Check the number of inodes (df -i). The assembly build may create many
small files. -Xiangrui
On Tue, Jul 15, 2014 at 11:35 PM, Chris DuBois <chris.dub...@gmail.com> wrote:
> Hi all,
>
> I am encountering the following error:
>
> INFO scheduler.TaskSetManager: Loss was due to java.io.IOException: No space
> left on device [duplicate 4]
>
> For each slave, df -h looks roughtly like this, which makes the above error
> surprising.
>
> Filesystem Size Used Avail Use% Mounted on
> /dev/xvda1 7.9G 4.4G 3.5G 57% /
> tmpfs 7.4G 4.0K 7.4G 1% /dev/shm
> /dev/xvdb 37G 3.3G 32G 10% /mnt
> /dev/xvdf 37G 2.0G 34G 6% /mnt2
> /dev/xvdv 500G 33M 500G 1% /vol
>
> I'm on an EC2 cluster (c3.xlarge + 5 x m3) that I launched using the
> spark-ec2 scripts and a clone of spark from today. The job I am running
> closely resembles the collaborative filtering example. This issue happens
> with the 1M version as well as the 10 million rating version of the
> MovieLens dataset.
>
> I have seen previous questions, but they haven't helped yet. For example, I
> tried setting the Spark tmp directory to the EBS volume at /vol/, both by
> editing the spark conf file (and copy-dir'ing it to the slaves) as well as
> through the SparkConf. Yet I still get the above error. Here is my current
> Spark config below. Note that I'm launching via ~/spark/bin/spark-submit.
>
> conf = SparkConf()
> conf.setAppName("RecommendALS").set("spark.local.dir",
> "/vol/").set("spark.executor.memory", "7g").set("spark.akka.frameSize",
> "100").setExecutorEnv("SPARK_JAVA_OPTS", " -Dspark.akka.frameSize=100")
> sc = SparkContext(conf=conf)
>
> Thanks for any advice,
> Chris
>
