[转]JStorm之Supervisor简介

一、简介

Supervisor是JStorm中的工作节点，类似于MR的TT，subscribe zookeeper的任务调度结果数据，根据任务调度情况启动/停止工作进程Worker。同时Supervisor需要定期向zookeeper写入活跃端口信息以便Nimbus监控。Supervisor不执行具体处理工作，所有的计算任务都交Worker完成。从整个架构上看，Supervisor处在整个JStorm三级管理架构的中间环节，辅助管理任务调度和资源管理工作。

二、架构

1.Supervisor

Supervisor单节点架构如上图所示，初始化时启动进程Supervisor，根据Nimbus分配的任务情况触发启动/停用Worker JVM进程，其中每个Worker进程启动一个或多个Task线程，其中Task须同属单个Topology。从整个Supervisor节点来看运行多个JVM进程，包括一个Supervisor进程和一个或多个Worker进程。
不同角色状态通过不同的方式维护。其中Task通过hb直接将包括时间信息和当前Task的统计信息写到zookeeper；Worker定期将包括Topology id，端口，Task id集合及当前时间写入本地；Supervisor定期将包括时间及节点资源（端口集合）写到zookeeper，同时从zookeeper读取任务调度结果，根据结果启动/停用Worker进程。

2.Worker

在Worker JVM进程内部，除了相互独立的Task线程外，Task线程会共享数据收发和节点之间连接管理等Worker进程内的公共资源，如图所示。其中：
VirtualPort：数据接收线程；
KeyoTupleSerialize：Tuple数据序列化；
TransferQueue：数据发送管道；
DrainerRunnable：数据发送线程；
RefreshConnections：节点之间连接管理线程。

三、实现与代码剖析

1.Supervisor

在jstorm-0.7.1中，Supervisor daemon实现在jstorm-server/src/main/java目录下com.alipay.dw.jstorm.daemon.supervisor包里。Supervisor.java是Supervisor daemon的入口，Supervisor进程主要做以下几件事情。

初始化

1、清理本地临时目录下数据$jstorm-local-dir/supervisor/tmp；
2、创建zk操作实例；
3、本地新建状态文件，$jstorm-local-dir/supervisor/localstate；
4、生成supervisor-id并写入localstate，其中key=”supervisor-id”；如果supervisor重启，先检查supervisor-id是否已经存在，若存在直接读取即可；
5、初始化并启动Heartbeat线程；
6、初始化并启动SyncProcessEvent线程；
7、初始化并启动SyncProcessEvent线程；
8、注册主进程退出数据清理Hook in SupervisorManger。

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@SuppressWarnings("rawtypes") public SupervisorManger mkSupervisor(Map conf, MQContext sharedContext) throws Exception { LOG.info("Starting Supervisor with conf " + conf); active = new AtomicBoolean(true); /* * Step 1: cleanup all files in /storm-local-dir/supervisor/tmp */ String path = StormConfig.supervisorTmpDir(conf); FileUtils.cleanDirectory(new File(path)); /* * Step 2: create ZK operation instance * StromClusterState */ StormClusterState stormClusterState = Cluster .mk_storm_cluster_state(conf); /* * Step 3, create LocalStat * LocalStat is one KV database * 4.1 create LocalState instance * 4.2 get supervisorId, if no supervisorId, create one */ LocalState localState = StormConfig.supervisorState(conf); String supervisorId = (String) localState.get(Common.LS_ID); if (supervisorId == null) { supervisorId = UUID.randomUUID().toString(); localState.put(Common.LS_ID, supervisorId); } Vector threads = new Vector(); // Step 5 create HeartBeat // every supervisor.heartbeat.frequency.secs, write SupervisorInfo to ZK String myHostName = NetWorkUtils.hostname(); int startTimeStamp = TimeUtils.current_time_secs(); Heartbeat hb = new Heartbeat(conf, stormClusterState, supervisorId, myHostName, startTimeStamp, active); hb.update(); AsyncLoopThread heartbeat = new AsyncLoopThread(hb, false, null, Thread.MIN_PRIORITY, true); threads.add(heartbeat); // Step 6 create and start sync Supervisor thread // every supervisor.monitor.frequency.secs second run SyncSupervisor EventManager processEventManager = new EventManagerImp(false); ConcurrentHashMap workerThreadPids = new ConcurrentHashMap(); //读取$jstorm-local-dir/supervior/localstate中key=local-assignments的value值，根据该值执行workers的kill/start SyncProcessEvent syncProcessEvent = new SyncProcessEvent(supervisorId, conf, localState, workerThreadPids, sharedContext); EventManager syncSupEventManager = new EventManagerImp(false); //通过比较$zkroot/assignments/{topologyid}全量数据和本地STORM-LOCAL-DIR/supervisor/stormdist/{topologyid}: //1.从nimbus下载有任务分配到本节点的topology的jar和配置数据 //2.从本地删除已经失效的topology的jar和配置数据 SyncSupervisorEvent syncSupervisorEvent = new SyncSupervisorEvent( supervisorId, conf, processEventManager, syncSupEventManager, stormClusterState, localState, syncProcessEvent); int syncFrequence = (Integer) conf .get(Config.SUPERVISOR_MONITOR_FREQUENCY_SECS); EventManagerPusher syncSupervisorPusher = new EventManagerPusher( syncSupEventManager, syncSupervisorEvent, active, syncFrequence); AsyncLoopThread syncSupervisorThread = new AsyncLoopThread( syncSupervisorPusher); threads.add(syncSupervisorThread); LOG.info("Starting supervisor with id " + supervisorId + " at host " + myHostName); // SupervisorManger which can shutdown all supervisor and workers return new SupervisorManger(conf, supervisorId, active, threads, syncSupEventManager, processEventManager, stormClusterState, workerThreadPids); }

Heartbeat线程

1、默认间隔60s向zookeeper汇报supervisor信息，汇报内容打包成SupervisorInfo，包括hostname，workerports，current time和during time等信息；

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@SuppressWarnings("unchecked") public void update() { SupervisorInfo sInfo = new SupervisorInfo( TimeUtils.current_time_secs(), myHostName, (List) conf.get(Config.SUPERVISOR_SLOTS_PORTS), (int) (TimeUtils.current_time_secs() - startTime)); try { stormClusterState.supervisor_heartbeat(supervisorId, sInfo); } catch (Exception e) { LOG.error("Failed to update SupervisorInfo to ZK", e);   } }

SyncProcessEvent线程

1、定期从本地文件$jstorm-local-dir/supervisor/localstate中读取key=”local-assignments”数据；该数据会由SyncSupervisorEvent线程定期写入；
2、读取本地$jstorm-local-dir /worker/ids/heartbeat中Worker状态数据；
3、对比local-assignments及worker的状态数据，执行操作start/kill worker进程；其中Worker和Supervisor属于不同JVM进程，Supervisor通过Shell命令启动Worker：

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nohup java –server -Djava.library.path="$JAVA.LIBRARY.PATH" -Dlogfile.name="$topologyid-worker-$port.log" -Dlog4j.configuration=jstorm.log4j.properties -Djstorm.home="$JSTORM_HOME" -cp $JAVA_CLASSSPATH:$JSTORM_CLASSPATH com.alipay.dw.jstorm.daemon.worker.Worker topologyid supervisorid port workerid

SyncProcessEvent线程执行流程如下：

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@SuppressWarnings("unchecked") @Override public void run() { LOG.debug("Syncing processes"); try { /** * Step 1: get assigned tasks from localstat Map */ //1.从本地文件$jstorm-local-dir/supervisor/localstate里读取key=“local-assignments”数据 Map localAssignments = null; try { localAssignments = (Map) localState .get(Common.LS_LOCAL_ASSIGNMENTS); } catch (IOException e) { LOG.error("Failed to get LOCAL_ASSIGNMENTS from LocalState", e); throw e; } if (localAssignments == null) { localAssignments = new HashMap(); } LOG.debug("Assigned tasks: " + localAssignments); /** * Step 2: get local WorkerStats from local_dir/worker/ids/heartbeat * Map */ //2.根据localAssignments与workers的hb比对结果得到workers的状态 Map localWorkerStats = null; try { localWorkerStats = getLocalWorkerStats(conf, localState, localAssignments); } catch (IOException e) { LOG.error("Failed to get Local worker stats"); throw e; } LOG.debug("Allocated: " + localWorkerStats); /** * Step 3: kill Invalid Workers and remove killed worker from * localWorkerStats */ //3.根据workers的状态值启动/停用相关worker Set keepPorts = killUselessWorkers(localWorkerStats); // start new workers startNewWorkers(keepPorts, localAssignments); } catch (Exception e) { LOG.error("Failed Sync Process", e); // throw e } }

SyncSupervisorEvent线程

1、从$zk-root/assignments/{topologyid}下载所有任务调度结果，并筛选出分配到当前supervisor的任务集合，验证单个端口仅分配了单个Topology的任务通过后，将上述任务集合写入本地文件$jstorm-local-dir/supervisor/localstate，以便SyncProcessEvent读取及后续操作；
2、对比任务分配结果与已经存在的Topology，从Nimbus下载新分配过来的Topology，同时删除过期Topology。
SyncSupervisorEvent线程执行流程如下：

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@Override public void run() { LOG.debug("Synchronizing supervisor"); try { RunnableCallback syncCallback = new EventManagerZkPusher(this, syncSupEventManager); /** * Step 1: get all assignments * and register /ZK-dir/assignment and every assignment watch * */ //1.从zk获取分配完成的任务集assignments:(topologyid -> Assignment) //$zkroot/assignments/{topologyid} Map assignments = Cluster.get_all_assignment( stormClusterState, syncCallback); LOG.debug("Get all assignments " + assignments); /** * Step 2: get topologyIds list from * STORM-LOCAL-DIR/supervisor/stormdist/ */ //2.本地已经下载的topology集合$jstorm-local-dir/supervisor/stormdist/{topologyid} List downloadedTopologyIds = StormConfig .get_supervisor_toplogy_list(conf); LOG.debug("Downloaded storm ids: " + downloadedTopologyIds); /** * Step 3: get from ZK local node's * assignment */ //3.从assignments里筛选出分配到当前supervisor的任务集合 Map localAssignment = getLocalAssign( stormClusterState, supervisorId, assignments); /** * Step 4: writer local assignment to LocalState */ //4.将步骤3得到的结果写本地文件$jstorm-local-dir/supervisor/localstate try { LOG.debug("Writing local assignment " + localAssignment); localState.put(Common.LS_LOCAL_ASSIGNMENTS, localAssignment); } catch (IOException e) { LOG.error("put LS_LOCAL_ASSIGNMENTS " + localAssignment + " of localState failed"); throw e; } // Step 5: download code from ZK //5.下载新分配任务的Topology Map topologyCodes = getTopologyCodeLocations(assignments); downloadTopology(topologyCodes, downloadedTopologyIds); /** * Step 6: remove any downloaded useless topology */ 6.删除过期任务的Topology removeUselessTopology(topologyCodes, downloadedTopologyIds); /** * Step 7: push syncProcesses Event */ processEventManager.add(syncProcesses); } catch (Exception e) { LOG.error("Failed to Sync Supervisor", e); // throw new RuntimeException(e); } }

2.Worker

在jstorm-0.7.1里，Worker daemon实现在jstorm-server/src/main/java目录下com.alipay.dw.jstorm.daemon.worker包。其中Worker.java是Worker daemon的入口。Worker进程的生命周期：
1、初始化Tuple序列化功能和数据发送管道；
2、创建分配到当前Worker的Tasks；
3、初始化并启动接收Tuple dispatcher；
4、初始化并启动用于维护Worker间连接线程RefreshConnections，包括创建/维护/销毁节点之间的连接等功能；
5、初始化并启动心跳线程WorkerHeartbeatRunable，更新本地目录：$jstorm_local_dir/worker/{workerid}/heartbeats/{workerid}；
6、初始化并启动发送Tuple线程DrainerRunable；
7、注册主线程退出现场数据清理Hook。
Worker Daemon初始化流程如下：

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public WorkerShutdown execute() throws Exception { //1. Tuple序列化+发送管道LinkedBlockingQueue WorkerTransfer workerTransfer = getSendingTransfer(); // shutdown task callbacks //2. 初始化task线程 List shutdowntasks = createTasks(workerTransfer); workerData.setShutdownTasks(shutdowntasks); //3. WorkerVirtualPort：tuple接收dispatcher // create virtual port object // when worker receives tupls, dispatch targetTask according to task_id // conf, supervisorId, topologyId, port, mqContext, taskids WorkerVirtualPort virtual_port = new WorkerVirtualPort(workerData); Shutdownable virtual_port_shutdown = virtual_port.launch(); //3. RefreshConnections：维护节点间的连接：创建新连接|维护已建立连接|销毁无用连接 // refresh connection RefreshConnections refreshConn = makeRefreshConnections(); AsyncLoopThread refreshconn = new AsyncLoopThread(refreshConn); // refresh ZK active status RefreshActive refreshZkActive = new RefreshActive(workerData); AsyncLoopThread refreshzk = new AsyncLoopThread(refreshZkActive); //4. WorkerHeartbeatRunable：心跳线程 // 每次心跳更新本地目录数据 $LOCAL_PATH/workers/{worker-id}/Heartbeats/{worker-id} // refresh hearbeat to Local dir RunnableCallback heartbeat_fn = new WorkerHeartbeatRunable(workerData); AsyncLoopThread hb = new AsyncLoopThread(heartbeat_fn, false, null, Thread.NORM_PRIORITY, true); //5. DrainerRunable：发送tuple线程 // transferQueue, nodeportSocket, taskNodeport DrainerRunable drainer = new DrainerRunable(workerData); AsyncLoopThread dr = new AsyncLoopThread(drainer, false, null, Thread.MAX_PRIORITY, true); AsyncLoopThread[] threads = { refreshconn, refreshzk, hb, dr }; //6. 注册主线程退出数据清理hook return new WorkerShutdown(workerData, shutdowntasks, virtual_port_shutdown, threads); }

3.Task

根据任务在Topology中不同节点角色，Task相应也会分成SpoutTask和BoltTask，二者除Task心跳及公共数据初始化等相同以外，各自有独立处理逻辑。核心实现在SpoutExecutors.java/BoltExecutors.java。

SpoutExecutors主要做两件事情：
1、作为DAG起点，负责发送原始Tuple数据；
2、如果Topology定义了Acker，SpoutExecutors会启动接收ack线程，根据接收到的ack决定是否重发Tuple；

BoltExecutor相比SpoutExecutor功能会稍微复杂：
1、接收从上游发送过来的Tuple，并根据Topology中定义的处理逻辑进行处理；
2、如果该Bolt存在下游，需要向下游发送新生成的Tuple；
3、如果Topology中定义了Acker，Bolt需要将经过简单计算的ack返回给根Spout。

四、结语

本文介绍了Supervisor/Worker/Task在整个JStorm中完成的工作及其实现逻辑和关键流程的源码剖析，其中难免存在不足和错误，欢迎交流指导。

五、参考文献

[1]Storm社区. http://Storm.incubator.apache.org/
[2]JStorm源码. https://github.com/alibaba/jStorm/
[3]Storm源码. https://github.com/nathanmarz/Storm/
[4]Jonathan Leibiusky, Gabriel Eisbruch, etc. Getting Started with Storm.http://shop.oreilly.com/product/0636920024835.do. O’Reilly Media, Inc.
[5]Xumingming Blog. http://xumingming.sinaapp.com/
[6]量子恒道官方博客. http://blog.linezing.com/