sql query optimization tips

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SQL Server database query optimization 50 tips (Part 1)

50 tips for optimizing query: (see which one is suitable for you) 1. Place data, logs, and indexes on different I/O devices to increase the reading speed. In the past, tempdb can be placed on raid0, which is not supported by SQL2000. The larger the data size (size), the more important it is to increase I/O. 2. vertically and horizontally split the table to reduce the table size (sp_spaceuse) 3. upgrade hard

30 mysql Tens Big Data SQL query optimization tips

to explicitly delete all temporary tables at the end of the stored procedure, TRUNCATE table first, and then drop table, which avoids longer locking of the system tables. 25. Avoid using cursors as much as possible, because cursors are inefficient and should be considered for overwriting if the cursor is manipulating more than 10,000 rows of data. 26. Before using a cursor-based method or temporal table method, you should first look for a set-based solution to solve the problem, and the set-bas

30 SQL query optimization tips for mysql with tens of millions of big data, mysqlsql

30 SQL query optimization tips for mysql with tens of millions of big data, mysqlsql 1. To optimize the query, try to avoid full table scanning. First, consider creating an index on the columns involved in where and order. 2. try to avoid null value determination on the fiel

SQL Server query performance optimization-index creation principles (ii) SQL Server query performance optimization-index creation principles (I)

Yesterday's SQL Server query performance optimization-index creation principle (I) mainly introduced the principle. today are some of the main principles and checks the created indexes. Iii. indexing principles In general, building indexes depends on the data usage scenarios. In other words, which SQL statements are co

SQL optimization--Logical optimization--sub-query optimization (MySQL)

data types of the participating operations, such as the int type has ">, d)join/on clause position: The JOIN/ON clause can be split into two parts, one is the JOIN block is similar to the FROM clause, and the ON clause block is similar to the WHERE clause, both of which can appear subqueries. The subquery is handled in the same way as the FROM clause and the WHERE clause. e)GROUPBY clause position: The destination column must be associated with the GROUPBY 1. Subq

SQL optimization----million data query optimization

= 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

SQL Server SQL performance optimization--pivot row and column conversion reduction Scan Count Optimization query statement

First of all, let's look at one of the steps here that translates into banner, which requires pivot, step-by-step Then look at the overall query results for the two query methods after the main table join So take a look at the latter query method is also through the industry after the conversion to do the join execution plan, you can see only the Word table

SQL optimization----million data query optimization

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

SQL optimization--Query optimization technology classification

: ① query Reuse, ② query rewrite rules, ③ query algorithm optimization, ④ parallel query optimization, ⑤ distributed query optimization, ⑥ o

SQL statement and query optimization of MySQL database performance optimization

Optimization objectivesReduce IO timesIo is always the easiest place to bottleneck the database, which is determined by the responsibility of the database, most of the database operations over 90% of the time is occupied by IO operations, reducing IO times is the first priority in SQL optimization, of course, is the most obvious

Correct use of indexes (SQL optimization), limit paging optimization, execution plan, slow log query

MySQL configuration file, my.cnf (Windows My.ini), and add the following lines under [Mysqld]: slow_query_log=1 long_query_time=2 slow_query_log_file= /usr/slow.log log_queries_not_using_indexes=1 Restarting the MySQL service Location of MySQL configuration file The windows:windows configuration file is My.ini, usually under the MySQL installation directory or under C:\Windows. The Linux:linux configuration file is my.cnf, usually in/etc. Identify the QR code in the

Improved MySQL Tens big Data SQL query Optimization 30 experience (MySQL index optimization note)

cursors are inefficient and should be considered for overwriting if the cursor is manipulating more than 10,000 rows of data.26. Before using a cursor-based method or temporal table method, you should first look for a set-based solution to solve the problem, and the set-based approach is generally more efficient.27. As with temporary tables, cursors are not unusable. Using Fast_forward cursors on small datasets is often preferable to other progressive processing methods, especially if you must

SQL optimization----million data query optimization (reprint)

rcvblls.balance>0ORDER by Cust.nameInto TEMP 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 reflec

Optimization of SQL massive data query and non-use like processing solutions, data query like

Optimization of SQL massive data query and non-use like processing solutions, data query like 1. To optimize the query, try to avoid full table scanning. First, consider creating an index on the columns involved in where and order. 2. Try to avoid null value determination on

Optimization of SQL massive data query and non-use like processing solutions, data query like

Optimization of SQL massive data query and non-use like processing solutions, data query like 1. To optimize the query, try to avoid full table scanning. First, consider creating an index on the columns involved in where and order.2. Try to avoid null value determination on

MySQL Query optimization tips

like:SELECT [Column1],[column2],.... From [TABLE] ORDER by [sort] LIMIT [offset],[limit];This SQL statement optimization is relatively simple and can be indexed on the [Sort] field.(2). WHERE + ORDER by + limit combination index optimization, shaped like:SELECT [Column1],[column2],.... From [TABLE] WHERE [COLUMNX] = [VALUE] ORDER by [sort] LIMIT [offset],[limit]

Analysis function optimization of Oracle SQL optimization scalar quantum query

,'YYYYMMDD') Rangebetween thePreceding Currentrow)End asf70115_70011, Case whenA.c_date>To_char (sysdate-3,'YYYYMMDD') Then sum(VALUEF1) Over(Partition byA.code,a. Year Order byTo_date (A.c_date,'YYYYMMDD') Rangebetween thePreceding Currentrow)End asf70104_70011, Case whenA.c_date>To_char (sysdate-3,'YYYYMMDD') Then sum(VALUEF6) Over(Partition byA.code,a. Year Order byTo_date (A.c_date,'YYYYMMDD') Rangebetween thePreceding Currentrow)End asf70126_70011, Case whenA.c

SQL statement Optimization-query two tables different rows not in, not EXISTS, connection query left join

. Method Three: Using connection query Connection queries include: 1. Self-connect (join equals inner JOIN): Query result is data that exists on both sides 2. Left join to the left join: return all data on the right, return to the back, null not present 3. Right join: Return all data on the right, return on left, no null 4. Fully connected full join: Returns if one of the tables exists and the other does

Five practical tips for MySQL Query Optimization,

Five practical tips for MySQL Query Optimization, This article summarizes and analyzes the MySQL query optimization techniques. We will share this with you for your reference. The details are as follows: Anyone familiar with SQL s

[go] Improve MySQL Tens Big Data SQL query Optimization 30 experience (MySQL index optimization note)

tables. 25. Avoid using cursors as much as possible, because cursors are inefficient and should be considered for overwriting if the cursor is manipulating more than 10,000 rows of data. 26. Before using a cursor-based method or temporal table method, you should first look for a set-based solution to solve the problem, and the set-based approach is generally more efficient. 27. As with temporary tables, cursors are not unusable. Using Fast_forward cursors on small datasets is often preferabl

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