title: Submitting 50 missing tasks from ShuffleMapStage - spark log explanation
body: <p>When I submit the spark streaming job it creates a job with 70 tasks and its getting completed like in 2 seconds. Then it starts up the same job with one task running which is the desired behaviour. The job is receiving mq data via a custom receiver. </p>
  
  <p>The jar I submit only contains a MQ custom reciever and kafka sink. No processors. It just send what has been received to mq to kafka. </p>
  
  <p>I could found following in the spark log. 
  But other than that I have no idea why it creates such amount of tasks at the initiation. </p>
  
  <p>INFO  DAGScheduler:54 - Submitting 50 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[1] at start at Streaming.java:59) (first 15 tasks are for partitions Vector(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14))</p>