Hi Xiangrui,
I accidentally did not send df -i for the master node. Here it is at the
moment of failure:
Filesystem Inodes IUsed IFree IUse% Mounted on
/dev/xvda1 524288 280938 243350 54% /
tmpfs 3845409 1 3845408 1% /dev/shm
/dev/xvdb 10002432 1027 10001405 1% /mnt
/dev/xvdf 10002432 16 10002416 1% /mnt2
/dev/xvdv 524288000 13 524287987 1% /vol
I am using default settings now, but is there a way to make sure that the
proper directories are being used? How many blocks/partitions do you
recommend?
Chris
On Wed, Jul 16, 2014 at 1:09 AM, Chris DuBois <chris.dub...@gmail.com>
wrote:
> Hi Xiangrui,
>
> Here is the result on the master node:
> $ df -i
> Filesystem Inodes IUsed IFree IUse% Mounted on
> /dev/xvda1 524288 273997 250291 53% /
> tmpfs 1917974 1 1917973 1% /dev/shm
> /dev/xvdv 524288000 30 524287970 1% /vol
>
> I have reproduced the error while using the MovieLens 10M data set on a
> newly created cluster.
>
> Thanks for the help.
> Chris
>
>
> On Wed, Jul 16, 2014 at 12:22 AM, Xiangrui Meng <men...@gmail.com> wrote:
>
>> Hi Chris,
>>
>> Could you also try `df -i` on the master node? How many
>> blocks/partitions did you set?
>>
>> In the current implementation, ALS doesn't clean the shuffle data
>> because the operations are chained together. But it shouldn't run out
>> of disk space on the MovieLens dataset, which is small. spark-ec2
>> script sets /mnt/spark and /mnt/spark2 as the local.dir by default, I
>> would recommend leaving this setting as the default value.
>>
>> Best,
>> Xiangrui
>>
>> On Wed, Jul 16, 2014 at 12:02 AM, Chris DuBois <chris.dub...@gmail.com>
>> wrote:
>> > Thanks for the quick responses!
>> >
>> > I used your final -Dspark.local.dir suggestion, but I see this during
>> the
>> > initialization of the application:
>> >
>> > 14/07/16 06:56:08 INFO storage.DiskBlockManager: Created local
>> directory at
>> > /vol/spark-local-20140716065608-7b2a
>> >
>> > I would have expected something in /mnt/spark/.
>> >
>> > Thanks,
>> > Chris
>> >
>> >
>> >
>> > On Tue, Jul 15, 2014 at 11:44 PM, Chris Gore <cdg...@cdgore.com> wrote:
>> >>
>> >> Hi Chris,
>> >>
>> >> I've encountered this error when running Spark’s ALS methods too. In
>> my
>> >> case, it was because I set spark.local.dir improperly, and every time
>> there
>> >> was a shuffle, it would spill many GB of data onto the local drive.
>> What
>> >> fixed it was setting it to use the /mnt directory, where a network
>> drive is
>> >> mounted. For example, setting an environmental variable:
>> >>
>> >> export SPACE=$(mount | grep mnt | awk '{print $3"/spark/"}' | xargs |
>> sed
>> >> 's/ /,/g’)
>> >>
>> >> Then adding -Dspark.local.dir=$SPACE or simply
>> >> -Dspark.local.dir=/mnt/spark/,/mnt2/spark/ when you run your driver
>> >> application
>> >>
>> >> Chris
>> >>
>> >> On Jul 15, 2014, at 11:39 PM, Xiangrui Meng <men...@gmail.com> wrote:
>> >>
>> >> > 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
>> >> >>
>> >>
>> >
>>
>
>
