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From "Tejas Patil (JIRA)" <>
Subject [jira] [Created] (SPARK-19326) Speculated task attempts do not get launched in few scenarios
Date Sun, 22 Jan 2017 03:46:26 GMT
Tejas Patil created SPARK-19326:

             Summary: Speculated task attempts do not get launched in few scenarios
                 Key: SPARK-19326
             Project: Spark
          Issue Type: Bug
          Components: Scheduler
    Affects Versions: 2.1.0, 2.0.2
            Reporter: Tejas Patil

Speculated copies of tasks do not get launched in some cases.

- All the running executors have no CPU slots left to accommodate a speculated copy of the
task(s). If the all running executors reside over a set of slow / bad hosts, they will keep
the job running for long time
- `spark.task.cpus` > 1 and the running executor has not filled up all its CPU slots. Since
the [speculated copies of tasks should run on different host|]
and not the host where the first copy was launched.

In both these cases, `ExecutorAllocationManager` does not know about pending speculation task
attempts and thinks that all the resource demands are well taken care of. ([relevant code|])

This adds variation in the job completion times and more importantly SLA misses :( In prod,
with a large number of jobs, I see this happening more often than one would think. Chasing
the bad hosts or reason for slowness doesn't scale.

Here is a tiny repro. Note that you need to launch this with (Mesos or YARN or standalone
deploy mode) along with `spark.speculation=true`

val someRDD = sc.parallelize(1 to 8, 8)
someRDD.mapPartitionsWithIndex( (index: Int, it: Iterator[Int]) => {
if (index == 8) {
  Thread.sleep(Long.MaxValue)  // fake long running task(s)
} => index + ", " + x).iterator

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