Twitter Storm中Bolt消息传递路径之源码解读

简介: Bolt作为task被executor执行,而executor是一个个的线程,所以executor必须存在于具体的process之中,而这个process就是worker。至于worker是如何被supervisor创建,尔后worker又如何创建executor线程,这些暂且按下不表。
+关注继续查看

Bolt作为task被executor执行,而executor是一个个的线程,所以executor必须存在于具体的process之中,而这个process就是worker。至于worker是如何被supervisor创建,尔后worker又如何创建executor线程,这些暂且按下不表。

 
假设同属于一个Topology的Spout与Bolt分别处于不同的JVM,即不同的worker中,不同的JVM可能处于同一台物理机器,也可能处于不同的物理机器中。为了让情景简单,认为JVM处于不同的物理机器中。
 
Spout的输出消息到达Bolt,作为Bolt的输入会经过这么几个阶段。
 
1. spout的输出通过该spout所处worker的消息输出线程,将tuple输入到Bolt所属的worker。它们之间的通路是socket连接,用ZeroMQ实现。
2. bolt所处的worker有一个专门处理socket消息的receive thread 接收到spout发送来的tuple
3. receive thread将接收到的消息传送给对应的bolt所在的executor。 在worker内部(即同一process内部),消息传递使用的是Lmax Disruptor pattern.
4. executor接收到tuple之后,由event-handler进行处理
 
下面是具体的源码
1. worker创建消息接收线程 
 
worker.clj
 
(defn launch-receive-thread [worker]
  (log-message "Launching receive-thread for " (:assignment-id worker) ":" (:port worker))
  (msg-loader/launch-receive-thread!
    (:mq-context worker)
    (:storm-id worker)
    (:port worker)
    (:transfer-local-fn worker)
    (-> worker :storm-conf (get TOPOLOGY-RECEIVER-BUFFER-SIZE))
    :kill-fn (fn [t] (halt-process! 11))))
 
注意加亮的行会将storm.yaml中配置使用ZMQ或其它
storm.messaging.transport:"backtype.storm.messaging.zmq"
 
2. worker从socket接收到新消息
vthread (async-loop
                 (fn []
                   (let [socket (.bind ^IContext context storm-id port)]
                     (fn []
                       (let [batched (ArrayList.)
                             init (.recv ^IConnection socket 0)]
                         (loop [packet init]
                           (let [task (if packet (.task ^TaskMessage packet))
                                 message (if packet (.message ^TaskMessage packet))]
                             (if (= task -1)
                               (do (log-message "Receiving-thread:[" storm-id ", " port "] received shutdown notice")
                                 (.close socket)
                                 nil )
                               (do
                                 (when packet (.add batched [task message]))
                                 (if (and packet (< (.size batched) max-buffer-size))
                                   (recur (.recv ^IConnection socket 1))
                                   (do (transfer-local-fn batched)
                                     0 ))))))))))
 
加亮行使用的transfer-local-fn会将接收的TaskMessage传递给相应的executor
 
3. transfer-local-fn
 
(defn mk-transfer-local-fn [worker]
  (let [short-executor-receive-queue-map (:short-executor-receive-queue-map worker)
        task->short-executor (:task->short-executor worker)
        task-getter (comp #(get task->short-executor %) fast-first)]
    (fn [tuple-batch]
      (let [grouped (fast-group-by task-getter tuple-batch)]
        (fast-map-iter [[short-executor pairs] grouped]
          (let [q (short-executor-receive-queue-map short-executor)]
            (if q
              (disruptor/publish q pairs)
              (log-warn "Received invalid messages for unknown tasks. Dropping... ")
              )))))))
 
用disruptor在线程之间进行消息传递。
 
多费一句话,mk-transfer-local-fn表示将外部世界的消息传递给本进程内的线程。而mk-transfer-fn则刚好在方向上反过来。
 
4. 消息被executor处理
 
executor.clj
==========================================================
(defn mk-task-receiver [executor-data tuple-action-fn]
  (let [^KryoTupleDeserializer deserializer (:deserializer executor-data)
        task-ids (:task-ids executor-data)
        debug? (= true (-> executor-data :storm-conf (get TOPOLOGY-DEBUG)))
        ]
    (disruptor/clojure-handler
      (fn [tuple-batch sequence-id end-of-batch?]
        (fast-list-iter [[task-id msg] tuple-batch]
          (let [^TupleImpl tuple (if (instance? Tuple msg) msg (.deserialize deserializer msg))]
            (when debug? (log-message "Processing received message " tuple))
            (if task-id
              (tuple-action-fn task-id tuple)
              ;; null task ids are broadcast tuples
              (fast-list-iter [task-id task-ids]
                (tuple-action-fn task-id tuple)
                ))
            ))))))
 
加亮行中tuple-action-fn定义于mk-threads(源文件executor.clj)中。因为当前以Bolt为例,所以会调用的tuple-action-fn定义于defmethod mk-threads :bolt [executor-data task-datas]
 
那么mk-task-receiver是如何与disruptor关联起来的呢,可以见定义于mk-threads中的下述代码
(let [receive-queue (:receive-queue executor-data)
              event-handler (mk-task-receiver executor-data tuple-action-fn)]
          (disruptor/consumer-started! receive-queue)
          (fn []            
            (disruptor/consume-batch-when-available receive-queue event-handler)
            0)))
 
到了这里,消息的发送与接收处理路径打通。
目录
相关文章
|
11月前
|
消息中间件 Java Kafka
Java实现Flink集成Kafka生产者
Java实现Flink集成Kafka生产者
273 0
推荐文章
更多