背景

本文基于 StarRocks 3.1.7
主要是分析以下两种超时设置的方式:

• SESSION 级别

    SET query_timeout = 10;SELECT sleep(20);

• SQL 级别

  select /*+ SET_VAR(query_timeout=10) */ sleep(20); 

通过本文的分析大致可以了解到在Starrocks的FE端是如何进行Command的交互以及数据流走向，其他的命令也是可以举一反三

分析

query_timeout 命令解析

和Spark以及hive等但是解析一样，StarRocks也是采用的Anltr4进行语法的解析，
对于StarRocks来说， 对应的语法解析文件为 StarRocks.g4文件，那么其set query_time在如下的位置

setStatement: SET setVar (',' setVar)*;setVar: (CHAR SET | CHARSET | CHARACTER SET) (identifierOrString | DEFAULT)                       #setNames| NAMES (charset = identifierOrString | DEFAULT)(COLLATE (collate = identifierOrString | DEFAULT))?                                     #setNames| PASSWORD '=' (string | PASSWORD '(' string ')')                                           #setPassword| PASSWORD FOR user '=' (string | PASSWORD '(' string ')')                                  #setPassword| userVariable '=' expression                                                               #setUserVar| varType? identifier '=' setExprOrDefault                                                  #setSystemVar| systemVariable '=' setExprOrDefault                                                       #setSystemVar| varType? TRANSACTION transaction_characteristics                                          #setTransaction;

继而可以找到对应的语法解析部分为 AstBuilder.java 中

 @Overridepublic ParseNode visitSetSystemVar(StarRocksParser.SetSystemVarContext context) {NodePosition pos = createPos(context);if (context.systemVariable() != null) {VariableExpr variableDesc = (VariableExpr) visit(context.systemVariable());Expr expr = (Expr) visit(context.setExprOrDefault());return new SystemVariable(variableDesc.getSetType(), variableDesc.getName(), expr, pos);} else {Expr expr = (Expr) visit(context.setExprOrDefault());String variable = ((Identifier) visit(context.identifier())).getValue();if (context.varType() != null) {return new SystemVariable(getVariableType(context.varType()), variable, expr, pos);} else {return new SystemVariable(SetType.SESSION, variable, expr, pos);}}}

从以上所示，SET query_timeout = 10; 就会在语法层面解析为 new SystemVariable(SetType.SESSION, variable, expr, pos)

数据流向

以上只是说到了 SET query_timeout = 10 只会被解析为SystemVariable对应的java数据结构，但是一条SQL从客户端发送过来，是怎么一个数据流呢？
我们大概的捋一下：

StarRocksFE中新建QeService对象||\/new NMysqlServer(port, scheduler, sslContext)||\/new AcceptListener(connectScheduler, sslContext)||\/AcceptListener.handleEvent||\/context.startAcceptQuery(processor)||\/NMysqlChannel.startAcceptQuery||\/conn.getSourceChannel().setReadListener(new ReadListener(nConnectContext, connectProcessor))||\/ReadListener.handleEvent||\/connectProcessor.processOnce()||\/connectProcessor.dispatch||\/connectProcessor.handleQuery||\/stmts = com.starrocks.sql.parser.SqlParser.parse(originStmt, ctx.getSessionVariable());||\/StmtExecutor.execute()||\/StatementPlanner.plan(parsedStmt, context)||\/StmtExecutor.handleSetStmt()||\/SetExecutor.execute // 会设置到变量的keyValue到`ConnectContext`的`SystemVariable`变量中，后续会或获取对应的值

query_timeout 怎么生效

还是定位到StarRocksFE.java中：

ExecuteEnv.setup();

该方法是整个执行环境的基础设置。其中会有ConnectScheduler的初始化：

public ConnectScheduler(int maxConnections) {this.maxConnections = new AtomicInteger(maxConnections);numberConnection = new AtomicInteger(0);nextConnectionId = new AtomicInteger(0);// Use a thread to check whether connection is timeout. Because// 1. If use a scheduler, the task maybe a huge number when query is messy.//    Let timeout is 10m, and 5000 qps, then there are up to 3000000 tasks in scheduler.// 2. Use a thread to poll maybe lose some accurate, but is enough to us.ScheduledExecutorService checkTimer = ThreadPoolManager.newDaemonScheduledThreadPool(1,"Connect-Scheduler-Check-Timer", true);checkTimer.scheduleAtFixedRate(new TimeoutChecker(), 0, 1000L, TimeUnit.MILLISECONDS);}

这里有个定时线程池去进行timeout的检查，间隔是一秒。具体的检查机制在TimeoutChecker类中：

private class TimeoutChecker extends TimerTask {@Overridepublic void run() {try {long now = System.currentTimeMillis();synchronized (ConnectScheduler.this) {//Because unregisterConnection will be callback in NMysqlChannel's close,//unregisterConnection will remove connectionMap (in the same thread)//This will result in a concurrentModifyException.//So here we copied the connectionIds to avoid removing iterator during operate iteratorArrayList<Long> connectionIds = new ArrayList<>(connectionMap.keySet());for (Long connectId : connectionIds) {ConnectContext connectContext = connectionMap.get(connectId);connectContext.checkTimeout(now);}}} catch (Throwable e) {//Catch Exception to avoid thread exitLOG.warn("Timeout checker exception, Internal error : " + e.getMessage());}}}

主要逻辑就是从connectionMap中获取对应的ConnectContext,从而调用ConnectContext.checkTimeout方法检查是否超时。
checkTimeout方法主要是通过sessionVariable.getQueryTimeoutS()获取设置的超时时间，如果超时，则调用StmtExecutor.cancel,继而调用Coordinator.cancel
所以现在就存在一个问题： 当前连接的ConnectContext什么时候被集成到 connectionMap中去的？
还是回到流程 AcceptListener.handleEvent 中去：

    connectScheduler.submit(context);...if (connectScheduler.registerConnection(context)) {MysqlProto.sendResponsePacket(context);connection.setCloseListener(streamConnection -> connectScheduler.unregisterConnection(context));} else {...

这里的submit 方法会生成context的conectionId.
registerConnection方法会把当前 ConnectionContext 的id和 ConnectionContext 组成KeyValue对并放置到connectionMap中

至此 SET query_timeout = 10 整体的数据流就结束了，待在同一个连接中进行select 操作的时候，就会根据执行的长短进行超时处理了。

注意：
对于 select /*+ SET_VAR(query_timeout=10) */ sleep(20); 这种情况的解析，是通过 HintCollector来解析的。
词法解析是在StarRocksLex.g4 中，

OPTIMIZER_HINT: '/*+' .*? '*/' -> channel(2);

对于获取hint是通过HintCollector的extractHintToRight获取的：

 private void extractHintToRight(ParserRuleContext ctx) {Token semi = ctx.start;int i = semi.getTokenIndex();List<Token> hintTokens = tokenStream.getHiddenTokensToRight(i, HINT_CHANNEL);if (hintTokens != null) {contextWithTokenMap.computeIfAbsent(ctx, e -> new ArrayList<>()).addAll(hintTokens);}}

对应的解析在：SqlParser.parseWithStarRocksDialect 方法中:

  HintCollector collector = new HintCollector((CommonTokenStream) parser.getTokenStream());collector.collect(singleStatementContexts.get(idx));AstBuilder astBuilder = new AstBuilder(sessionVariable.getSqlMode(), collector.getContextWithHintMap());

AstBuilder 中会存储 hint到 hintMap 变量中，而在 visitQuerySpecification方法中

        selectList.setOptHints(extractVarHints(hintMap.get(context)));

从而在StmtExecutor.execute中会调用 optHints = selectRelation.getSelectList().getOptHints();获取对应的hint，

 if (isQuery &&((QueryStatement) parsedStmt).getQueryRelation() instanceof SelectRelation) {SelectRelation selectRelation = (SelectRelation) ((QueryStatement) parsedStmt).getQueryRelation();optHints = selectRelation.getSelectList().getOptHints();}if (optHints != null) {LOG.error("optHints: parsedStmt:" + parsedStmt.getOrigStmt() +"  "+ optHints.size());});SessionVariable sessionVariable = (SessionVariable) sessionVariableBackup.clone();for (String key : optHints.keySet()) {VariableMgr.setSystemVariable(sessionVariable,new SystemVariable(key, new StringLiteral(optHints.get(key))), true);}context.setSessionVariable(sessionVariable);

这样 hint相关的变量就设置到ConnectContext的SessionVariable中了，后续的流程和之前的一致,只不过在StatExecutor执行的最后会把time_out给复原:

    SessionVariable sessionVariableBackup = context.getSessionVariable();...SessionVariable sessionVariable = (SessionVariable) sessionVariableBackup.clone();for (String key : optHints.keySet()) {VariableMgr.setSystemVariable(sessionVariable,new SystemVariable(key, new StringLiteral(optHints.get(key))), true);}context.setSessionVariable(sessionVariable);...context.setSessionVariable(sessionVariableBackup);