In this post, we share five simple but still powerful tips for PostgreSQL query optimization. Here's what I have (DB version, table information, number of rows, EXPLAIN ANALYZE of the two queries I would like to optimize): PostgreSQL is one of the most popular open-source relational database systems. I've had similar ideas in the past and even hacked together something (very dirty), so it's great someone else is interested in this topic too. On Mon, Jun 10, 2019 at 11:53:02AM +0300, Konstantin Knizhnik wrote: >Hi, > >Inefficiency of Postgres on some complex queries in most cases is >caused by errors in selectivity estimations. Bibliography. We also focused on understanding what makes a query poor or bad in nature. At one point, we advised one of our customers that had a 10TB database to use a date-based multi-column index. Planning set operations Planning for set operations is somewhat primitive Generate plans for child queries, then add a node to concatenate the result sets together Some set operations require more work: UNION:sort and remove duplicates The product of more than 30 years of development work, PostgreSQL has proven to be a highly reliable and robust database that can handle a large number of complicated data workloads. create or replace function customers_in_zip(p_zip_code varchar(5)) returns setof customers as $$ select * from customers where zip_code = p_zip_code; $$ language sql; That usually refers to language sql functions which are completely replaced by the contained query when used inside another query, e.g. Up to PostgreSQL v11, the optimizer had this knowledge wired in. EverSQL will tune your SQL queries instantly and automatically. This algorithm, first introduced in the "System R" database, produces a near-optimal join order, but can take an enormous amount of time and memory space when the number of joins in the query grows large. So PostgreSQL assigns costs to multiple competing strategies and chooses the ones with lower costs. this function . Cost estimates are arbitrary values that are assigned to each step in query execution based on the expected resource load it may create. The current PostgreSQL optimizer implementation performs a near-exhaustive search over the space of alternative strategies. This page consists of tips, issues, benchmarks, and tools to performance optimize PostgreSQL using different techniques. I've been reading through similar questions here and Postgres tuning articles online, but unfortunately I haven't had any luck. However, the main use case for this kind of support function will be PostGIS, and support functions were introduced specifically to … In this section, we saw a few tips on how to optimize PostgreSQL queries, and how to treat joins. Mastering PostgreSQL 11, Hans-Jurgen Schonig, Packt Publishing, October 2018; PostgreSQL for Data Architects, Jayadevan Maymala, Packt Publishing, March 2015 In this post, we share five powerful tips for PostgreSQL query optimization. As per the PostgreSQL documentation, it is an arbitrary value for the planner’s estimate of the cost. At one point, we advised one of our customers that had a 10TB database to use a date-based multi-column index. The term "inlining" has a different meaning in Postgres. PostgreSQL Query Optimizer Internals – p. 20. As a result, their date range query sped up by 112x. Some of the most critical aspects of tuning PostgreSQL for performance are hardware updates, configuration, vacuuming, query performance, and indexing of queries. 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