Shading - jdbc 源码分析(四) - sql 路由

上一篇文章我们分析了sharding-jdbc 解析 select 语句（sql 解析之 Select），今天我们分析下 sql 路由。

声明：本文基于1.5.M1版本

时序图：

执行逻辑

下面我们以上篇文章的Select语句分析：

SELECT o.order_id FROM order o WHERE o.order_id = 4

在分析之前首先看下分库分表的配置：

Map<String, DataSource> dataSourceMap = new HashMap<>();
        dataSourceMap.put("ds_0", null);
        dataSourceMap.put("ds_1", null);
        DataSourceRule dataSourceRule = new DataSourceRule(dataSourceMap);
        TableRule orderTableRule = TableRule.builder("order").actualTables(Lists.newArrayList("order_0", "order_1")).dataSourceRule(dataSourceRule).build();
        TableRule orderItemTableRule = TableRule.builder("order_item").actualTables(Lists.newArrayList("order_item_0", "order_item_1")).dataSourceRule(dataSourceRule).build();
        TableRule orderAttrTableRule = TableRule.builder("order_attr").actualTables(Lists.newArrayList("ds_0.order_attr_a", "ds_1.order_attr_b")).dataSourceRule(dataSourceRule)
                .tableShardingStrategy(new TableShardingStrategy("order_id", new OrderAttrShardingAlgorithm())).build();
        shardingRule = ShardingRule.builder().dataSourceRule(dataSourceRule).tableRules(Lists.newArrayList(orderTableRule, orderItemTableRule, orderAttrTableRule))
                .bindingTableRules(Collections.singletonList(new BindingTableRule(Arrays.asList(orderTableRule, orderItemTableRule))))
                .databaseShardingStrategy(new DatabaseShardingStrategy("order_id", new OrderShardingAlgorithm()))
                .tableShardingStrategy(new TableShardingStrategy("order_id", new OrderShardingAlgorithm())).build();
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order表分了2个库，2个表，以order_id为分片键

1、StatementRoutingEngine 路由入口：

• 构造方法：通过ShardingContext（分片上下文）创建SQLRouter
• SQLRouter 解析SQL（内部调用上一片文章的SQLParsingEngine），并路由

public StatementRoutingEngine(final ShardingContext shardingContext) {
        sqlRouter = SQLRouterFactory.createSQLRouter(shardingContext);
    }
    
    /**
     * SQL路由.
     *
     * @param logicSQL 逻辑SQL
     * @return 路由结果
     */
    public SQLRouteResult route(final String logicSQL) {
        SQLStatement sqlStatement = sqlRouter.parse(logicSQL, 0);
        return sqlRouter.route(logicSQL, Collections.emptyList(), sqlStatement);
    }
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这里判断是否只分库，若只分库，则new UnparsingSQLRouter，不需要走SQL解析的逻辑（直接落到具体的库，执行SQL即可），否则new ParsingSQLRouter

/**
     * 创建SQL路由器.
     * 
     * @param shardingContext 数据源运行期上下文
     * @return SQL路由器
     */
    public static SQLRouter createSQLRouter(final ShardingContext shardingContext) {
        return HintManagerHolder.isDatabaseShardingOnly() ? new UnparsingSQLRouter(shardingContext) : new ParsingSQLRouter(shardingContext);
    }
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2、ParsingSQLRouter#route：

public SQLRouteResult route(final String logicSQL, final List<Object> parameters, final SQLStatement sqlStatement) {
        final Context context = MetricsContext.start("Route SQL");
        SQLRouteResult result = new SQLRouteResult(sqlStatement);
        if (sqlStatement instanceof InsertStatement && null != ((InsertStatement) sqlStatement).getGeneratedKey()) {
        //insert 语句处理主键（有空分析分析）
            processGeneratedKey(parameters, (InsertStatement) sqlStatement, result);
        }
        //路由
        RoutingResult routingResult = route(parameters, sqlStatement);
       ...(后面是重写的逻辑，先省略)
        MetricsContext.stop(context);
        logSQLRouteResult(result, parameters);
        return result;
    }
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2-1、根据sqlStatement解析的表对象获取逻辑表

若单表，走SimpleRoutingEngine#route，否则走ComplexRoutingEngine#route

private RoutingResult route(final List<Object> parameters, final SQLStatement sqlStatement) {
        Collection<String> tableNames = sqlStatement.getTables().getTableNames();
        RoutingEngine routingEngine;
        if (1 == tableNames.size() || shardingRule.isAllBindingTables(tableNames)) {
            routingEngine = new SimpleRoutingEngine(shardingRule, parameters, tableNames.iterator().next(), sqlStatement);
        } else {
            // TODO 可配置是否执行笛卡尔积
            routingEngine = new ComplexRoutingEngine(shardingRule, parameters, tableNames, sqlStatement);
        }
        return routingEngine.route();
    }
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2-2、SimpleRoutingEngine#route

正常情况下都是单表，我们就以单表的情况分析

1. 根据逻辑表名词获取我们配置的TableRule
2. 根据TableRule获取真实的db、table
3. 组装RoutingResult

public RoutingResult route() {
        TableRule tableRule = shardingRule.getTableRule(logicTableName);
        Collection<String> routedDataSources = routeDataSources(tableRule);
        Collection<String> routedTables = routeTables(tableRule, routedDataSources);
        return generateRoutingResult(tableRule, routedDataSources, routedTables);
    }
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• getTableRule： 首先根据逻辑表查找，找到了就直接返回，没找到的话判断我们的默认数据库是不是存在，然后用默认数据库帮我们创建一个无需分库分表的TableRule

/**
     * 根据逻辑表名称查找分片规则.
     *
     * @param logicTableName 逻辑表名称
     * @return 该逻辑表的分片规则
     */
    public TableRule getTableRule(final String logicTableName) {
        Optional<TableRule> tableRule = tryFindTableRule(logicTableName);
        if (tableRule.isPresent()) {
            return tableRule.get();
        }
        if (dataSourceRule.getDefaultDataSource().isPresent()) {
            return createTableRuleWithDefaultDataSource(logicTableName, dataSourceRule);
        }
        throw new ShardingJdbcException("Cannot find table rule and default data source with logic table: '%s'", logicTableName);
    }
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private TableRule createTableRuleWithDefaultDataSource(final String logicTableName, final DataSourceRule defaultDataSourceRule) {
        Map<String, DataSource> defaultDataSourceMap = new HashMap<>(1);
        defaultDataSourceMap.put(defaultDataSourceRule.getDefaultDataSourceName(), defaultDataSourceRule.getDefaultDataSource().get());
        return TableRule.builder(logicTableName)
                .dataSourceRule(new DataSourceRule(defaultDataSourceMap))
                .databaseShardingStrategy(new DatabaseShardingStrategy("", new NoneDatabaseShardingAlgorithm()))
                .tableShardingStrategy(new TableShardingStrategy("", new NoneTableShardingAlgorithm())).build();
    }
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• routeDataSources：(注释就写在代码里了)

private Collection<String> routeDataSources(final TableRule tableRule) {
        1、根据TableRule 获取数据库分片策略
        DatabaseShardingStrategy strategy = shardingRule.getDatabaseShardingStrategy(tableRule);
        2、判断有没有用强制路由，有的话直接用强制路由的value，没有的话就用我们查询条件里面用到的分片value
        List<ShardingValue<?>> shardingValues = HintManagerHolder.isUseShardingHint() ? getDatabaseShardingValuesFromHint(strategy.getShardingColumns())
                : getShardingValues(strategy.getShardingColumns());
        logBeforeRoute("database", logicTableName, tableRule.getActualDatasourceNames(), strategy.getShardingColumns(), shardingValues);
        3、调用分片策略计算分片值
        Collection<String> result = strategy.doStaticSharding(sqlStatement.getType(), tableRule.getActualDatasourceNames(), shardingValues);
        logAfterRoute("database", logicTableName, result);
        Preconditions.checkState(!result.isEmpty(), "no database route info");
        return result;
    }
    
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• routeTables（没区别嘛）

private Collection<String> routeTables(final TableRule tableRule, final Collection<String> routedDataSources) {
        TableShardingStrategy strategy = shardingRule.getTableShardingStrategy(tableRule);
        List<ShardingValue<?>> shardingValues = HintManagerHolder.isUseShardingHint() ? getTableShardingValuesFromHint(strategy.getShardingColumns())
                : getShardingValues(strategy.getShardingColumns());
        logBeforeRoute("table", logicTableName, tableRule.getActualTables(), strategy.getShardingColumns(), shardingValues);
        Collection<String> result = tableRule.isDynamic() ? strategy.doDynamicSharding(shardingValues)
                : strategy.doStaticSharding(sqlStatement.getType(), tableRule.getActualTableNames(routedDataSources), shardingValues);
        logAfterRoute("table", logicTableName, result);
        Preconditions.checkState(!result.isEmpty(), "no table route info");
        return result;
    }
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强制路由的感觉可以单独写一篇文章说，所以就不分析了，以后写，我们看不走强制路由的逻辑。

• getShardingValues

private List<ShardingValue<?>> getShardingValues(final Collection<String> shardingColumns) {
        List<ShardingValue<?>> result = new ArrayList<>(shardingColumns.size());
        for (String each : shardingColumns) {
          //SQL解析的getConditions对象（上一篇文章简单分析过），这里查找分片列是否存在，存在就转换为ShardingValue
            Optional<Condition> condition = sqlStatement.getConditions().find(new Column(each, logicTableName));
            if (condition.isPresent()) {
                result.add(condition.get().getShardingValue(parameters));
            }
        }
        return result;
    }
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• getShardingValue

operator：这个可以理解为条件对象的操作符号（=、in、between）

/**
     * 将条件对象转换为分片值.
     *
     * @param parameters 参数列表
     * @return 分片值
     */
    public ShardingValue<?> getShardingValue(final List<Object> parameters) {
        List<Comparable<?>> conditionValues = getValues(parameters);
        switch (operator) {
            case EQUAL:
                return new ShardingValue<Comparable<?>>(column.getTableName(), column.getName(), conditionValues.get(0));
            case IN:
                return new ShardingValue<>(column.getTableName(), column.getName(), conditionValues);
            case BETWEEN:
                return new ShardingValue<>(column.getTableName(), column.getName(), Range.range(conditionValues.get(0), BoundType.CLOSED, conditionValues.get(1), BoundType.CLOSED));
            default:
                throw new UnsupportedOperationException(operator.getExpression());
        }
    }
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• getValues

positionValueMap:存放条件值（分片Value），positionIndexMap：这段逻辑似乎没太看懂。。

private List<Comparable<?>> getValues(final List<Object> parameters) {
        List<Comparable<?>> result = new LinkedList<>(positionValueMap.values());
        for (Entry<Integer, Integer> entry : positionIndexMap.entrySet()) {
            Object parameter = parameters.get(entry.getValue());
            if (!(parameter instanceof Comparable<?>)) {
                throw new ShardingJdbcException("Parameter `%s` should extends Comparable for sharding value.", parameter);
            }
            if (entry.getKey() < result.size()) {
                result.add(entry.getKey(), (Comparable<?>) parameter);
            } else {
                result.add((Comparable<?>) parameter);
            }
        }
        return result;
    }
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• ShardingStrategy#doStaticSharding：

/**
     * 计算静态分片.
     *
     * @param sqlType SQL语句的类型
     * @param availableTargetNames 所有的可用分片资源集合
     * @param shardingValues 分片值集合
     * @return 分库后指向的数据源名称集合
     */
    public Collection<String> doStaticSharding(final SQLType sqlType, final Collection<String> availableTargetNames, final Collection<ShardingValue<?>> shardingValues) {
        Collection<String> result = new TreeSet<>(String.CASE_INSENSITIVE_ORDER);
        if (shardingValues.isEmpty()) {
            Preconditions.checkState(!isInsertMultiple(sqlType, availableTargetNames), "INSERT statement should contain sharding value.");
            result.addAll(availableTargetNames);
        } else {
            result.addAll(doSharding(shardingValues, availableTargetNames));
        }
        return result;
    }
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一般我们的表实现 SingleKeyShardingAlgorithm 类，定义我们自己的分片逻辑，返回计算出来的结果值

private Collection<String> doSharding(final Collection<ShardingValue<?>> shardingValues, final Collection<String> availableTargetNames) {
        if (shardingAlgorithm instanceof NoneKeyShardingAlgorithm) {
            return Collections.singletonList(((NoneKeyShardingAlgorithm) shardingAlgorithm).doSharding(availableTargetNames, shardingValues.iterator().next()));
        }
        if (shardingAlgorithm instanceof SingleKeyShardingAlgorithm) {
            SingleKeyShardingAlgorithm<?> singleKeyShardingAlgorithm = (SingleKeyShardingAlgorithm<?>) shardingAlgorithm;
            ShardingValue shardingValue = shardingValues.iterator().next();
            switch (shardingValue.getType()) {
                case SINGLE:
                    return Collections.singletonList(singleKeyShardingAlgorithm.doEqualSharding(availableTargetNames, shardingValue));
                case LIST:
                    return singleKeyShardingAlgorithm.doInSharding(availableTargetNames, shardingValue);
                case RANGE:
                    return singleKeyShardingAlgorithm.doBetweenSharding(availableTargetNames, shardingValue);
                default:
                    throw new UnsupportedOperationException(shardingValue.getType().getClass().getName());
            }
        }
        if (shardingAlgorithm instanceof MultipleKeysShardingAlgorithm) {
            return ((MultipleKeysShardingAlgorithm) shardingAlgorithm).doSharding(availableTargetNames, shardingValues);
        }
        throw new UnsupportedOperationException(shardingAlgorithm.getClass().getName());
    }
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• 最后

过滤获取真实的DataNode，组装RoutingResult

private RoutingResult generateRoutingResult(final TableRule tableRule, final Collection<String> routedDataSources, final Collection<String> routedTables) {
        RoutingResult result = new RoutingResult();
        for (DataNode each : tableRule.getActualDataNodes(routedDataSources, routedTables)) {
            result.getTableUnits().getTableUnits().add(new TableUnit(each.getDataSourceName(), logicTableName, each.getTableName()));
        }
        return result;
    }
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