25 Tips for Optimizing Your PostgreSQL Queries（postgresql查询优化）

PostgreSQL is a powerful open source object-relational database system, highly customizable and extensible. Query performance is one of the top concerns when using the platform and users should always strive to improve the performance of their queries. The following are 25 tips to optimize your PostgreSQL queries and ensure optimal performance.

1.Check Your Configuration: Before you begin, ensure PostgreSQL is configured correctly. You can change configuration parameters to optimize performance in the postgresql.conf file.

2.Create Indexes: Indexes are a great way to speed up the execution of queries by allowing the database to quickly and easily find the necessary data. Create the appropriate indexes to support your queries and improve the query performance time.

3.Avoid Sequential Scans: Sequential scans are one of the worst offenders when it comes to query performance. Doing a full table scan of a large table can be time consuming. When possible, try to use indices or key lookups to avoid sequential scans.

4.Use Explain to Analyze Queries: The Explain utility is a great way to analyze query performance. It provides useful information about the plan being used to execute the query, and can help pinpoint areas of improvement.

5.Breakup Queries: If your query is made up of several parts (eg: a UNION or JOIN), it is advisable to break them up into multiple queries and execute them separately. This can greatly reduce the amount of work PostgreSQL needs to do and improve performance.

6.Optimize Joins: When joining large tables, it may be beneficial to use hash joins or merge joins. Hash joins will be more efficient when the join conditions are not selective and there are many records that need to be joined. Merge joins may be more efficient when the join conditions are selective and only select records need to be joined.

7.Use Explain Analyze: When running EXPLAIN, add the ANALYZE option to get execution stats. This will show how much time was spent in each step of the query plan and help identify areas of improvement.

8.Optimize WHERE Clauses: When using WHERE clauses, ensure the conditions are applied in the most efficient way. Try to use simpler expressions and use ofoperator operators that can take advantage of indexes, such as = instead of !=.

9.Use Limit: If you only need a certain number of records from a query, use the LIMIT clause to tell PostgreSQL to only retrieve that many records. This can drastically reduce the execution time and improve performance.

10.Optimize Data Types: When designing tables, be mindful of the data types you choose for the columns. Be sure to use the most appropriate data type for the data you are storing. Using the wrong data type can lead to slower execution times.

11.Use Covering Indexes: Create a covering index when possible. This can significantly improve query performance by not requiring a lookup in the main table for each row.

12.Avoid Wildcards: Try to avoid using wildcards when possible, as they can significantly slow down the query. Also be aware of the order of the columns in the index – make sure they are in the same order as in the query.

13.Optimize Sorts: Sorts in PostgreSQL can often be sped up by changing the ORDER BY to a GROUP BY, or vice versa. This will often be faster than doing an explicit sort.

14.Use Parallel Query Execution: If you have multiple cores in your system, you can take advantage of PostgreSQL’s parallel query execution. This can quickly speed up complex queries by utilizing multiple cores.

15.Use Temporary Tables: If you need to perform the same set of operations multiple times, it may help to store the results in a temporary table. This can speed up the performance in some cases.

16.Understand Multi-Version Concurrency Control (MVCC): PostgreSQL uses MVCC to ensure rows are automatically visible at the right time. Make sure you understand MVCC and how it works, as it can have a huge impact on performance.

17.Vacuum Regularly: Vacuuming is an important part of keeping PostgreSQL running efficiently. Vacuuming will reclaim space and help to ensure efficient read performance.

18.Avoid Data Type Overloading: Don’t use the same data type for multiple purposes. This can usually help performance in the long run.

19.Avoid Unnecessary Lengthy Transactions: Avoid keeping transactions open for too long. Long-running transactions will only make access to data slower for other users.

20.Use the proper Isolation Level: It is important to use the correct isolation level for your transaction. Using the wrong isolation level can lead to consistency problems and slower performance in PostgreSQL.

21.Reuse prepared queries: It is often more efficient to reuse prepared queries than to execute the same SQL statement multiple times.

22.Communicate Between Backend And Frontend: Make sure the backend and frontend are connected properly. Having a slow connection can drastically slow down processing.

23.Optimize Memory Use: Make sure PostgreSQL has enough memory to work efficiently, and optimize memory usage where possible.

24.Review Cost Estimations: Occassionally review the cost estimations that are being used by the query planner. If they appear to be off, it may be beneficial to update them.

25.Implement Performance Tuning: Performance tuning can be a tricky process, but it can have a big impact on performance. When done correctly, it can lead to significant increases in query performance.

Following these 25 tips can help to optimize your PostgreSQL queries and ensure optimal performance. Exploring all of these tips and understanding how they work can be beneficial to improving the performance of your queries.