SQL Optimization: A very simple article to improve SQL performance!
In order to improve the query efficiency in SQL queries, we often take some measures to optimize the query statements. Some of the methods summarized below can be referred to if necessary. In the optimization experience of a certain operator, I once encountered a relatively interesting SQL, the details are as follows:
1 The execution of the initial SQL is as follows
SQL> SELECT 2 NVL(T.RELA_OFFER_SPEC_ID, SUBOS.SUB_OFFER_SPEC_ID) "offerSpecId" 3 FROM OFFER_SPEC_RELA T 4 LEFT JOIN OFFER_SPEC_GRP_RELA SUBOS 5 ON T.RELA_GRP_ID = SUBOS.OFFER_SPEC_GRP_ID 6 AND subos.start_dt <= SYSDATE 7 AND subos.end_dt >= SYSDATE 8 WHERE T.RELA_TYPE_CD = 2 9 AND t.start_dt <= SYSDATE 10 AND t.end_dt >= SYSDATE 11 AND (T.OFFER_SPEC_ID = 109910000618 12 OR EXISTS 13 (SELECT A.OFFER_SPEC_GRP_ID 14 FROM OFFER_SPEC_GRP_RELA A 15 WHERE A.SUB_OFFER_SPEC_ID = 109910000618 16 AND T.OFFER_SPEC_GRP_ID = A.OFFER_SPEC_GRP_ID 17 )) 18 AND rownum<500; no rows selected Execution Plan ---------------------------------------------------------- Plan hash value: 1350156609
Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(ROWNUM<500) 2 - filter("T"."OFFER_SPEC_ID"=109910000618 OR EXISTS (SELECT 0 FROM "SPEC"."OFFER_SPEC_GRP_RELA" "A" WHERE "A"."OFFER_SPEC_GRP_ID"=:B1 AND "A"."SUB_OFFER_SPEC_ID"=109910000618)) 3 - access("T"."RELA_GRP_ID"="SUBOS"."OFFER_SPEC_GRP_ID"(+)) 4 - filter("T"."RELA_TYPE_CD"=2 AND "T"."END_DT">=SYSDATE@! AND "T"."START_DT"<=SYSDATE@!) 5 - filter("SUBOS"."END_DT"(+)>=SYSDATE@! AND "SUBOS"."START_DT"(+)<=SYSDATE@!) 6 - access("A"."SUB_OFFER_SPEC_ID"=109910000618 AND "A"."OFFER_SPEC_GRP_ID"=:B1) Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 12444 consistent gets 0 physical reads 0 redo size 339 bytes sent via SQL*Net to client 509 bytes received via SQL*Net from client 1 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 0 rows processed PLAN GET DISK WRITE ROWS ROWS USER_IO(MS) ELA(MS) CPU(MS) CLUSTER(MS) PLSQL END_TI I HASH VALUE EXEC PRE EXEC PRE EXEC PER EXEC ROW_P PRE EXEC PRE FETCH PER EXEC PRE EXEC PRE EXEC PER EXEC PER EXEC
2 First analysis
There should be the following points worth noting at this time
1) The sql is executed every day Thousands of times, the average execution returns less than 10 rows of data, but the average logical read reaches 1.2W, which may cause performance problems.
2) Two full table scans appear in the execution plan path with IDs 4 and 5. Seeing this, we can think that there may be no suitable indexes, resulting in a full table scan and low execution efficiency.
3) FILTER appears in the execution plan path with ID 2, and 3, and 6 are its sub-paths. If FILTER has two or more sub-paths, its execution principle will be similar to a nested loop. , if the subpath with the smallest ID number returns a large number of rows, it may cause the subpath with the smaller ID number to be executed multiple times, resulting in low performance. This situation generally occurs when "OR EXISTS" exists and can be avoided according to the situation.
Related links:
PHP-FPM achieves performance optimization, php-fpm performance optimization
[SQL]MySQL performance Optimization_MySQL
MySQL Optimization Video Tutorial
The above is the detailed content of SQL Optimization: A very simple article to improve SQL performance!. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

InnoDB's full-text search capabilities are very powerful, which can significantly improve database query efficiency and ability to process large amounts of text data. 1) InnoDB implements full-text search through inverted indexing, supporting basic and advanced search queries. 2) Use MATCH and AGAINST keywords to search, support Boolean mode and phrase search. 3) Optimization methods include using word segmentation technology, periodic rebuilding of indexes and adjusting cache size to improve performance and accuracy.

The difference between clustered index and non-clustered index is: 1. Clustered index stores data rows in the index structure, which is suitable for querying by primary key and range. 2. The non-clustered index stores index key values and pointers to data rows, and is suitable for non-primary key column queries.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

MySQL and MariaDB can coexist, but need to be configured with caution. The key is to allocate different port numbers and data directories to each database, and adjust parameters such as memory allocation and cache size. Connection pooling, application configuration, and version differences also need to be considered and need to be carefully tested and planned to avoid pitfalls. Running two databases simultaneously can cause performance problems in situations where resources are limited.

In MySQL database, the relationship between the user and the database is defined by permissions and tables. The user has a username and password to access the database. Permissions are granted through the GRANT command, while the table is created by the CREATE TABLE command. To establish a relationship between a user and a database, you need to create a database, create a user, and then grant permissions.

MySQL supports four index types: B-Tree, Hash, Full-text, and Spatial. 1.B-Tree index is suitable for equal value search, range query and sorting. 2. Hash index is suitable for equal value searches, but does not support range query and sorting. 3. Full-text index is used for full-text search and is suitable for processing large amounts of text data. 4. Spatial index is used for geospatial data query and is suitable for GIS applications.
