postgresql query optimization

PostgreSQL recursive query for tree structure query and postgresql Recursion A very interesting feature found during Postgresql's use is that recursive queries can be used for results that require a tree-like structure. For example, the data structure of common company departments is similar to the following SQL state

Five tips for Instagram to improve PostgreSQL performance, postgresql Performance Optimization As Instagram grows, Postgres continues to serve as a solid foundation for Instagram and stores a vast majority of user data. Less than a year ago, we also wrote on our blog that Instagram "stores a large amount of data" and adds 90 pieces of data per second. Now, this d

Tutorial on implementing recursive query in PostgreSQL, postgresql Recursion Introduction I am working on a program in nilint32 (Open Source !) It is used to design and initiate surveys. The following is an example of a survey: Internally, it indicates the drop: A Survey involves many questions (question ). A series of problems can be classified into (optional)

Java SQL statement optimization experience and PostgreSQL statement Optimization Java SQL statement optimization experience (1) select the most efficient table name sequence (only valid in the rule-based seo/'target = '_ blank'> Optimizer ):The ORACLE parser processes the table names in the FROM clause in the order FRO

PostgreSQL recursive query for Tree Structure Query A very interesting feature found during PostgreSQL's use is that recursive queries can be used for results that require a tree-like structure. For example, the data structure of common company departments is similar to the following SQL statement when we design the table structure. If parent_id is NULL, it indic

node with two child nodes? Department_11 and? Department_12.-Department_11 node has another child node? department_111.?-Department_12 node has two child nodes? department_121 and? department_122.? The following is a recursive query generation tree structure query statement With RECURSIVE T (ID, NAME, parent_id, PATH, DEPTH) as (SELECTID, NAME, parent_id, Array[id] asPATH,1 asDEPTH fromDEPARTMENTWHEREpare

Options Default value Description Whether to optimize Reason Max_connections 100 Maximum number of client connections allowed Whether Because in the course of testing, 100 connections are sufficient Fsync On Forcing data to be updated synchronously to disk Is Because the IO pressure of the system is very large, in order to better test the influence of other configuration, change the paramet

records from a query result;Prepared Query );Use analyze to maintain accurate optimization statistics;Regular use of vacuum or pg_autovacuumDelete the index (then re-create the index) When making a large amount of data changes)2. Procedural experienceCheck whether the connection pool is used. If not, use it as soon as possible;Check the program again. After the

to reduce the overhead of transaction commit;CLUSTER is used to extract multiple records from an index;Use LIMIT when retrieving some records from a query result;Prepared Query );Use ANALYZE to maintain accurate optimization statistics;Regular use of VACUUM or pg_autovacuumDelete the index (then re-create the index) when making a large amount of data changes)2.

the data through the index and then the IO to the data block to get the data it is a process from physical storage to memory parsing into logical fields. That conforms to the requirements of the von Neumann architecture (external memory data is read into memory to be processed) Two table nodes (two table junction nodes) Multiple table nodes: Consider how the multi-table join sequence constitutes the least expensive "execution plan". Decide whether AB first or BC is connected first. Many datab