Github user drexin commented on the pull request:
https://github.com/apache/spark/pull/1358#issuecomment-48706534
Hi Patrick,
the problem is described in [this mailing list
entry](http://mail-archives.apache.org/mod_mbox/mesos-user/201407.mbox/%3c53b66e6d.7090...@uninett.no%3e)
If I understand the [documentation on run
modes](http://spark.apache.org/docs/latest/running-on-mesos.html) and the code
correctly, in fine grained mode it starts a separate instance of
`MesosExecutorBackend` for each spark task. If this is correct, then as soon as
2 tasks run concurrently on the same machine we should run into this problem.
On [this
line](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala#L329)
in the `BlockManagerMasterActor`, there is a check on the `BlockManagerId`,
which will always be different per `Executor` instance, because the port in
there is randomly assigned. The `executorId` however is always set to the mesos
`slaveId`. This means that we are running into [this
case](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala#L331-L335)
as soon as we start two `Executor` instances on the same slave. This PR fixes
this by adding the counter to the `executorId`. Please tell me if I overlooked
something.
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