that this table has been partitioned by week. A query requesting orders for a single week would only access a single partition of the Orders table. If the Orders table had 2 years of historical data, then this query would access one partition instead of 104 partitions. This query could potentially execute 100 times faster simply because of partition pruning.

Partition pruning works with all of Oracle performance features. Oracle uses partition pruning with any indexing or join technique, or parallel access method.

Partition-Wise Joins

Partitioning can also improve the performance of multi-table joins by using a technique known as partition-wise joins. Partition-wise joins can be applied when two tables are being joined and both tables are partitioned on the join key, or when a reference partitioned table is joined with its parent table. Partition-wise joins break a large join into smaller joins that occur between each of the partitions, completing the overall join in less time. This offers significant performance benefits both for serial and parallel execution.