1.RANGE 分区 创建实例: CREATE TABLE EMP ( id int not null primary key auto_increment, name char(25) not null default '' ) PARTITION BY RANGE (id) ( 将字段id定义为分区的字段 PARTITION P0 VALUES LESS THAN (100), 99以下的id都归到p0分区 PARTITION P1 VALUES LESS THAN (200), 100-199 PARTITION P2 VALUES LESS THAN (300) 200-299 ); PS::因为默认会将0也算进去,所以P0实际可以存储0-99或-数 PS::要么不包含主键,如果要包含主键,那么分区字段也必须是主键 PS::mysql5.5以上支持日期进行分区,有什么作用,^_^,你可以想到的 2.List分区 创建实例: CREATE TABLE LIST_EMP ( tid int not null PRIMARY key auto_increment, tname char(20) ) PARTITION BY LIST (tid) ( PARTITION P0 VALUES IN (1,3,5,7,9), PARTITION P1 VALUES IN (2,4,6,8,10) ); PS::通过上面的2种分区不难看出,RANGE分区是指定一个范围,而List分区是指定一个列表,在list中,只有指定的值才能存进去! PS::个人觉得List分区更多可以用在分类上面 测试: insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php'); insert into list_emp values (null,'Php');ERROR 1526 (HY000): Table has no partition for value 11 PS::第11条数据的时候报错,因为没有任何分区表包含了它

MySQLhandlesconcurrencyusingamixofrow-levelandtable-levellocking,primarilythroughInnoDB'srow-levellocking.ComparedtootherRDBMS,MySQL'sapproachisefficientformanyusecasesbutmayfacechallengeswithdeadlocksandlacksadvancedfeatureslikePostgreSQL'sSerializa

MySQLhandlestransactionseffectivelyusingtheInnoDBengine,supportingACIDpropertiessimilartoPostgreSQLandOracle.1)MySQLusesREPEATABLEREADasthedefaultisolationlevel,whichcanbeadjustedtoREADCOMMITTEDforhigh-trafficscenarios.2)Itoptimizesperformancewithabu

MySQL data types are divided into numerical, date and time, string, binary and spatial types. Selecting the correct type can optimize database performance and data storage.

Best practices include: 1) Understanding the data structure and MySQL processing methods, 2) Appropriate indexing, 3) Avoid SELECT*, 4) Using appropriate JOIN types, 5) Use subqueries with caution, 6) Analyzing queries with EXPLAIN, 7) Consider the impact of queries on server resources, 8) Maintain the database regularly. These practices can make MySQL queries not only fast, but also maintainability, scalability and resource efficiency.

MySQLisbetterforspeedandsimplicity,suitableforwebapplications;PostgreSQLexcelsincomplexdatascenarioswithrobustfeatures.MySQLisidealforquickprojectsandread-heavytasks,whilePostgreSQLispreferredforapplicationsrequiringstrictdataintegrityandadvancedSQLf

MySQL processes data replication through three modes: asynchronous, semi-synchronous and group replication. 1) Asynchronous replication performance is high but data may be lost. 2) Semi-synchronous replication improves data security but increases latency. 3) Group replication supports multi-master replication and failover, suitable for high availability requirements.

The EXPLAIN statement can be used to analyze and improve SQL query performance. 1. Execute the EXPLAIN statement to view the query plan. 2. Analyze the output results, pay attention to access type, index usage and JOIN order. 3. Create or adjust indexes based on the analysis results, optimize JOIN operations, and avoid full table scanning to improve query efficiency.

Using mysqldump for logical backup and MySQLEnterpriseBackup for hot backup are effective ways to back up MySQL databases. 1. Use mysqldump to back up the database: mysqldump-uroot-pmydatabase>mydatabase_backup.sql. 2. Use MySQLEnterpriseBackup for hot backup: mysqlbackup--user=root-password=password--backup-dir=/path/to/backupbackup. When recovering, use the corresponding life


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