postgresql query optimization tips

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

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

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

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

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.

statements to reduce the cost of committing a transaction;Use cluster when extracting multiple records from an index;Use limit when extracting part of a record from a query result;Use pre-compiled queries (Prepared query);Use analyze to maintain accurate optimization statistics;Regular use of VACUUM or pg_autovacuumDelete indexes first when making large amounts

Mr. Huang took an SQL statement and asked me if I could optimize it. After reading it, the data volume is not large and the query is not complex. The record optimization process is as follows:DB: PostgreSQL 9.1OS: CentOS 6Count (d_personal_report_view )~ 9 K entries. The field type involved in the amount is numeric (9, 2 ).Original SQL: select distinct c.doctor_n

PostgreSQL CPU Full (100%) performance analysis and optimizationTransferred from: https://help.aliyun.com/knowledge_detail/43562.htmlIn database operations, a DBA often encounters a more urgent problem, that is, the sudden CPU full (CPU utilization reaches 100%), causing the business to stall. When the CPU is full, it is often necessary to start from the backend database, go back to the specific SQL, and finally locate the business layer. The followin

Tags: GRE method each query optimization semi compiler present represents voidThen read with me. PostgreSQL source Code (ix)--executor (the--scan node (top) of the query execution module), this chapter ends the remaining seven scan nodes. T_SubqueryScanState, T_FunctionScanState, T_ValuesScanState, T_CteSca

Tips for improving PostgreSQL Performance In a (poor) PostgreSQL query, only a small change is required (ANY (ARRAY [...]). to ANY (VALUES (...))) the query time can be reduced from 20 s to 0.2 s. From the simplest use of explain analyze, to the use of EXPLAIN s community, t

EFFECTIVE_CACHE_SIZE128MB optimizer assumes that a query can use the maximum memory, and shared_buffers regardless (1/2 of the recommended memory) is set slightly larger and the optimizer prefers to use index scans instead of sequential scansMAINTENANCE_WORK_MEM16MB the memory defined here is only used when a more resource-intensive command call is made, such as vacuum, to increase the value, and to speed up the execution of the command.WAL_BUFFER768

Tags: PostgreSQL mysqlMySQL has one and excellent syntax create TABLE ... like, you can quickly copy a table and create a copy of it. PostgreSQL also has a similar syntax and is more flexible, but pay attention to the details.First look at MySQL syntax: CREATE TABLE ... likeThe original table T1, with the following structure:+----------+------------------+------+-----+---------+----------------+|Field |Type

After using gin () to create a full-text index, the query is still very efficient when the result set is large, although there is a walk index.Update_time is not null and plainto_tsquery (' driver ') @@ keyword_participle ORDER by Avg_mon_search DESC LIMIT OFFSET 0;Background: The keyword table has 80 million rows of data, a gin (keyword_participle) index is established, and the BTREE index of the other sort fieldsAnalysis: When the

= rcvlbes.customer_id and rcvblls.balance>0 ORDER by Cust.name Into TEMP cust_with_balance Then query in the temporary table in the following way: SELECT * from Cust_with_balance WHERE postcode> "98000" The rows in the staging table are less than the rows in the primary table, and the physical order is the required order, reducing disk I/O, so the query effort can be significantly reduced. Note: Changes to

Database optimization tips and database optimization tipsDatabase TIPS ::1. When creating a table for record or data analysis: Use Id as the primary key, 1, 2, 3... indicates the number of messages. The user account id is used as a foreign key. A user corresponds to a unique accountId.One accountId can correspond to mu

cust_with_balanceThen query in the temporary table in the following way:SELECT * from Cust_with_balanceWHERE postcode> "98000"The rows in the staging table are less than the rows in the primary table, and the physical order is the required order, reducing disk I/O, so the query effort can be significantly reduced.Note: Changes to the primary table are not reflected when the staging table is created. When d