inline 配置，只支持 = IN 两种 SQL 语法
    但是业务需要 >= <= 之类的范围查询，所以需要修改分片策略

    1. 实现精准分片接口 PreciseShardingAlgorithm 和范围分片接口 RangeShardingAlgorithm
    2. 修改 application.yaml 配置文件

    配置文件：

    1. ...
    2. 省略数据源以及默认配置
    3. ...
    4.         t_eth_transaction:
    5.           actual-data-nodes: test$->{1}.t_eth_transaction$->{9..12}
    6.           table-strategy:
    7. #            inline:
    8. #              sharding-column: block_number
    9. #              algorithm-expression: t_eth_transaction$->{ (block_number/1000000) as int}    # 分表规则为id对3取模，id%3为0表示分到user0表
    10.              standard: # 单列sharidng算法,需要配合对应的 preciseShardingAlgorithm,rangeShardingAlgorithm 接口的实现使用
    11.                shardingColumn: block_number # 列名,允许单列
    12.                preciseAlgorithmClassName: com.paradise.sharding.strategy.RangeShardingAlgorithmImpl # preciseShardingAlgorithm接口的实现类
    13.                rangeAlgorithmClassName: com.paradise.sharding.strategy.RangeShardingAlgorithmImpl # rangeShardingAlgorithm接口的实现类

    接口实现：

    1. package com.paradise.sharding.strategy;
    3. import com.google.common.collect.Range;
    4. import lombok.extern.slf4j.Slf4j;
    5. import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
    6. import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
    7. import org.apache.shardingsphere.api.sharding.standard.RangeShardingAlgorithm;
    8. import org.apache.shardingsphere.api.sharding.standard.RangeShardingValue;
    10. import java.util.Collection;
    11. import java.util.LinkedHashSet;
    12. import java.util.Map;
    13. import java.util.function.Function;
    14. import java.util.stream.Collectors;
    16. /**
    17.  * 分片策略实现
    18.  * 包含精准分片与范围分片
    19.  *
    20.  * @author Paradise
    21.  */
    22. @Slf4j
    23. public class RangeShardingAlgorithmImpl implements RangeShardingAlgorithm<Long>, PreciseShardingAlgorithm<Long> {
    25.     /**
    26.      * 100w 分片区块
    27.      */
    28.     private static final long DIVISOR = 1_000_000;
    29.     /**
    30.      * 分片表前缀
    31.      */
    32.     private static final String TABLE_PREFIX = "t_eth_transaction";
    34.     public RangeShardingAlgorithmImpl() {
    35.         log.info("初始化 -> [{}]", "RangeShardingAlgorithmImpl ----- 范围分片算法-启用");
    36.     }
    38.     /**
    39.      * Sharding.
    40.      *
    41.      * @param availableTargetNames available data sources or tables' names
    42.      * @param shardingValue        sharding value
    43.      * @return sharding results for data sources or tables' names
    44.      */
    45.     @Override
    46.     public Collection<String> doSharding(Collection<String> availableTargetNames, RangeShardingValue<Long> shardingValue) {
    47.         // 可用表名称 Map
    48.         final Map<String, String> map = availableTargetNames.stream()
    49.                 .collect(Collectors.toMap(Function.identity(), Function.identity()));
    50.         // 构造返回结果
    51.         Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
    52.         // 获取待查询范围
    53.         Range<Long> range = shardingValue.getValueRange();
    54.         // 除法取整
    55.         long low = range.lowerEndpoint() / DIVISOR;
    56.         long upper = range.upperEndpoint() / DIVISOR;
    57.         // 遍历获取路由表信息
    58.         for (long i = low; i <= upper; i++) {
    59.             final String table = TABLE_PREFIX + i;
    60.             if (map.containsKey(table)) {
    61.                 result.add(table);
    62.             }
    63.         }
    64.         return result;
    65.     }
    67.     /**
    68.      * Sharding.
    69.      *
    70.      * @param availableTargetNames available data sources or tables' names
    71.      * @param shardingValue        sharding value
    72.      * @return sharding result for data source or table's name
    73.      */
    74.     @Override
    75.     public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Long> shardingValue) {
    76.         // 可用表名称 Map
    77.         final Map<String, String> map = availableTargetNames.stream()
    78.                 .collect(Collectors.toMap(Function.identity(), Function.identity()));
    79.         final long value = shardingValue.getValue() / DIVISOR;
    80.         final String table = TABLE_PREFIX + value;
    81.         if (map.containsKey(table)) {
    82.             return table;
    83.         }
    84.         log.info("分片表：{} 不存在", table);
    85.         throw new UnsupportedOperationException(table + " Not Exist!");
    86.     }
    88. }