分库分表与自定义分表规则

总体介绍

  • Oinone的分库分表方案是基于Sharding-JDBC的整合方案,要先具备一些Sharding-JDBC的知识。[Sharding-JDBC]https://shardingsphere.apache.org/document/current/cn/overview/

  • 做分库分表前,大家要有一个明确注意的点就是分表字段(也叫均衡字段)的选择,它是非常重要的,与业务场景非常相关。在明确了分库分表字段以后,甚至在功能上都要做一些妥协。比如分库分表字段在查询管理中做为查询条件是必须带上的,不然效率只会更低。

  • 分表字段不允许更新,所以代码里更新策略设置类永不更新,并在设置了在页面修改的时候为readonly

配置分表策略

  1. 配置ShardingModel模型走分库分表的数据源pamirsSharding
  2. 为pamirsSharding配置数据源以及sharding规则
    a. pamirs.sharding.define用于oinone的数据库表创建用
    b. pamirs.sharding.rule用于分表规则配置
  3. 为pamirsSharding配置数据源以及sharding规则

    1)指定模型对应数据源

pamirs:
  framework:
    system:
      system-ds-key: base
      system-models:
        - base.WorkerNode
    data:
      default-ds-key: pamirs
      ds-map:
        base: base
      modelDsMap:
        "[demo.ShardingModel]": pamirsSharding  #配置模型对应的库

2)分库分表规则配置

pamirs: 
  sharding:
    define:
      data-sources:
        ds: pamirs
        pamirsSharding: pamirs #申明pamirsSharding库对应的pamirs数据源
      models:
        "[trigger.PamirsSchedule]":
          tables: 0..13
        "[demo.ShardingModel]":
          tables: 0..7
          table-separator: _
    rule:
      pamirsSharding: #配置pamirsSharding库的分库分表规则
        actual-ds:
          - pamirs  #申明pamirsSharding库对应的pamirs数据源
        sharding-rules:
          # Configure sharding rule ,以下配置跟sharding-jdbc配置一致
          - tables:
              demo_core_sharding_model: #demo_core_sharding_model表规则配置
                actualDataNodes: pamirs.demo_core_sharding_model_${0..7}
                tableStrategy:
                  standard:
                    shardingColumn: user_id
                    shardingAlgorithmName: table_inline
            shardingAlgorithms:
              table_inline:
                type: INLINE
                props:
                  algorithm-expression: demo_core_sharding_model_${(Long.valueOf(user_id) % 8)}
        props:
          sql.show: true

自定义规则

  • 默认规则即通用的分库分表策略,如按照数据量、哈希等方式进行分库分表;通常默认规则是可以的。
  • 但在一些复杂的业务场景下,使用默认规则可能无法满足需求,需要根据实际情况进行自定义。例如,某些业务可能有特定的数据分布模式或者查询特点,需要定制化的分库分表规则来优化数据访问性能或者满足业务需求。在这种情况下,使用自定义规则可以更好地适应业务的需求。

自定义分表规则示例

示例1:按月份分表(DATE_MONTH )

package pro.shushi.pamirs.demo.core.sharding;

import cn.hutool.core.date.DateUtil;
import com.google.common.collect.Range;
import org.apache.shardingsphere.sharding.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.RangeShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.StandardShardingAlgorithm;
import org.springframework.stereotype.Component;
import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j;

import java.util.*;

/**
 * @author wangxian
 * @version 1.0
 * @description
 */
@Component
@Slf4j
public class DateMonthShardingAlgorithm implements StandardShardingAlgorithm<Date> {

    private Properties props;

    @Override
    public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Date> preciseShardingValue) {
        Date date = preciseShardingValue.getValue();
        String suffix = "_" + (DateUtil.month(date) + 1);
        for (String tableName : availableTargetNames) {
            if (tableName.endsWith(suffix)) {
                return tableName;
            }
        }
        throw new IllegalArgumentException("未找到匹配的数据表");
    }

    @Override
    public Collection<String> doSharding(Collection<String> availableTargetNames, RangeShardingValue<Date> rangeShardingValue) {
        List<String> list = new ArrayList<>();
        log.info(rangeShardingValue.toString());
        Range<Date> valueRange = rangeShardingValue.getValueRange();
        Date lowerDate = valueRange.lowerEndpoint();
        Date upperDate = valueRange.upperEndpoint();
        Integer begin = DateUtil.month(lowerDate) + 1;
        Integer end = DateUtil.month(upperDate) + 1;
        TreeSet<String> suffixList = ShardingUtils.getSuffixListForRange(begin, end);
        for (String tableName : availableTargetNames) {
            if (containTableName(suffixList, tableName)) {
                list.add(tableName);
            }
        }
        return list;
    }

    private boolean containTableName(Set<String> suffixList, String tableName) {
        boolean flag = false;
        for (String s : suffixList) {
            if (tableName.endsWith(s)) {
                flag = true;
                break;
            }
        }
        return flag;
    }

    @Override
    public void init() {

    }

    @Override
    public String getType() {
        return "DATE_MONTH";
    }

    @Override
    public Properties getProps() {
        return this.props;
    }

    @Override
    public void setProps(Properties properties) {
        this.props = props;
    }
}

示例2:按特定字段截取去取模分表

package pro.shushi.pamirs.demo.core.sharding;

import org.apache.shardingsphere.sharding.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.RangeShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.StandardShardingAlgorithm;
import org.springframework.stereotype.Component;
import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j;

import java.util.Collection;
import java.util.Properties;

/**
 * @author wangxian
 * @version 1.0
 * @description
 */
@Component
@Slf4j
public class AppUserCodeShardingAlgorithm implements StandardShardingAlgorithm<String> {

    private Properties props;

    @Override
    public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<String> preciseShardingValue) {
        String appUserCode = preciseShardingValue.getValue();
        String suffix = "_" + Long.parseLong(appUserCode.substring(1)) % 21;
        for (String tableName : availableTargetNames) {
            if (tableName.endsWith(suffix)) {
                return tableName;
            }
        }
        throw new IllegalArgumentException("未找到匹配的数据表");
    }

    @Override
    public Collection<String> doSharding(final Collection<String> availableTargetNames, final RangeShardingValue<String> shardingValue) {
        return availableTargetNames;
    }

    @Override
    public String getType() {
        return "APP_USER_CODE_TYPE";
    }

    @Override
    public Properties getProps() {
        return this.props;
    }

    @Override
    public void setProps(Properties properties) {
        this.props = props;
    }

    @Override
    public void init() {

    }
}

使用自定义分表策略

1)指定模型对应数据源

pamirs:
  framework:
    system:
      system-ds-key: base
      system-models:
        - base.WorkerNode
    data:
      default-ds-key: pamirs_biz
      ds-map:
        base: base
        demo_core: pamirs
      modelDsMap:
        "[demo.record.MsgRecode]": pamirsSharding

2)分库分表规则配置

pamirs:
  sharding:
    define:
      data-sources:
        ds: pamirs
        pamirsSharding: pamirs
      models:
        "[trigger.PamirsSchedule]":
          tables: 0..13
        "[demo.record.MsgRecode]":
          tables: 0..20
          table-separator: _
    rule:
      pamirsSharding:
        actual-ds:
          - pamirs
        sharding-rules:
          - tables:
              demo_core_record_msg_recode:
                actualDataNodes: pamirs.demo_core_record_msg_recode_${0..20}
                tableStrategy:
                  standard:
                    shardingColumn: app_user_code
                    shardingAlgorithmName: app_user_code_table_algorithm
            shardingAlgorithms:
              app_user_code_table_algorithm:
                type: APP_USER_CODE_TYPE
                props:
                  strategy: STANDARD
                  algorithmClassName:
                    pro.shushi.pamirs.demo.core.sharding.AppUserCodeShardingAlgorithm

配置自定义规则SPI

分库分表规则SPI

在resources/META-INF/services 配置 org.apache.shardingsphere.sharding.spi.ShardingAlgorithm

pro.shushi.pamirs.demo.core.sharding.AppUserCodeShardingAlgorithm
pro.shushi.pamirs.demo.core.sharding.DateMonthShardingAlgorithm

Oinone社区 作者:望闲原创文章,如若转载,请注明出处:https://doc.oinone.top/backend/7155.html

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    问题描述 在本地启动导入设计数据的工程时,会出现dubbo调用超时导致设计数据无法完整导入的问题。 org.apache.dubbo.remoting.TimeoutException 产生原因 pom中的包依赖出现问题,导致没有使用正确的远程服务。 本地可能出现的异常报错堆栈信息如下: xception in thread "fixed-1-thread-10" PamirsException level: ERROR, code: 10100025, type: SYSTEM_ERROR, msg: 函数执行错误, extra:, extend: null at pro.shushi.pamirs.meta.common.exception.PamirsException$Builder.errThrow(PamirsException.java:190) at pro.shushi.pamirs.framework.faas.fun.manage.ManagementAspect.around(ManagementAspect.java:118) at sun.reflect.GeneratedMethodAccessor498.invoke(Unknown Source) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at org.springframework.aop.aspectj.AbstractAspectJAdvice.invokeAdviceMethodWithGivenArgs(AbstractAspectJAdvice.java:644) at org.springframework.aop.aspectj.AbstractAspectJAdvice.invokeAdviceMethod(AbstractAspectJAdvice.java:633) at org.springframework.aop.aspectj.AspectJAroundAdvice.invoke(AspectJAroundAdvice.java:70) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:175) at org.springframework.aop.framework.CglibAopProxy$CglibMethodInvocation.proceed(CglibAopProxy.java:749) at org.springframework.aop.interceptor.ExposeInvocationInterceptor.invoke(ExposeInvocationInterceptor.java:95) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:186) at org.springframework.aop.framework.CglibAopProxy$CglibMethodInvocation.proceed(CglibAopProxy.java:749) at org.springframework.aop.framework.CglibAopProxy$DynamicAdvisedInterceptor.intercept(CglibAopProxy.java:691) at pro.shushi.pamirs.framework.orm.DefaultWriteApi$$EnhancerBySpringCGLIB$$b4cea2b4.createOrUpdateBatchWithResult(<generated>) at pro.shushi.pamirs.meta.base.manager.data.OriginDataManager.createOrUpdateBatchWithResult(OriginDataManager.java:161) at pro.shushi.pamirs.meta.base.manager.data.OriginDataManager.createOrUpdateBatch(OriginDataManager.java:152) at pro.shushi.pamirs.ui.designer.service.installer.UiDesignerInstaller.lambda$install$0(UiDesignerInstaller.java:42) at pro.shushi.pamirs.core.common.function.AroundRunnable.run(AroundRunnable.java:26) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.dubbo.rpc.RpcException: Failed to invoke the method createOrUpdateBatchWithResult in the service org.apache.dubbo.rpc.service.GenericService. Tried 1 times of the providers [192.168.0.123:20880] (1/1) from the registry 127.0.0.1:2181 on the consumer 192.168.0.123 using the dubbo version 2.7.22. Last error is: Invoke remote method timeout. method: $invoke, provider: dubbo://192.168.0.123:20880/ui.designer.UiDesignerViewLayout.oio.defaultWriteApi?anyhost=true&application=pamirs-demo&application.version=1.0.0&check=false&deprecated=false&dubbo=2.0.2&dynamic=true&generic=true&group=pamirs&interface=ui.designer.UiDesignerViewLayout.oio.defaultWriteApi&metadata-type=remote&methods=*&payload=104857600&pid=69748&qos.enable=false&register.ip=192.168.0.123&release=2.7.15&remote.application=pamirs-test&retries=0&serialization=pamirs&service.name=ServiceBean:pamirs/ui.designer.UiDesignerViewLayout.oio.defaultWriteApi:1.0.0&side=consumer&sticky=false&timeout=5000&timestamp=1701136088893&version=1.0.0, cause: org.apache.dubbo.remoting.TimeoutException: Waiting server-side response timeout by scan timer. start time: 2023-11-28 10:23:05.835, end time: 2023-11-28 10:23:10.856, client elapsed: 695 ms, server elapsed: 4326 ms, timeout: 5000 ms, request: Request [id=0, version=2.0.2, twoway=true, event=false, broken=false, data=null], channel: /192.168.0.123:49449 -> /192.168.0.123:20880 at org.apache.dubbo.rpc.cluster.support.FailoverClusterInvoker.doInvoke(FailoverClusterInvoker.java:110) at org.apache.dubbo.rpc.cluster.support.AbstractClusterInvoker.invoke(AbstractClusterInvoker.java:265) at org.apache.dubbo.rpc.cluster.interceptor.ClusterInterceptor.intercept(ClusterInterceptor.java:47) at org.apache.dubbo.rpc.cluster.support.wrapper.AbstractCluster$InterceptorInvokerNode.invoke(AbstractCluster.java:92) at org.apache.dubbo.rpc.cluster.support.wrapper.MockClusterInvoker.invoke(MockClusterInvoker.java:98) at org.apache.dubbo.registry.client.migration.MigrationInvoker.invoke(MigrationInvoker.java:170) at org.apache.dubbo.rpc.proxy.InvokerInvocationHandler.invoke(InvokerInvocationHandler.java:96) at org.apache.dubbo.common.bytecode.proxy0.$invoke(proxy0.java) at pro.shushi.pamirs.framework.faas.distribution.computer.RemoteComputer.compute(RemoteComputer.java:124) at pro.shushi.pamirs.framework.faas.FunEngine.run(FunEngine.java:80) at pro.shushi.pamirs.distribution.faas.remote.spi.service.RemoteFunctionHelper.run(RemoteFunctionHelper.java:68) at pro.shushi.pamirs.framework.faas.fun.manage.ManagementAspect.around(ManagementAspect.java:109) … 20 more Caused…

    2023年11月28日
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