ShardingSphere生产实战
由于业务发展,数据库中某几张核心表未来半年单表数据能达到20亿左右。也因为外部的因素,只能用mysql来存储数据。所以考虑分库分表,最终选型为ShardingSphere。
方案选型可见文章:Mysql大数据量解决方案
考虑拆分后数据不会绝对均匀,按前期每表存400万来算,大约需512张表。8个库,那每库有64张表。团队采用的单分片键,按什么分片可自行约定,比如按地区,按业务标识等。
配置的分片策略为:
库:sharding_column % 8
表:sharding_column / 8 % 64
本地用了两个版本测试,线上用的是5.2.0版本。
5.0.0-alpha 和 5.2.0配置文件有差异。
配置文件中common项可以配置数据源的公共配置。5.2.0版本公共项只能在每个数据源下都配置一遍。
maven版本:
- <shardingsphere-starter.version>5.0.0-alpha</shardingsphere-starter.version>
-
- <dependency>
- <groupId>org.apache.shardingsphere</groupId>
- <artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId>
- <version>${shardingsphere-starter.version}</version>
- </dependency>
-
- <!-- druid -->
- <dependency>
- <groupId>com.alibaba</groupId>
- <artifactId>druid</artifactId>
- <version>1.1.22</version>
- </dependency>
application.yml:
- spring:
- shardingsphere:
- datasource:
- common:
- type: com.alibaba.druid.pool.DruidDataSource
- driver-class-name: com.mysql.cj.jdbc.Driver
- initial-size: 6
- maxActive: 20
- # 配置获取连接等待超时的时间
- maxWait: 60000
- # 配置间隔多久才进行一次检测,检测需要关闭的空闲连接,单位是毫秒
- timeBetweenEvictionRunsMillis: 60000
- # 配置一个连接在池中最小生存的时间,单位是毫秒
- minEvictableIdleTimeMillis: 300000
- #Oracle需要打开注释
- #validationQuery: SELECT 1 FROM DUAL
- testWhileIdle: true
- testOnBorrow: false
- testOnReturn: false
- # 打开PSCache,并且指定每个连接上PSCache的大小
- poolPreparedStatements: true
- maxPoolPreparedStatementPerConnectionSize: 20
- # 配置监控统计拦截的filters,去掉后监控界面sql无法统计,'wall'用于防火墙
- filters: stat,wall,slf4j
- # 通过connectProperties属性来打开mergeSql功能;慢SQL记录
- connectionProperties: druid.stat.mergeSql\=true;druid.stat.slowSqlMillis\=5000
- wall:
- multi-statement-allow: true
- names: ds0, ds_1, ds_2, ds_3, ds4, ds_5, ds_6, ds_7
- ds0:
- type: com.alibaba.druid.pool.DruidDataSource
- driverClassName: com.mysql.cj.jdbc.Driver
- url: jdbc:mysql://127.0.0.1/test?autoReconnect=true&useSSL=false&serverTimezone=Asia/Shanghai&characterEncoding=utf8
- username: root
- password: root
- ds1:
- ......
- 省略
- rules:
- sharding:
- tables:
- # 逻辑表名
- t_record:
- actualDataNodes: ds_$->{0..7}.t_record_$->{0..63}
- # 配置表分片策略
- tableStrategy:
- standard:
- shardingColumn: record_id
- shardingAlgorithmName: t-record-inline
- keyGenerateStrategy:
- column: id
- keyGeneratorName: snowflake
- defaultShardingColumn: record_id
- #绑定表
- bindingTables:
- - t_record
- defaultTableStrategy:
- none:
- defaultDatabaseStrategy:
- standard:
- shardingColumn: record_id
- shardingAlgorithmName: database-inline
- #分片算法配置
- sharding-algorithms:
- t-record-inline:
- type: INLINE
- props:
- algorithm-expression: t_record_$->{record_id.intdiv(8) % 64}
- database-inline:
- type: INLINE
- props:
- algorithm-expression: ds_$->{record_id % 8}
- default-key-generate-strategy:
- column: id
- key-generator-name: snowflake
- key-generators:
- snowflake:
- type: SNOWFLAKE
- props:
- worker-id: 123
- props:
- sql-show: true
-
配置Druid监控代码:
- @Configuration
- public class DruidConfig {
-
- @Bean
- public ServletRegistrationBean statViewServlet() {
- ServletRegistrationBean bean = new ServletRegistrationBean(new StatViewServlet(), "/druid/*");
- Map<String, String> initParams = new HashMap<>();
- initParams.put("loginUsername", "root");
- initParams.put("loginPassword", "root");
- //initParams.put("", true);
- //默认就是允许所有访问
- initParams.put("allow", "127.0.0.1");
- //黑名单IP
- initParams.put("deny", "192.168.1.1");
- bean.setInitParameters(initParams);
- return bean;
- }
-
- @Bean
- public FilterRegistrationBean webStatFilter() {
- WebStatFilter webStatFilter = new WebStatFilter();
-
- FilterRegistrationBean<WebStatFilter> filterRegistrationBean = new FilterRegistrationBean<>(webStatFilter);
- filterRegistrationBean.setUrlPatterns(Arrays.asList("/*"));
- filterRegistrationBean.addInitParameter("exclusions", "*.js,*.gif,*.jpg,*.png,*.css,*.ico,/druid/*");
-
- return filterRegistrationBean;
- }
- }
maven版本:
- <shardingsphere-starter.version>5.2.0</shardingsphere-starter.version>
- <dependency>
- <groupId>org.apache.shardingsphere</groupId>
- <artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId>
- <version>${shardingsphere-starter.version}</version>
- </dependency>
-
- <!-- druid -->
- <dependency>
- <groupId>com.alibaba</groupId>
- <artifactId>druid</artifactId>
- <version>1.1.18</version>
- </dependency>
application.yml:
- spring:
- shardingsphere:
- datasource:
- names: ds0, ds_1, ds_2, ds_3, ds4, ds_5, ds_6, ds_7
- ds_0:
- type: com.alibaba.druid.pool.DruidDataSource
- driverClassName: com.mysql.cj.jdbc.Driver
- url: jdbc:mysql://127.0.0.1/prod?autoReconnect=true&useSSL=false&serverTimezone=Asia/Shanghai&characterEncoding=utf8
- username: root
- password: root
- maxWait: 60000
- maxActive: 100
- validationQuery: SELECT 1
- testWhileIdle: true
- testOnBorrow: true
- timeBetweenEvictionRunsMillis: 300000
- minEvictableIdleTimeMillis: 3600000
- useUnfairLock: true
- ds_1:
- ......
- 省略
- rules:
- sharding:
- tables:
- # 逻辑表名
- t_record:
- actualDataNodes: ds_${0..7}.t_record_${0..63}
- # 配置表分片策略
- tableStrategy:
- standard:
- shardingColumn: record_id
- shardingAlgorithmName: t-record-inline
- keyGenerateStrategy:
- column: id
- keyGeneratorName: UUID
- defaultShardingColumn: record_id
- #绑定表
- bindingTables:
- - t_record
- defaultTableStrategy:
- none:
- defaultDatabaseStrategy:
- standard:
- shardingColumn: record_id
- shardingAlgorithmName: database-inline
- #分片算法配置
- sharding-algorithms:
- t-record-inline:
- type: INLINE
- props:
- algorithm-expression: t_record_${record_id.intdiv(8) % 64}
- database-inline:
- type: INLINE
- props:
- algorithm-expression: ds_${record_id % 8}
- default-key-generate-strategy:
- column: id
- key-generator-name: UUID
- key-generators:
- UUID:
- type: UUID
-
- props:
- sql-show: false
-
record_id/8有时会出现0.5的结果,则表名为t_record_0.5,会报错。
原因是Groovy不提供专用的整数除法运算符符号,需将表达式中 record_id/8 修改为 record_id.intdiv(8)
- spring:
- shardingsphere:
- datasource:
- names: ds0, ds_1, ds_2, ds_3, ds4, ds_5, ds_6, ds_7
- ds_0:
- filters: stat
可见github上issues:https://github.com/apache/shardingsphere/issues/21211
- 报错
- Caused by: org.yaml.snakeyaml.constructor.ConstructorException: Can't construct a java object for tag:yaml.org,2002:com.alibaba.druid.filter.stat.StatFilter; exception=Class is not accepted: com.alibaba.druid.filter.stat.StatFilter
- in 'string', line 76, column 5:
- - !!com.alibaba.druid.filter.stat. ...
排查后是因为 ShardingSphereAutoConfiguration 自动配置没有把审计的实现类注入。于是乎本地手动注入,具体实现为配置一个后置处理器BeanPostProcessor 即可。
具体案例可参考之前文章:策略模式、模板模式实战
- @Override
- public Object postProcessAfterInitialization(Object bean, String beanName) throws BeansException {
-
- //加载审计配置,ShardingRuleSpringBootConfiguration自动配置类未加载,所以手动加载
- if (bean instanceof AlgorithmProvidedShardingRuleConfiguration) {
- PropertySource source = ((ConfigurableEnvironment) environment).getPropertySources().get("applicationConfig: [classpath:/application.yml]");
- Object val = source.getProperty("spring.shardingsphere.rules.sharding.auditors.sharding_key_required_auditor.type");
- //简单实现
- if (val != null) {
- Map<String, ShardingAuditAlgorithm> auditors = new LinkedHashMap<>();
- auditors.put("sharding-key-required-auditor", new DMLShardingConditionsShardingAuditAlgorithm());
- ((AlgorithmProvidedShardingRuleConfiguration) bean).setAuditors(auditors);
- }
- }
- return bean;
- }
5.2.0版本中配置ShardingSphere主键生成策略不生效,与MybatisPlus主键生成策略冲突,猜测原因是5.2.0版本问题。
所以代码中主键生成用MybatispPlus内置的雪花算法实现。
除了分片表之外,ShardingSphere连接的数据源中,不能有重复的表。ShardingSphere启动时,会把对应的数据源和表的映射关系放在Map中,如果重复,则一个表会对应多个数据源。表关联会报错(必须指定相同的数据源)。
分片表和普通表可以join查询,但必须指定相同的数据源。
ShardingSphere支持跨库事务更新,如果是代码逻辑异常则会回滚。