数据库中间件Mycat源码解析:Mycat的SQL解析和路由

Posted 闲庭细步

tags:

篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了数据库中间件Mycat源码解析:Mycat的SQL解析和路由相关的知识,希望对你有一定的参考价值。

mycat对sql的解析分为两部分,一个是普通sql,另一个是PreparedStatment。

下面以解析普通sql为例分析(另一种方式大同小异),sql从客户端发过来后server接收后会调用FrontendCommandHandler的handle方法,这个方法会调用FrontendConnection的query方法,接着query方法会调用ServerQueryHandler的query方法,接着调用ServerConnection的execute方法。如下图所示:

public void execute(String sql, int type) {
		//连接状态检查
		if (this.isClosed()) {
			LOGGER.warn("ignore execute ,server connection is closed " + this);
			return;
		}
		// 事务状态检查
		if (txInterrupted) {
			writeErrMessage(ErrorCode.ER_YES,
					"Transaction error, need to rollback." + txInterrputMsg);
			return;
		}

		// 检查当前使用的DB
		String db = this.schema;
		boolean isDefault = true;
		if (db == null) {
			db = SchemaUtil.detectDefaultDb(sql, type);
			if (db == null) {
				writeErrMessage(ErrorCode.ERR_BAD_LOGICDB, "No MyCAT Database selected");
				return;
			}
			isDefault = false;
		}
		
		// 兼容phpAdmin's, 支持对mysql元数据的模拟返回
		//// TODO: 2016/5/20 支持更多information_schema特性
		if (ServerParse.SELECT == type 
				&& db.equalsIgnoreCase("information_schema") ) {
			MysqlInformationSchemaHandler.handle(sql, this);
			return;
		}

		if (ServerParse.SELECT == type 
				&& sql.contains("mysql") 
				&& sql.contains("proc")) {
			
			SchemaUtil.SchemaInfo schemaInfo = SchemaUtil.parseSchema(sql);
			if (schemaInfo != null 
					&& "mysql".equalsIgnoreCase(schemaInfo.schema)
					&& "proc".equalsIgnoreCase(schemaInfo.table)) {
				
				// 兼容MySQLWorkbench
				MysqlProcHandler.handle(sql, this);
				return;
			}
		}
		
		SchemaConfig schema = MycatServer.getInstance().getConfig().getSchemas().get(db);
		if (schema == null) {
			writeErrMessage(ErrorCode.ERR_BAD_LOGICDB,
					"Unknown MyCAT Database '" + db + "'");
			return;
		}

		//fix navicat   SELECT STATE AS `State`, ROUND(SUM(DURATION),7) AS `Duration`, CONCAT(ROUND(SUM(DURATION)/*100,3), '%') AS `Percentage` FROM INFORMATION_SCHEMA.PROFILING WHERE QUERY_ID= GROUP BY STATE ORDER BY SEQ
		if(ServerParse.SELECT == type &&sql.contains(" INFORMATION_SCHEMA.PROFILING ")&&sql.contains("CONCAT(ROUND(SUM(DURATION)/*100,3)"))
		{
			InformationSchemaProfiling.response(this);
			return;
		}
		
		/* 当已经设置默认schema时,可以通过在sql中指定其它schema的方式执行
		 * 相关sql,已经在mysql客户端中验证。
		 * 所以在此处增加关于sql中指定Schema方式的支持。
		 */
		if (isDefault && schema.isCheckSQLSchema() && isNormalSql(type)) {
			SchemaUtil.SchemaInfo schemaInfo = SchemaUtil.parseSchema(sql);
			if (schemaInfo != null && schemaInfo.schema != null && !schemaInfo.schema.equals(db)) {
				SchemaConfig schemaConfig = MycatServer.getInstance().getConfig().getSchemas().get(schemaInfo.schema);
				if (schemaConfig != null)
					schema = schemaConfig;
			}
		}

		routeEndExecuteSQL(sql, type, schema);

	}
最后有个routeEndExecuteSQL方法,它会首先调用RouteService的route方法先进行路由,然后调用HintSQLHandler的route方法,这个方法里调用RouteStrategy的route方法,这里使用了一个策略模式,包含下面几种sql类型,不同类型使用不同策略。
public final class ServerParse {

	public static final int OTHER = -1;
	public static final int BEGIN = 1;
	public static final int COMMIT = 2;
	public static final int DELETE = 3;
	public static final int INSERT = 4;
	public static final int REPLACE = 5;
	public static final int ROLLBACK = 6;
	public static final int SELECT = 7;
	public static final int SET = 8;
	public static final int SHOW = 9;
	public static final int START = 10;
	public static final int UPDATE = 11;
	public static final int KILL = 12;
	public static final int SAVEPOINT = 13;
	public static final int USE = 14;
	public static final int EXPLAIN = 15;
	public static final int EXPLAIN2 = 151;
	public static final int KILL_QUERY = 16;
	public static final int HELP = 17;
	public static final int MYSQL_CMD_COMMENT = 18;
	public static final int MYSQL_COMMENT = 19;
	public static final int CALL = 20;
	public static final int DESCRIBE = 21;
    public static final int LOAD_DATA_INFILE_SQL = 99;
    public static final int DDL = 100;

使用不同的路由方法是在routeNormalSqlWithAST中决定的,

public RouteResultset routeNormalSqlWithAST(SchemaConfig schema,
			String stmt, RouteResultset rrs, String charset,
			LayerCachePool cachePool) throws SQLNonTransientException {
		
		/**
		 *  只有mysql时只支持mysql语法
		 */
		SQLStatementParser parser = null;
		if (schema.isNeedSupportMultiDBType()) {
			parser = new MycatStatementParser(stmt);
		} else {
			parser = new MySqlStatementParser(stmt); 
		}

		MycatSchemaStatVisitor visitor = null;
		SQLStatement statement;
		
		/**
		 * 解析出现问题统一抛SQL语法错误
		 */
		try {
			statement = parser.parseStatement();
            visitor = new MycatSchemaStatVisitor();
		} catch (Exception t) {
	        LOGGER.error("DruidMycatRouteStrategyError", t);
			throw new SQLSyntaxErrorException(t);
		}

		/**
		 * 检验unsupported statement
		 */
		checkUnSupportedStatement(statement);


		DruidParser druidParser = DruidParserFactory.create(schema, statement, visitor);
		druidParser.parser(schema, rrs, statement, stmt,cachePool,visitor);

		/**
		 * DruidParser 解析过程中已完成了路由的直接返回
		 */
		if ( rrs.isFinishedRoute() ) {
			return rrs;
		}
		
		/**
		 * 没有from的select语句或其他
		 */
        DruidShardingParseInfo ctx=  druidParser.getCtx() ;
        if((ctx.getTables() == null || ctx.getTables().size() == 0)&&(ctx.getTableAliasMap()==null||ctx.getTableAliasMap().isEmpty()))
        {
		    return RouterUtil.routeToSingleNode(rrs, schema.getRandomDataNode(), druidParser.getCtx().getSql());
		}

		if(druidParser.getCtx().getRouteCalculateUnits().size() == 0) {
			RouteCalculateUnit routeCalculateUnit = new RouteCalculateUnit();
			druidParser.getCtx().addRouteCalculateUnit(routeCalculateUnit);
		}
		
		SortedSet<RouteResultsetNode> nodeSet = new TreeSet<RouteResultsetNode>();
		for(RouteCalculateUnit unit: druidParser.getCtx().getRouteCalculateUnits()) {
			RouteResultset rrsTmp = RouterUtil.tryRouteForTables(schema, druidParser.getCtx(), unit, rrs, isSelect(statement), cachePool);
			if(rrsTmp != null) {
				for(RouteResultsetNode node :rrsTmp.getNodes()) {
					nodeSet.add(node);
				}
			}
		}
		
		RouteResultsetNode[] nodes = new RouteResultsetNode[nodeSet.size()];
		int i = 0;
		for (Iterator<RouteResultsetNode> iterator = nodeSet.iterator(); iterator.hasNext();) {
			nodes[i] = iterator.next();
			i++;
		}		
		rrs.setNodes(nodes);		
		
		//分表
		/**
		 *  subTables="t_order$1-2,t_order3"
		 *目前分表 1.6 开始支持 幵丏 dataNode 在分表条件下只能配置一个,分表条件下不支持join。
		 */
		if(rrs.isDistTable()){
			return this.routeDisTable(statement,rrs);
		}
		
		return rrs;
	}
它使用druid做数据库连接池,支持分库分表,下面我们以多个表的分库分表路由策略为例子进行分析。

public static void findRouteWithcConditionsForTables(SchemaConfig schema, RouteResultset rrs,
			Map<String, Map<String, Set<ColumnRoutePair>>> tablesAndConditions,
			Map<String, Set<String>> tablesRouteMap, String sql, LayerCachePool cachePool, boolean isSelect)
			throws SQLNonTransientException {
		
		//为分库表找路由
		for(Map.Entry<String, Map<String, Set<ColumnRoutePair>>> entry : tablesAndConditions.entrySet()) {
			String tableName = entry.getKey().toUpperCase();
			TableConfig tableConfig = schema.getTables().get(tableName);
			if(tableConfig == null) {
				String msg = "can't find table define in schema "
						+ tableName + " schema:" + schema.getName();
				LOGGER.warn(msg);
				throw new SQLNonTransientException(msg);
			}
			if(tableConfig.getDistTables()!=null && tableConfig.getDistTables().size()>0){
				routeToDistTableNode(tableName,schema,rrs,sql, tablesAndConditions, cachePool,isSelect);
			}
			//全局表或者不分库的表略过(全局表后面再计算)
			if(tableConfig.isGlobalTable() || schema.getTables().get(tableName).getDataNodes().size() == 1) {
				continue;
			} else {//非全局表:分库表、childTable、其他
				Map<String, Set<ColumnRoutePair>> columnsMap = entry.getValue();
				String joinKey = tableConfig.getJoinKey();
				String partionCol = tableConfig.getPartitionColumn();
				String primaryKey = tableConfig.getPrimaryKey();
				boolean isFoundPartitionValue = partionCol != null && entry.getValue().get(partionCol) != null;
                boolean isLoadData=false;
                if (LOGGER.isDebugEnabled()
						&& sql.startsWith(LoadData.loadDataHint)||rrs.isLoadData()) {
                     //由于load data一次会计算很多路由数据,如果输出此日志会极大降低load data的性能
                         isLoadData=true;
                }
				if(entry.getValue().get(primaryKey) != null && entry.getValue().size() == 1&&!isLoadData)
                {//主键查找
					// try by primary key if found in cache
					Set<ColumnRoutePair> primaryKeyPairs = entry.getValue().get(primaryKey);
					if (primaryKeyPairs != null) {
						if (LOGGER.isDebugEnabled()) {
                                 LOGGER.debug("try to find cache by primary key ");
						}
						String tableKey = schema.getName() + '_' + tableName;
						boolean allFound = true;
						for (ColumnRoutePair pair : primaryKeyPairs) {//可能id in(1,2,3)多主键
							String cacheKey = pair.colValue;
							String dataNode = (String) cachePool.get(tableKey, cacheKey);
							if (dataNode == null) {
								allFound = false;
								continue;
							} else {
								if(tablesRouteMap.get(tableName) == null) {
									tablesRouteMap.put(tableName, new HashSet<String>());
								}
								tablesRouteMap.get(tableName).add(dataNode);
								continue;
							}
						}
						if (!allFound) {
							// need cache primary key ->datanode relation
							if (isSelect && tableConfig.getPrimaryKey() != null) {
								rrs.setPrimaryKey(tableKey + '.' + tableConfig.getPrimaryKey());
							}
						} else {//主键缓存中找到了就执行循环的下一轮
							continue;
						}
					}
				}
				if (isFoundPartitionValue) {//分库表
					Set<ColumnRoutePair> partitionValue = columnsMap.get(partionCol);
					if(partitionValue == null || partitionValue.size() == 0) {
						if(tablesRouteMap.get(tableName) == null) {
							tablesRouteMap.put(tableName, new HashSet<String>());
						}
						tablesRouteMap.get(tableName).addAll(tableConfig.getDataNodes());
					} else {
						for(ColumnRoutePair pair : partitionValue) {
							if(pair.colValue != null) {
								Integer nodeIndex = tableConfig.getRule().getRuleAlgorithm().calculate(pair.colValue);
								if(nodeIndex == null) {
									String msg = "can't find any valid datanode :" + tableConfig.getName()
											+ " -> " + tableConfig.getPartitionColumn() + " -> " + pair.colValue;
									LOGGER.warn(msg);
									throw new SQLNonTransientException(msg);
								}

								ArrayList<String> dataNodes = tableConfig.getDataNodes();
								String node;
								if (nodeIndex >=0 && nodeIndex < dataNodes.size()) {
									node = dataNodes.get(nodeIndex);
								} else {
									node = null;
									String msg = "Can't find a valid data node for specified node index :"
											+ tableConfig.getName() + " -> " + tableConfig.getPartitionColumn()
											+ " -> " + pair.colValue + " -> " + "Index : " + nodeIndex;
									LOGGER.warn(msg);
									throw new SQLNonTransientException(msg);
								}
								if(node != null) {
									if(tablesRouteMap.get(tableName) == null) {
										tablesRouteMap.put(tableName, new HashSet<String>());
									}
									tablesRouteMap.get(tableName).add(node);
								}
							}
							if(pair.rangeValue != null) {
								Integer[] nodeIndexs = tableConfig.getRule().getRuleAlgorithm()
										.calculateRange(pair.rangeValue.beginValue.toString(), pair.rangeValue.endValue.toString());
								ArrayList<String> dataNodes = tableConfig.getDataNodes();
								String node;
								for(Integer idx : nodeIndexs) {
									if (idx >= 0 && idx < dataNodes.size()) {
										node = dataNodes.get(idx);
									} else {
										String msg = "Can't find valid data node(s) for some of specified node indexes :"
												+ tableConfig.getName() + " -> " + tableConfig.getPartitionColumn();
										LOGGER.warn(msg);
										throw new SQLNonTransientException(msg);
									}
									if(node != null) {
										if(tablesRouteMap.get(tableName) == null) {
											tablesRouteMap.put(tableName, new HashSet<String>());
										}
										tablesRouteMap.get(tableName).add(node);

									}
								}
							}
						}
					}
				} else if(joinKey != null && columnsMap.get(joinKey) != null && columnsMap.get(joinKey).size() != 0) {//childTable  (如果是select 语句的父子表join)之前要找到root table,将childTable移除,只留下root table
					Set<ColumnRoutePair> joinKeyValue = columnsMap.get(joinKey);
					
					Set<String> dataNodeSet = ruleByJoinValueCalculate(rrs, tableConfig, joinKeyValue);

					if (dataNodeSet.isEmpty()) {
						throw new SQLNonTransientException(
								"parent key can't find any valid datanode ");
					}
					if (LOGGER.isDebugEnabled()) {
						LOGGER.debug("found partion nodes (using parent partion rule directly) for child table to update  "
								+ Arrays.toString(dataNodeSet.toArray()) + " sql :" + sql);
					}
					if (dataNodeSet.size() > 1) {
						routeToMultiNode(rrs.isCacheAble(), rrs, dataNodeSet, sql);
						rrs.setFinishedRoute(true);
						return;
					} else {
						rrs.setCacheAble(true);
						routeToSingleNode(rrs, dataNodeSet.iterator().next(), sql);
						return;
					}

				} else {
					//没找到拆分字段,该表的所有节点都路由
					if(tablesRouteMap.get(tableName) == null) {
						tablesRouteMap.put(tableName, new HashSet<String>());
					}
					tablesRouteMap.get(tableName).addAll(tableConfig.getDataNodes());
				}
			}
		}
	}
mycat会先找主键(支持多主键),根据主键去找不同的node节点,然后在不同的node分别执行sql,这样它就获取了sql的路由表,所谓的路由表就是查找表存在于哪些节点中。这个如果是在依据主键分库分表(同时存在多种分片类型如下图所示)的情况下主要通过分析sql中的存在的表名和主键的键值在schema配置中通过算法(RuleAlgorithm)查找的(如果没有主键范围就路由到所有节点),找到节点后,才具体去执行sql。

PartitionByDate
PartitionByFileMap
PartitionByHashMod
PartitionByHotDate
PartitionByJumpConsistentHash
PartitionByLong
PartitionByMod
PartitionByMonth
PartitionByMurmurHash
PartitionByPattern
PartitionByPrefixPattern
PartitionByRangeDateHash
PartitionByRangeMod
PartitionByString
PartitionDirectBySubString

在上面提到的routeEndExecuteSQL方法中找到路由节点后它会调用NonBlockingSession的execute方法,它分为单节点模式和多节点模式,下面以多节点模式为例,在这种情况下它会调用MultiNodeQueryHandler的execute方法。

public void execute() throws Exception {
		final ReentrantLock lock = this.lock;
		lock.lock();
		try {
			this.reset(rrs.getNodes().length);
			this.fieldsReturned = false;
			this.affectedRows = 0L;
			this.insertId = 0L;
		} finally {
			lock.unlock();
		}
		MycatConfig conf = MycatServer.getInstance().getConfig();
		startTime = System.currentTimeMillis();
		LOGGER.debug("rrs.getRunOnSlave()-" + rrs.getRunOnSlave());
		for (final RouteResultsetNode node : rrs.getNodes()) {
			BackendConnection conn = session.getTarget(node);
			if (session.tryExistsCon(conn, node)) {
				LOGGER.debug("node.getRunOnSlave()-" + node.getRunOnSlave());
				node.setRunOnSlave(rrs.getRunOnSlave());	// 实现 master/slave注解
				LOGGER.debug("node.getRunOnSlave()-" + node.getRunOnSlave());
				_execute(conn, node);
			} else {
				// create new connection
				LOGGER.debug("node.getRunOnSlave()1-" + node.getRunOnSlave());
				node.setRunOnSlave(rrs.getRunOnSlave());	// 实现 master/slave注解
				LOGGER.debug("node.getRunOnSlave()2-" + node.getRunOnSlave());
				PhysicalDBNode dn = conf.getDataNodes().get(node.getName());
				dn.getConnection(dn.getDatabase(), autocommit, node, this, node);
				// 注意该方法不仅仅是获取连接,获取新连接成功之后,会通过层层回调,最后回调到本类 的connectionAcquired
				// 这是通过 上面方法的 this 参数的层层传递完成的。
				// connectionAcquired 进行执行操作:
				// session.bindConnection(node, conn);
				// _execute(conn, node);
			}

		}
	}

到此优化后的sql被发给路由结果中的各个节点执行。



以上是关于数据库中间件Mycat源码解析:Mycat的SQL解析和路由的主要内容,如果未能解决你的问题,请参考以下文章

MyCat源码分析系列之——SQL下发

数据库中间件 MyCAT 源码分析 —— 调试环境搭建

MyCAT 源码解析合集

MyCAT 源码解析 —— 分片结果合并(使用unsaferow)

MySQL:Mycat实现读写分离Season2:其二

数据库中间件 MyCAT 源码分析 —— 调试环境搭建