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From Gerard Maas <gerard.m...@gmail.com>
Subject Spark (Streaming?) holding on to Mesos Resources
Date Mon, 26 Jan 2015 21:25:35 GMT
(looks like the list didn't like a HTML table on the previous email. My
excuses for any duplicates)

Hi,

We are observing with certain regularity that our Spark  jobs, as Mesos
framework, are hoarding resources and not releasing them, resulting in
resource starvation to all jobs running on the Mesos cluster.

For example:
This is a job that has spark.cores.max = 4 and spark.executor.memory="3g"

| ID               |Framework      |Host                |CPUs  |Mem
…5050-16506-1146497 FooStreaming dnode-4.hdfs.private 7 13.4 GB
…5050-16506-1146495 FooStreaming    dnode-0.hdfs.private 1 6.4 GB
…5050-16506-1146491 FooStreaming    dnode-5.hdfs.private 7 11.9 GB
…5050-16506-1146449 FooStreaming    dnode-3.hdfs.private 7 4.9 GB
…5050-16506-1146247 FooStreaming    dnode-1.hdfs.private 0.5 5.9 GB
…5050-16506-1146226 FooStreaming    dnode-2.hdfs.private 3 7.9 GB
…5050-16506-1144069 FooStreaming    dnode-3.hdfs.private 1 8.7 GB
…5050-16506-1133091 FooStreaming    dnode-5.hdfs.private 1 1.7 GB
…5050-16506-1133090 FooStreaming    dnode-2.hdfs.private 5 5.2 GB
…5050-16506-1133089 FooStreaming    dnode-1.hdfs.private 6.5 6.3 GB
…5050-16506-1133088 FooStreaming    dnode-4.hdfs.private 1 251 MB
…5050-16506-1133087 FooStreaming    dnode-0.hdfs.private 6.4 6.8 GB

The only way to release the resources is by manually finding the process in
the cluster and killing it. The jobs are often streaming but also batch
jobs show this behavior. We have more streaming jobs than batch, so stats
are biased.
Any ideas of what's up here? Hopefully some very bad ugly bug that has been
fixed already and that will urge us to upgrade our infra?

Mesos 0.20 +  Marathon 0.7.4 + Spark 1.1.0

-kr, Gerard.

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