sharding sphere 4.0.0-RC1版本按年分表（后续优化）

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1. sharding sphere 4.0.0-RC1版本按年分表（后续优化）

1.1. 概述

关于上一篇中LogShardingAlgorithm的tables，我原先是在第一次调用的时候初始化，这样做虽然能实现功能，但每次调用都会走这个if判断，虽然性能损耗不大，但我觉得这不是业务应该走的逻辑顺序，我的理想是在LogShardingAlgorithm被实例化后去自动初始化tables

现在面对的问题是LogShardingAlgorithm的实例化是在Spring初始化中间执行的，且它本身的创建不是通过Spring的@Component等注解生成，而是通过反射实例化。若在实例化刚开始，也就是构造方法执行的时候执行初始化，那时候applicationContext还没有初始化完毕，拿不到环境参数，连Datasource也还没开始初始化

1.2. 解决方法

经过改造后，代码如下，单独拎出一个初始化方法，在类对象实例化后调用

/*** @author: laoliangliang* @description: 日志分片* @create: 2020/1/2 10:19**/
@Slf4j
public class LogShardingAlgorithm implements PreciseShardingAlgorithm, RangeShardingAlgorithm<Integer> {/*** 缓存存在的表*/private List<String> tables;private final String systemLogHead = "system_log_";public void init(){tables = DBUtil.getAllSystemLogTable();}@Overridepublic String doSharding(Collection availableTargetNames, PreciseShardingValue shardingValue) {String target = shardingValue.getValue().toString();String year = target.substring(target.lastIndexOf("_")   1, target.lastIndexOf("_")   5);if (!tables.contains(systemLogHead   year)) {DBUtil.createLogTable(year);tables.add(year);}return shardingValue.getLogicTableName()   "_"   year;}@Overridepublic Collection<String> doSharding(Collection<String> availableTargetNames, RangeShardingValue<Integer> shardingValue) {Collection<String> availables = new ArrayList<>();Range valueRange = shardingValue.getValueRange();for (String target : tables) {Integer shardValue = Integer.parseInt(target.substring(target.lastIndexOf("_")   1, target.lastIndexOf("_")   5));if (valueRange.hasLowerBound()) {String lowerStr = valueRange.lowerEndpoint().toString();Integer start = Integer.parseInt(lowerStr.substring(0, 4));if (start - shardValue > 0) {continue;}}if (valueRange.hasUpperBound()) {String upperStr = valueRange.upperEndpoint().toString();Integer end = Integer.parseInt(upperStr.substring(0, 4));if (end - shardValue < 0) {continue;}}availables.add(target);}return availables;}
}

其中init方法通过另一个类实例化完成后调用，难点在于如何拿到该实例化的LogShardingAlgorithm

import cn.hutool.core.util.ReflectUtil;
import com.google.common.base.Optional;
import com.onegene.platform.system.log.LogShardingAlgorithm;
import org.apache.shardingsphere.core.rule.ShardingRule;
import org.apache.shardingsphere.core.rule.TableRule;
import org.apache.shardingsphere.core.strategy.route.ShardingStrategy;
import org.apache.shardingsphere.shardingjdbc.jdbc.core.ShardingContext;
import org.apache.shardingsphere.shardingjdbc.jdbc.core.datasource.ShardingDataSource;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;import javax.annotation.PostConstruct;
import javax.sql.DataSource;
/*** @author: laoliangliang* @description:* @create: 2020/1/18 8:29**/
@Component
public class StartupConfig {@Autowiredprivate DataSource dataSource;@PostConstructpublic void init() {this.loadLogInit();}private void loadLogInit() {if (dataSource instanceof ShardingDataSource) {ShardingDataSource sds = (ShardingDataSource) dataSource;ShardingContext shardingContext = sds.getShardingContext();ShardingRule shardingRule = shardingContext.getShardingRule();Optional<TableRule> systemLog = shardingRule.findTableRule("system_log");TableRule tableRule = systemLog.orNull();if (tableRule != null) {ShardingStrategy tableShardingStrategy = tableRule.getTableShardingStrategy();LogShardingAlgorithm preciseShardingAlgorithm = (LogShardingAlgorithm) ReflectUtil.getFieldValue(tableShardingStrategy, "preciseShardingAlgorithm");LogShardingAlgorithm rangeShardingAlgorithm = (LogShardingAlgorithm) ReflectUtil.getFieldValue(tableShardingStrategy, "rangeShardingAlgorithm");preciseShardingAlgorithm.init();rangeShardingAlgorithm.init();}}}
}

1.3. 总结

通过查看源码可以知道，它最后把LogShardingAlgorithm实例化的对象放入了ShardingDataSource，那我们就要从里面把它取出来，若它正常没提供get方法，那我们就用反射硬把它取出来

通过上述代码可以看出，范围分片和精确分片需要实例化两个类，我想是否可以合到一个类，网上也找了一下，发现有的版本使用ComplexKeysShardingAlgorithm算法是可以同时实现范围和精确分片查询的，但经过我实际测试，现在的4.0.0版本不行，原因在于以下代码，此为复杂分片源码

public final class ComplexShardingStrategy implements ShardingStrategy {@Getterprivate final Collection<String> shardingColumns;private final ComplexKeysShardingAlgorithm shardingAlgorithm;public ComplexShardingStrategy(final ComplexShardingStrategyConfiguration complexShardingStrategyConfig) {Preconditions.checkNotNull(complexShardingStrategyConfig.getShardingColumns(), "Sharding columns cannot be null.");Preconditions.checkNotNull(complexShardingStrategyConfig.getShardingAlgorithm(), "Sharding algorithm cannot be null.");shardingColumns = new TreeSet<>(String.CASE_INSENSITIVE_ORDER);shardingColumns.addAll(Splitter.on(",").trimResults().splitToList(complexShardingStrategyConfig.getShardingColumns()));shardingAlgorithm = complexShardingStrategyConfig.getShardingAlgorithm();}@SuppressWarnings("unchecked")@Overridepublic Collection<String> doSharding(final Collection<String> availableTargetNames, final Collection<RouteValue> shardingValues) {Map<String, Collection<Comparable<?>>> columnShardingValues = new HashMap<>(shardingValues.size(), 1);String logicTableName = "";for (RouteValue each : shardingValues) {// 重点这里他把each的值强行转化成了ListRouteValue而范围查询对应的为BetweenRouteValue，所以在源码级别就被卡死了，除非重写策略，否则这个已经不能像以前那样用了columnShardingValues.put(each.getColumnName(), ((ListRouteValue) each).getValues());logicTableName = each.getTableName();}Collection<String> shardingResult = shardingAlgorithm.doSharding(availableTargetNames, new ComplexKeysShardingValue(logicTableName, columnShardingValues));Collection<String> result = new TreeSet<>(String.CASE_INSENSITIVE_ORDER);result.addAll(shardingResult);return result;}
}

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