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

时间:2020-01-18 14:27:40      阅读:112      评论:0      收藏:0      [点我收藏+]

标签:new t   nta   转化   反射   wired   http   构造   tween   reflect   

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LogShardingAlgorithmtables,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();
    }

    @Override
    public 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;
    }

    @Override
    public 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 {
    @Autowired
    private DataSource dataSource;

    @PostConstruct
    public 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 {
    
    @Getter
    private 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")
    @Override
    public 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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sharding sphere 4.0.0-RC1版本 按年分表(后续优化)

标签:new t   nta   转化   反射   wired   http   构造   tween   reflect   

原文地址:https://www.cnblogs.com/sky-chen/p/12208821.html

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