Planner statistics for indexed expressions
Summary: PostgreSQL is gathering statistics for indexed expressions, in order to make good choices of query plans.
Summary: PostgreSQL is gathering statistics for indexed expressions, in order to make good choices of query plans.
Summary: Planner statistics play a key role in improving the performance of the database. The query planner uses the statistical data to generate efficient run plans for queries. The purpose of this post is to explain the types of statistics in PostgreSQL and how to read and understand them.
Summary: The pg_show_plans
extension can show query plans of all the currently running SQL statements. Query plans can be shown in several formats, like JSON
or YAML
.
Summary: The pg_store_plans
module provides a means for tracking execution plan statistics of all SQL statements executed by a server.
Summary: in this article, let’s take a look at the detailed usage of pg_hint_plan
in various scenarios.
Summary: The pg_hint_plan
extension provides a hint table, through which you can change the execution plan of a query in a convenient way.
Summary: The pg_hint_plan
extension gives PostgreSQL ability to manually force some decisions in execution plans.
Summary: The pg_stat_kcache
extension gathers statistics about physical disk access and CPU consumption done by backends.
Summary: The pg_qualstats
extension gathers statistics about predicates, helping find what indices are missing.
Summary: A hypothetical, or virtual, index is an index that does not really exist, and therefore does not cost CPU, disk or any resource to create. They are useful to find out whether specific indexes can increase the performance for problematic queries, since you can discover if PostgreSQL will use these indexes or not without having to spend resources to create them.
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