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What is partition wise join?
A full partition-wise join divides a large join into smaller joins between a pair of partitions from the two joined tables. To use this feature, you must equipartition both tables on their join keys, or use reference partitioning. You can use various partitioning methods to equipartition both tables.
What is partition pruning in MySQL?
The optimization known as partition pruning is based on a relatively simple concept which can be described as “Do not scan partitions where there can be no matching values”. By limiting the search, it is possible to expend much less time and effort in finding matching rows than by scanning all partitions in the table.
What is partition pruning?
Partition pruning is an essential performance feature for data warehouses. In partition pruning, the optimizer analyzes FROM and WHERE clauses in SQL statements to eliminate unneeded partitions when building the partition access list.
How to use a partition wise join in 3.2?
3.2.1 Full Partition-Wise Joins A full partition-wise join divides a large join into smaller joins between a pair of partitions from the two joined tables. To use full partition-wise joins, you must equipartition both tables on their join keys, or use reference partitioning. You can use various partitioning methods to equipartition both tables.
How does partition selection work in MySQL 5.6?
MySQL 5.6 supports explicit selection of partitions and subpartitions that, when executing a statement, should be checked for rows matching a given WHERE condition. Partition selection is similar to partition pruning, in that only specific partitions are checked for matches, but differs in two key respects:
When to use linear key partitioning in MySQL?
When a table is created using [LINEAR] HASH or [LINEAR] KEY partitioning and the names of the partitions are not specified, MySQL automatically names the partitions p0, p1 , p2., p N-1, where N is the number of partitions.
How does partition wise joins reduce response time?
Partition-wise joins reduce query response time by minimizing the amount of data exchanged among parallel execution servers when joins execute in parallel. This functionality significantly reduces response time and improves the use of both CPU and memory resources.