springboot通过sharding-dbc按年、月分片-Toy模板网

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spring:
    autoconfigure:
        exclude: com.alibaba.druid.spring.boot.autoconfigure.DruidDataSourceAutoConfigure
    main:
        allow-bean-definition-overriding: true
    shardingsphere:
        #配置数据源
        datasource:
            names: ds-master
            ds-master:
                type: com.alibaba.druid.pool.DruidDataSource
                driver-class-name: com.mysql.cj.jdbc.Driver
                url: jdbc:mysql://147.1.5.229:3306/aihosp?useUnicode=true&characterEncoding=UTF-8&allowMultiQueries=true&serverTimezone=GMT%2B8&rewriteBatchedStatements=true
                username: aihosp
                password: DF3f3#KF#83Fe
        sharding:
            tables:
                year_table:
                    actual-data-nodes: ds-master.year_table$->{2021..2025}  #按年分表
                    tableStrategy:
                        standard: #用于单分片键的标准分片场景
                            sharding-column: create_date
                            precise-algorithm-class-name: com.gxfy.common.algorithm.PreciseRangeShardingAlgorithm # 精确分片算法类名称，用于=和IN。该类需实现PreciseShardingAlgorithm接口并提供无参数的构造器
                            range-algorithm-class-name: com.gxfy.common.algorithm.PreciseRangeShardingAlgorithm #范围分片算法类名称，用于BETWEEN，可选。该类需实现RangeShardingAlgorithm接口并提供无参数的构造器
                    key-generator:
                        column: id
                        type: SNOWFLAKE #分布式全局ID（雪花算法）
                        retry-interval-milliseconds: 500
             
                month_table:
                    actual-data-nodes: ds-master.month_table$->{2022..2025}0$->{1..9},ds-master.month_table$->{2022..2025}1$->{0..2}  #按月分表
                    tableStrategy:
                        standard: #用于单分片键的标准分片场景
                            sharding-column: create_date
                            precise-algorithm-class-name: com.gxfy.common.algorithm.PreciseRangeShardingAlgorithm
                            range-algorithm-class-name: com.gxfy.common.algorithm.PreciseRangeShardingAlgorithm
                    key-generator:
                        column: id
                        type: SNOWFLAKE #分布式全局ID（雪花算法）
                        retry-interval-milliseconds: 500
     ）
                        retry-interval-milliseconds: 500

        #其他运行属性
        props:
            sql:
                show: false

3、分片算法

import com.google.common.collect.Range;
import lombok.extern.slf4j.Slf4j;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.api.sharding.standard.RangeShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.RangeShardingValue;

import java.util.Collection;
import java.util.LinkedHashSet;
import java.util.Set;

/**
 *
 * 按年分片
 * 精准分库PreciseShardingDBAlgorithm
 *
 * 范围分库RangeShardingDBAlgorithm
 *
 * 精准分表PreciseShardingTableAlgorithm
 *
 * 范围分表RangeShardingTableAlgorithm：
 */
@Slf4j
public class PreciseRangeShardingAlgorithm implements PreciseShardingAlgorithm<String>,RangeShardingAlgorithm<String> {
    /**
     *  RangeShardingAlgorithm的重写  根据传入的分片健的值，对所有待选择的表中 根据自己的业务逻辑进行判断，选择符合条件的表返回
     * @param tableNameList 返回需要查询的表
     * @param shardingValue 传入的分片健的值
     * @return 返回符合条件的表名称
     */
    @Override
    public Collection<String> doSharding(Collection<String> tableNameList, RangeShardingValue<String> shardingValue) {

        System.out.println("[MyTableRangeShardingAlgorithm] shardingValue: [{}]\n"+ shardingValue);
        Set<String> tableNameResultList = new LinkedHashSet<>();
        Range<String> rangeValue = shardingValue.getValueRange();

        String flag = "year";
        for (String tableName : tableNameList) {
            if (tableName.startsWith("month_table")) {
                flag = "month";
                break;
            }

        }

        if ("year".equals(flag)) {
            int lowInt = Integer.parseInt(rangeValue.lowerEndpoint().substring(0,5).replaceAll("-",""));
            int upperInt = Integer.parseInt(rangeValue.upperEndpoint().substring(0,5).replaceAll("-",""));

            for (String tableNameItem : tableNameList) {
                String substring = tableNameItem.substring(tableNameItem.length() - 4);
                int tableItem = Integer.valueOf(substring);
                if(tableItem >=  lowInt && tableItem <= upperInt ){
                    tableNameResultList.add(tableNameItem);
                }

            }
        } else if ("month".equals(flag)) {

            int lowInt = Integer.parseInt(rangeValue.lowerEndpoint().substring(0,7).replaceAll("-",""));
            int upperInt = Integer.parseInt(rangeValue.upperEndpoint().substring(0,7).replaceAll("-",""));

            for (String tableNameItem : tableNameList) {
                String substring = tableNameItem.substring(tableNameItem.length() - 6,tableNameItem.length());
                int tableItem = Integer.valueOf(substring);
                if(tableItem >=  lowInt && tableItem <= upperInt ){
                    tableNameResultList.add(tableNameItem);
                }

            }
        }


        return tableNameResultList;
    }



    /** PreciseShardingAlgorithm的重写 */
    @Override
    public String doSharding(Collection<String> collection, PreciseShardingValue<String> preciseShardingValue) {
        String s = buildShardingTable(preciseShardingValue.getLogicTableName(), preciseShardingValue.getValue());
        return s;
    }

    /**
     * 构建分片后的表名
     * @param logicTableName
     * @param date
     * @return
     */
    private String buildShardingTable(String logicTableName, String date) {

        StringBuffer stringBuffer = new StringBuffer(logicTableName).append("_").append(date, 0, 4);
        if (logicTableName.startsWith("month_table") ) {
            // 月分表
           stringBuffer = new StringBuffer(logicTableName).append("_").append(date, 0, 4)
                    .append(date, 5, 7);
        }
        return stringBuffer.toString();
    }

}