In Spark Streaming, is there a way to detect when a batch has finished?

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北海茫月
北海茫月 2020-12-19 13:22

I use Spark 1.6.0 with Cloudera 5.8.3.
I have a DStream object and plenty of transformations defined on top of it,

val stream = KafkaUtils.c         


        
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  • 2020-12-19 13:57

    Using streaming listeners should solve the problem for you:

    (sorry it's a java example)

    ssc.addStreamingListener(new JobListener());
    
    // ...
    
    class JobListener implements StreamingListener {
    
     @Override
        public void onBatchCompleted(StreamingListenerBatchCompleted batchCompleted) {
    
            System.out.println("Batch completed, Total delay :" + batchCompleted.batchInfo().totalDelay().get().toString() +  " ms");
    
        }
    
       /*
    
       snipped other methods
    
       */
    
    
    }
    

    https://gist.github.com/akhld/b10dc491aad1a2007183

    https://jaceklaskowski.gitbooks.io/mastering-apache-spark/content/spark-streaming/spark-streaming-streaminglisteners.html

    http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.streaming.scheduler.StreamingListener

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  • 2020-12-19 14:04

    Start a stream with name myStreamName and wait for it to start up -

    deltaStreamingQuery = (streamingDF
      .writeStream
      .format("delta")
      .queryName(myStreamName)
      .start(writePath)
    )
    
    untilStreamIsReady(myStreamName) 
    

    PySpark version wait for the stream to start up:

    def getActiveStreams():
      try:
        return spark.streams.active
      except:
        print("Unable to iterate over all active streams - using an empty set instead.")
        return []
    
    def untilStreamIsReady(name, progressions=3):
      import time
      queries = list(filter(lambda query: query.name == name, getActiveStreams()))
    
      while (len(queries) == 0 or len(queries[0].recentProgress) < progressions):
        time.sleep(5) # Give it a couple of seconds
        queries = list(filter(lambda query: query.name == name, getActiveStreams()))
    
      print("The stream {} is active and ready.".format(name))
    

    Spark Scala version wait for the stream to start up:

    def getActiveStreams():Seq[org.apache.spark.sql.streaming.StreamingQuery] = {
      return try {
        spark.streams.active
      } catch {
        case e:Throwable => {
          // In extream cases, this funtion may throw an ignorable error.
          println("Unable to iterate over all active streams - using an empty set instead.")
          Seq[org.apache.spark.sql.streaming.StreamingQuery]()
        }
      }
    }
    
    def untilStreamIsReady(name:String, progressions:Int = 3):Unit = {
      var queries = getActiveStreams().filter(_.name == name)
    
      while (queries.length == 0 || queries(0).recentProgress.length < progressions) {
        Thread.sleep(5*1000) // Give it a couple of seconds
        queries = getActiveStreams().filter(_.name == name)
      }
      println("The stream %s is active and ready.".format(name))
    }
    

    To the original question.. add another version of this function - wait for the stream first to start up and then wait another time (just add a negative condition on the wait state) for it to finish, so the complete version would look something like this -

    untilStreamIsReady(myStreamName) 
    untilStreamIsDone(myStreamName)   // reverse of untilStreamIsReady - wait when myStreamName will not be in the list 
    
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