PostgreSQL is a mature and robust RDBMS since it has 30 years of history. Over the year, its query optimizer has been enhanced and usually produces good query plans.

However, can it always come up with good query plans? The optimization process has to use some assumptions to produce plans fast enough. Some of those assumptions are relatively easy to check (e.g. statistics are up-to-date), some harder (e.g. correct indexes are created), and some nearly impossible (e.g. making sure that the statistic samples are representative enough even for skewed data repartition). For now, given those various caveats, DBA sometimes can't always realize easily that they miss a chance to get a meaningful performance improvement.

To help DBA to get a truly good query plan, we'll present below some tools that can help to fix some of those problems by providing a missing index adviser, looking for extended statistics to create, and row estimation error correction information to get appropriate join orders with join methods automatically.

• pg_qualstats: provides a new index and extended statistics suggestions to gather many predicate statistics on the production workload.
• pg_plan_advsr: provides alternative good query plans automatically to analyze iterative query executions information to fix estimation rows error.

In this talk, we will explain how those tools work under the hood and see what can be done, how they can work together. Also, we will mention what other tools also exist for related problems. Therefore, it will be useful for DBA who are interested in improving query performance or want to check whether current settings of indexes and statistics are adequate.