Sharding-JDBC（三）3.1.0版本实践

一、Sharding-JDBC依赖

<!-- sharding-jdbc-core -->
<dependency><groupId>io.shardingsphere</groupId><artifactId>sharding-jdbc-core</artifactId><version>3.1.0</version>
</dependency>
<!-- sharding-jdbc-spring-namespace -->
<dependency><groupId>io.shardingsphere</groupId><artifactId>sharding-jdbc-spring-namespace</artifactId><version>3.1.0</version>
</dependency>

和2.0.3版本相比，依赖的名称有所改变，不要搞错了哦。

二、代码实践

业务背景就不再介绍了，不了解可移步至Sharding-JDBC（二）2.0.3版本实践。

如下代码配置了标准分片策略中的精确分片算法PreciseShardingAlgorithm和Hint分片算法HintShardingAlgorithm。

XML配置：

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xmlns:tx="http://www.springframework.org/schema/tx"xmlns:sharding="http://shardingsphere.io/schema/shardingsphere/sharding"xsi:schemaLocation="http://www.springframework.org/schema/beanshttp://www.springframework.org/schema/beans/spring-beans.xsdhttp://www.springframework.org/schema/txhttp://www.springframework.org/schema/tx/spring-tx.xsdhttp://shardingsphere.io/schema/shardingsphere/shardinghttp://shardingsphere.io/schema/shardingsphere/sharding/sharding.xsd"><!-- 标准分片策略 --><sharding:standard-strategy id="settlementTableShardingStandardStrategy" sharding-column="pay_serial_number"precise-algorithm-ref="preciseTableShardingAlgorithm"/><!-- 基于暗示(Hint)的分片策略 --><sharding:hint-strategy id="settlementHintTableShardingStrategy" algorithm-ref="hintTableShardingAlgorithm"/><sharding:hint-strategy id="settlementHintDatabaseShardingStrategy" algorithm-ref="hintDatabaseShardingAlgorithm"/><sharding:data-source id="shardingDataSource"><sharding:sharding-rule data-source-names="dataSource"><sharding:table-rules><sharding:table-rule logic-table="settlement"table-strategy-ref="settlementTableShardingStandardStrategy"/><!-- logic-table参数的大小写必须和SettlementMapper.xml中selectByExample方法的表名大小一致！！！ --><!-- logic-table必须和org.cellphone.finance.repo.SettlementRepository.querySettlements中的logicTable及SQL中的表名一致，否则无法找到分片策略 --><!-- 逻辑表名，不需要和真实表名一致 --><sharding:table-rule logic-table="settlement_hint"database-strategy-ref="settlementHintDatabaseShardingStrategy"table-strategy-ref="settlementHintTableShardingStrategy"/></sharding:table-rules></sharding:sharding-rule><sharding:props><prop key="sql.show">true</prop></sharding:props></sharding:data-source><bean id="transactionManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager"><property name="dataSource" ref="shardingDataSource"/></bean><tx:annotation-driven/></beans>

精确分片算法：

package org.cellphone.finance.repo.sharding;import com.google.common.collect.Lists;
import io.shardingsphere.api.algorithm.sharding.PreciseShardingValue;
import io.shardingsphere.api.algorithm.sharding.standard.PreciseShardingAlgorithm;
import org.apache.commons.collections.CollectionUtils;
import org.cellphone.common.constant.CommonConst;
import org.springframework.stereotype.Component;import java.util.Collection;/*** 精确分片算法，属于标准分片算法，用于处理=和IN的分片* <p>* 使用精确分片算法的前提：分片字段必须存在与SQL中、数据库表结构中，否则无法使用精确分片算法* <p>* 此分片算法应用于SETTLEMENT数据表，这里是按天分表* <p>* 特别说明：Sharding Jdbc版本：3.1.0* <p>* Created by on 2018/4/9.*/
@Component("preciseTableShardingAlgorithm")
public class PreciseTableShardingAlgorithm implements PreciseShardingAlgorithm<String> {/*** 精确分片算法** @param availableTargetNames 目标数据源名称或数据表名称，注意：是逻辑数据源名或逻辑数据表名，来自SQL* @param shardingValue        分片值，来自SQL中分片字段对应的值* @return 真实数据源名称或数据表名称*/@Overridepublic String doSharding(final Collection<String> availableTargetNames, final PreciseShardingValue<String> shardingValue) {// 默认数据表名称，有可能数据库中不存在这张表String tableName = "settlement";// 逻辑表名为空，返回默认表名if (CollectionUtils.isEmpty(availableTargetNames))return tableName;// availableTargetNames来自SQL，只有一个元素tableName = Lists.newArrayList(availableTargetNames).get(0);String paySerialNumber = shardingValue.getValue();String suffix = paySerialNumber.substring(5, 13);return tableName + CommonConst.UNDERLINE + suffix;}
}

Hint数据源分片算法：

package org.cellphone.finance.repo.sharding;import io.shardingsphere.api.algorithm.sharding.ShardingValue;
import io.shardingsphere.api.algorithm.sharding.hint.HintShardingAlgorithm;
import org.springframework.stereotype.Component;import java.util.Collection;/*** Sharding Jdbc基于暗示(Hint)的数据分片算法** 使用Sharding Jdbc 3.x版本时，此数据源分片算法这个一定要有！！！* 否则无法正常使用org.cellphone.finance.repo.sharding.HintTableShardingAlgorithm算法* <p>* Created by on 2019/4/25.*/
@Component("hintDatabaseShardingAlgorithm")
public class HintDatabaseShardingAlgorithm implements HintShardingAlgorithm {@Overridepublic Collection<String> doSharding(Collection<String> availableTargetNames, ShardingValue shardingValue) {return availableTargetNames;}
}

Hint数据表分片算法：

package org.cellphone.finance.repo.sharding;import com.google.common.collect.Lists;
import io.shardingsphere.api.algorithm.sharding.ListShardingValue;
import io.shardingsphere.api.algorithm.sharding.ShardingValue;
import io.shardingsphere.api.algorithm.sharding.hint.HintShardingAlgorithm;
import org.apache.commons.collections.CollectionUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.commons.lang3.time.DateFormatUtils;
import org.apache.commons.lang3.time.DateUtils;
import org.cellphone.common.constant.CommonConst;
import org.cellphone.common.constant.DateConst;
import org.springframework.stereotype.Component;import java.text.ParseException;
import java.util.*;/*** Sharding Jdbc基于暗示(Hint)的数据分片算法* 版本：Sharding Jdbc 3.1.0** 官方介绍（2.x版本）：http://shardingsphere.apache.org/document/legacy/2.x/cn/02-guide/hint-sharding-value/* 官方介绍（4.x版本）：https://shardingsphere.apache.org/document/current/cn/manual/sharding-jdbc/usage/hint/* <p>* <p>* <p>* <p>* 使用此算法的背景如下：* 1. SETTLEMENT（支付表）是按时间维度进行分表，该时间取自PAY_SERIAL_NUMBER中的时间数据，非表中的时间字段；* <p>* 2. 使用用户手机号此类条件查询数据时，请求参数除传入业务参数外，*      还需传入时间段（即分片字段，例：startTime和endTime）以确定分表范围；*      但是！！！startTime和endTime（即分片字段）不存在SQL中、数据库表结构中，而存在于外部业务逻辑* <p>* <p>* <p>* 因此，第2点导致无法直接使用Sharding Jdbc的PreciseShardingAlgorithm（精确分片算法）或RangeShardingAlgorithm（范围分片算法），* 只能使用HintShardingAlgorithm（基于暗示的数据分片算法），该算法的使用场景如下：* 1. 分片字段不存在SQL中、数据库表结构中，而存在于外部业务逻辑；* <p>* 2. 强制在主库进行某些数据操作。* <p>* <p>* Created by on 2019/4/25.*/
@Component("hintTableShardingAlgorithm")
public class HintTableShardingAlgorithm implements HintShardingAlgorithm {/*** 分片算法** @param availableTargetNames 逻辑数据库名称或逻辑数据表名称* @param shardingValue        用来确定分表的参数* @return 实际数据表名称列表，SQL实际操作的数据表*/@Overridepublic Collection<String> doSharding(Collection<String> availableTargetNames, ShardingValue shardingValue) {String realTableName = StringUtils.EMPTY;for (String each : availableTargetNames) {if (StringUtils.isNotBlank(each)) {// 基于hint的逻辑表名：settlement_hintrealTableName = each.replace("_hint", StringUtils.EMPTY);break;}}List<String> tables = new ArrayList<>();ListShardingValue<String> listShardingValue = (ListShardingValue<String>) shardingValue;List<String> list = Lists.newArrayList(listShardingValue.getValues());// 缺少确定分表的参数，无法确定具体分表，直接返回真实表名称if (CollectionUtils.isEmpty(list)) {tables.add(realTableName);return tables;}// 拆分分表参数，此参数值来自：com.fcbox.manage.core.repo.FcBoxPostRepository.queryFcBoxPosts()String[] queryTime = list.get(0).split(CommonConst.UNDERLINE);Date startTime, endTime;try {startTime = DateUtils.parseDate(queryTime[0], DateConst.DATE_FORMAT_NORMAL);endTime   = DateUtils.parseDate(queryTime[1], DateConst.DATE_FORMAT_NORMAL);} catch (ParseException e) {// 分表参数解析错误，无法确定具体分表，直接返回真实表名称tables.add(realTableName);return tables;}Calendar calendar = Calendar.getInstance();// 组织startTime和endTime时段范围内的分表while (startTime.getTime() <= endTime.getTime()) {tables.add(realTableName + CommonConst.UNDERLINE + DateFormatUtils.format(startTime, DateConst.DATE_FORMAT_YYYY_MM_DD));calendar.setTime(startTime);calendar.add(Calendar.DATE, 1);startTime = calendar.getTime();}return tables;}
}

与Hint分片算法对应的Java查询方法 settlementMapper.selectByExample(example)：

    public List<Settlement> querySettlements(SettlementExample example, String startTime, String endTime) {// 组织查询时间，传入org.cellphone.finance.repo.sharding.HintTableShardingAlgorithm分片算法中以确认具体分表String queryTime = startTime + CommonConst.UNDERLINE + endTime;// 获取HintManagerHintManager hintManager = HintManager.getInstance();/** 添加数据源分片键值，使用Sharding Jdbc 3.x版本一定要添加数据源分片键值，否则无法使用HintTableShardingAlgorithm分片算法* 若无分库，addDatabaseShardingValue方法的value字段随意填充* 若有分库，addDatabaseShardingValue方法的value字段填充实际参数值*/hintManager.addDatabaseShardingValue("settlement_hint", StringUtils.EMPTY);// 添加数据表分片键值hintManager.addTableShardingValue("settlement_hint", queryTime);List<Settlement> settlements = settlementMapper.selectByExample(example);// 清除分片键值hintManager.close();return settlements;}

以及该查询方法对应的SQL语句：

select * from settlement_hint t where t.pay_serial_number = ?

单元测试代码：

@Test
public void test003QuerySettlements() throws ParseException {String startTime = "2018-04-03 00:00:00", endTime = "2018-04-05 00:00:00";SettlementExample example = new SettlementExample();SettlementExample.Criteria criteria = example.createCriteria();criteria.andPaySerialNumberEqualTo(paySerialNumber);List<Settlement> settlements = repository.querySettlements(example, startTime, endTime);Assert.assertEquals("136********", settlements.get(0).getUserMobile());
}

三、源码分析

和2.0.3版本相比，3.1.0版本的路由入口变成了 io.shardingsphere.core.routing.type.standard.StandardRoutingEngine#route() ，但基本上区别不大，仅仅是多了一步需要确定路由的真实数据源，尽管数据源只有一个，也需要显式配置数据源路由算法。代码中标注了注释的部分都是路由代码比较核心的部分。

/** Copyright 2016-2018 shardingsphere.io.* <p>* Licensed under the Apache License, Version 2.0 (the "License");* you may not use this file except in compliance with the License.* You may obtain a copy of the License at**     http://www.apache.org/licenses/LICENSE-2.0** Unless required by applicable law or agreed to in writing, software* distributed under the License is distributed on an "AS IS" BASIS,* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.* See the License for the specific language governing permissions and* limitations under the License.* </p>*/package io.shardingsphere.core.routing.type.standard;import com.google.common.base.Optional;
import com.google.common.base.Preconditions;
import io.shardingsphere.api.algorithm.sharding.ShardingValue;
import io.shardingsphere.core.hint.HintManagerHolder;
import io.shardingsphere.core.optimizer.condition.ShardingCondition;
import io.shardingsphere.core.optimizer.condition.ShardingConditions;
import io.shardingsphere.core.optimizer.insert.InsertShardingCondition;
import io.shardingsphere.core.routing.strategy.ShardingStrategy;
import io.shardingsphere.core.routing.strategy.hint.HintShardingStrategy;
import io.shardingsphere.core.routing.type.RoutingEngine;
import io.shardingsphere.core.routing.type.RoutingResult;
import io.shardingsphere.core.routing.type.RoutingTable;
import io.shardingsphere.core.routing.type.TableUnit;
import io.shardingsphere.core.rule.BindingTableRule;
import io.shardingsphere.core.rule.DataNode;
import io.shardingsphere.core.rule.ShardingRule;
import io.shardingsphere.core.rule.TableRule;
import lombok.RequiredArgsConstructor;import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.LinkedHashSet;
import java.util.LinkedList;
import java.util.List;/*** Standard routing engine.** @author zhangliang* @author maxiaoguang* @author panjuan*/
@RequiredArgsConstructor
public final class StandardRoutingEngine implements RoutingEngine {private final ShardingRule shardingRule;private final String logicTableName;private final ShardingConditions shardingConditions;/*** 相比2.0.3版本，精简成了1行代码** @return 路由结果*/@Overridepublic RoutingResult route() {return generateRoutingResult(getDataNodes(shardingRule.getTableRuleByLogicTableName(logicTableName)));}private RoutingResult generateRoutingResult(final Collection<DataNode> routedDataNodes) {RoutingResult result = new RoutingResult();for (DataNode each : routedDataNodes) {TableUnit tableUnit = new TableUnit(each.getDataSourceName());tableUnit.getRoutingTables().add(new RoutingTable(logicTableName, each.getTableName()));result.getTableUnits().getTableUnits().add(tableUnit);}return result;}/*** 获取数据节点，即真实表** @param tableRule 从XML读取的table rule* @return 数据节点列表*/private Collection<DataNode> getDataNodes(final TableRule tableRule) {// 判断是否是通过Hint分片策略进行路由if (isRoutingByHint(tableRule)) {return routeByHint(tableRule);}if (isRoutingByShardingConditions(tableRule)) {return routeByShardingConditions(tableRule);}return routeByMixedConditions(tableRule);}/*** 判断是否是通过Hint分片策略进行路由* <p>* 数据源分片策略和数据表分片策略都必须是HintShardingStrategy，这意味者必须显式配置数据源Hint分片策略和数据表Hint分片策略** @param tableRule 从XML读取的table rule* @return*/private boolean isRoutingByHint(final TableRule tableRule) {return shardingRule.getDatabaseShardingStrategy(tableRule) instanceof HintShardingStrategy && shardingRule.getTableShardingStrategy(tableRule) instanceof HintShardingStrategy;}/*** 通过Hint分片策略进行路由** @param tableRule* @return*/private Collection<DataNode> routeByHint(final TableRule tableRule) {return route(tableRule, getDatabaseShardingValuesFromHint(), getTableShardingValuesFromHint());}private boolean isRoutingByShardingConditions(final TableRule tableRule) {return !(shardingRule.getDatabaseShardingStrategy(tableRule) instanceof HintShardingStrategy || shardingRule.getTableShardingStrategy(tableRule) instanceof HintShardingStrategy);}private Collection<DataNode> routeByShardingConditions(final TableRule tableRule) {return shardingConditions.getShardingConditions().isEmpty() ? route(tableRule, Collections.<ShardingValue>emptyList(), Collections.<ShardingValue>emptyList()): routeByShardingConditionsWithCondition(tableRule);}private Collection<DataNode> routeByShardingConditionsWithCondition(final TableRule tableRule) {Collection<DataNode> result = new LinkedList<>();for (ShardingCondition each : shardingConditions.getShardingConditions()) {Collection<DataNode> dataNodes = route(tableRule, getShardingValuesFromShardingConditions(shardingRule.getDatabaseShardingStrategy(tableRule).getShardingColumns(), each),getShardingValuesFromShardingConditions(shardingRule.getTableShardingStrategy(tableRule).getShardingColumns(), each));reviseShardingConditions(each, dataNodes);result.addAll(dataNodes);}return result;}private Collection<DataNode> routeByMixedConditions(final TableRule tableRule) {return shardingConditions.getShardingConditions().isEmpty() ? routeByMixedConditionsWithHint(tableRule) : routeByMixedConditionsWithCondition(tableRule);}private Collection<DataNode> routeByMixedConditionsWithCondition(final TableRule tableRule) {Collection<DataNode> result = new LinkedList<>();for (ShardingCondition each : shardingConditions.getShardingConditions()) {Collection<DataNode> dataNodes = route(tableRule, getDatabaseShardingValues(tableRule, each), getTableShardingValues(tableRule, each));reviseShardingConditions(each, dataNodes);result.addAll(dataNodes);}return result;}private Collection<DataNode> routeByMixedConditionsWithHint(final TableRule tableRule) {if (shardingRule.getDatabaseShardingStrategy(tableRule) instanceof HintShardingStrategy) {return route(tableRule, getDatabaseShardingValuesFromHint(), Collections.<ShardingValue>emptyList());}return route(tableRule, Collections.<ShardingValue>emptyList(), getTableShardingValuesFromHint());}private List<ShardingValue> getDatabaseShardingValues(final TableRule tableRule, final ShardingCondition shardingCondition) {ShardingStrategy dataBaseShardingStrategy = shardingRule.getDatabaseShardingStrategy(tableRule);return isGettingShardingValuesFromHint(dataBaseShardingStrategy)? getDatabaseShardingValuesFromHint() : getShardingValuesFromShardingConditions(dataBaseShardingStrategy.getShardingColumns(), shardingCondition);}private List<ShardingValue> getTableShardingValues(final TableRule tableRule, final ShardingCondition shardingCondition) {ShardingStrategy tableShardingStrategy = shardingRule.getTableShardingStrategy(tableRule);return isGettingShardingValuesFromHint(tableShardingStrategy)? getTableShardingValuesFromHint() : getShardingValuesFromShardingConditions(tableShardingStrategy.getShardingColumns(), shardingCondition);}private boolean isGettingShardingValuesFromHint(final ShardingStrategy shardingStrategy) {return shardingStrategy instanceof HintShardingStrategy;}/*** 从HintManagerHolder中获取数据源分片值** @return 数据源分片值列表*/private List<ShardingValue> getDatabaseShardingValuesFromHint() {// getDatabaseShardingValue方法实现有点恶心，不兼容大小写...Optional<ShardingValue> shardingValueOptional = HintManagerHolder.getDatabaseShardingValue(logicTableName);return shardingValueOptional.isPresent() ? Collections.singletonList(shardingValueOptional.get()) : Collections.<ShardingValue>emptyList();}private List<ShardingValue> getTableShardingValuesFromHint() {// getTableShardingValue方法实现有点恶心，不兼容大小写...Optional<ShardingValue> shardingValueOptional = HintManagerHolder.getTableShardingValue(logicTableName);return shardingValueOptional.isPresent() ? Collections.singletonList(shardingValueOptional.get()) : Collections.<ShardingValue>emptyList();}private List<ShardingValue> getShardingValuesFromShardingConditions(final Collection<String> shardingColumns, final ShardingCondition shardingCondition) {List<ShardingValue> result = new ArrayList<>(shardingColumns.size());for (ShardingValue each : shardingCondition.getShardingValues()) {Optional<BindingTableRule> bindingTableRule = shardingRule.findBindingTableRule(logicTableName);if ((logicTableName.equals(each.getLogicTableName()) || bindingTableRule.isPresent() && bindingTableRule.get().hasLogicTable(logicTableName))&& shardingColumns.contains(each.getColumnName())) {result.add(each);}}return result;}/*** 路由，获取真实表列表** @param tableRule              从XML读取的table rule* @param databaseShardingValues 数据源分片值* @param tableShardingValues    数据表分片值* @return 真实表列表*/private Collection<DataNode> route(final TableRule tableRule, final List<ShardingValue> databaseShardingValues, final List<ShardingValue> tableShardingValues) {Collection<String> routedDataSources = routeDataSources(tableRule, databaseShardingValues);Collection<DataNode> result = new LinkedList<>();for (String each : routedDataSources) {result.addAll(routeTables(tableRule, each, tableShardingValues));}return result;}/*** 路由到真实数据源** @param tableRule              从XML读取的table rule* @param databaseShardingValues 数据源分片值* @return 真实数据源列表*/private Collection<String> routeDataSources(final TableRule tableRule, final List<ShardingValue> databaseShardingValues) {Collection<String> availableTargetDatabases = tableRule.getActualDatasourceNames();if (databaseShardingValues.isEmpty()) {return availableTargetDatabases;}Collection<String> result = new LinkedHashSet<>(shardingRule.getDatabaseShardingStrategy(tableRule).doSharding(availableTargetDatabases, databaseShardingValues));Preconditions.checkState(!result.isEmpty(), "no database route info");return result;}/*** 路由到真实数据表，和2.0.3版本没啥区别** @param tableRule           从XML读取的table rule* @param routedDataSource    已确认好的数据源* @param tableShardingValues 数据表分片值* @return 真实表列表*/private Collection<DataNode> routeTables(final TableRule tableRule, final String routedDataSource, final List<ShardingValue> tableShardingValues) {Collection<String> availableTargetTables = tableRule.getActualTableNames(routedDataSource);Collection<String> routedTables = new LinkedHashSet<>(tableShardingValues.isEmpty() ? availableTargetTables: shardingRule.getTableShardingStrategy(tableRule).doSharding(availableTargetTables, tableShardingValues));Preconditions.checkState(!routedTables.isEmpty(), "no table route info");Collection<DataNode> result = new LinkedList<>();for (String each : routedTables) {result.add(new DataNode(routedDataSource, each));}return result;}private void reviseShardingConditions(final ShardingCondition each, final Collection<DataNode> dataNodes) {if (each instanceof InsertShardingCondition) {((InsertShardingCondition) each).getDataNodes().addAll(dataNodes);}}
}

分析到此，Sharding-JDBC 3.1.0版本可以支持分片键不存在于SQL中和数据表结构中的使用场景。但3.1.0版本还有一个比较恶心的地方，Sharding-JDBC在初始化时，会连接数据库获取数据表的元数据，包括需要水平切分的表和不需水平切分的表。代码如下：

/** Copyright 2016-2018 shardingsphere.io.* <p>* Licensed under the Apache License, Version 2.0 (the "License");* you may not use this file except in compliance with the License.* You may obtain a copy of the License at**     http://www.apache.org/licenses/LICENSE-2.0** Unless required by applicable law or agreed to in writing, software* distributed under the License is distributed on an "AS IS" BASIS,* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.* See the License for the specific language governing permissions and* limitations under the License.* </p>*/package io.shardingsphere.core.metadata.table.executor;import com.google.common.base.Optional;
import io.shardingsphere.core.exception.ShardingException;
import io.shardingsphere.core.executor.ShardingExecuteEngine;
import io.shardingsphere.core.metadata.datasource.DataSourceMetaData;
import io.shardingsphere.core.metadata.datasource.ShardingDataSourceMetaData;
import io.shardingsphere.core.metadata.table.TableMetaData;
import io.shardingsphere.core.rule.ShardingRule;
import io.shardingsphere.core.rule.TableRule;import java.sql.Connection;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.Collection;
import java.util.HashMap;
import java.util.LinkedHashSet;
import java.util.Map;/*** Table meta data initializer.** @author zhangliang*/
public final class TableMetaDataInitializer {private final ShardingDataSourceMetaData shardingDataSourceMetaData;private final TableMetaDataConnectionManager connectionManager;private final TableMetaDataLoader tableMetaDataLoader;public TableMetaDataInitializer(final ShardingDataSourceMetaData shardingDataSourceMetaData, final ShardingExecuteEngine executeEngine,final TableMetaDataConnectionManager connectionManager, final int maxConnectionsSizePerQuery, final boolean isCheckingMetaData) {this.shardingDataSourceMetaData = shardingDataSourceMetaData;this.connectionManager = connectionManager;tableMetaDataLoader = new TableMetaDataLoader(shardingDataSourceMetaData, executeEngine, connectionManager, maxConnectionsSizePerQuery, isCheckingMetaData);}/*** Load all table meta data.** @param shardingRule sharding rule* @return all table meta data*/public Map<String, TableMetaData> load(final ShardingRule shardingRule) {Map<String, TableMetaData> result = new HashMap<>();try {// 加载需要水平切分的表元数据result.putAll(loadShardingTables(shardingRule));// 加载不需水平切分的表元数据，如果数据库中表数量很大，这里耗时很久...result.putAll(loadDefaultTables(shardingRule));} catch (final SQLException ex) {throw new ShardingException(ex);}return result;}private Map<String, TableMetaData> loadShardingTables(final ShardingRule shardingRule) throws SQLException {Map<String, TableMetaData> result = new HashMap<>(shardingRule.getTableRules().size(), 1);for (TableRule each : shardingRule.getTableRules()) {result.put(each.getLogicTable(), tableMetaDataLoader.load(each.getLogicTable(), shardingRule));}return result;}private Map<String, TableMetaData> loadDefaultTables(final ShardingRule shardingRule) throws SQLException {Map<String, TableMetaData> result = new HashMap<>(shardingRule.getTableRules().size(), 1);Optional<String> actualDefaultDataSourceName = shardingRule.findActualDefaultDataSourceName();if (actualDefaultDataSourceName.isPresent()) {for (String each : getAllTableNames(actualDefaultDataSourceName.get())) {result.put(each, tableMetaDataLoader.load(each, shardingRule));}}return result;}/*** 连接数据库，获取所有表元数据** @param dataSourceName 数据源名称* @return 所有数据表元数据列表* @throws SQLException*/private Collection<String> getAllTableNames(final String dataSourceName) throws SQLException {Collection<String> result = new LinkedHashSet<>();DataSourceMetaData dataSourceMetaData = shardingDataSourceMetaData.getActualDataSourceMetaData(dataSourceName);String catalog = null == dataSourceMetaData ? null : dataSourceMetaData.getSchemeName();try (Connection connection = connectionManager.getConnection(dataSourceName);ResultSet resultSet = connection.getMetaData().getTables(catalog, null, null, new String[]{"TABLE"})) {while (resultSet.next()) {String tableName = resultSet.getString("TABLE_NAME");if (!tableName.contains("$")) {result.add(tableName);}}}return result;}
}