spark-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Akhil Das <ak...@sigmoidanalytics.com>
Subject Re: cannot run spark-shell interactively against cluster from remote host - confusing memory warnings
Date Mon, 26 Jan 2015 15:15:49 GMT
When you say remote cluster you need to make sure a few things like:

- No firewall/network is blocking any connection (Simply ping from
localmachine to remote ip and vice versa)
- Make sure all ports (unless you specify them manually) are open.

You can also refer this discussion,
http://apache-spark-user-list.1001560.n3.nabble.com/Submitting-Spark-job-on-Unix-cluster-from-dev-environment-Windows-td16989.html

Hope it helps.

Thanks
Best Regards

On Sun, Jan 25, 2015 at 2:40 AM, Joseph Lust <jlust@mc10inc.com> wrote:

>  I’ve setup a Spark cluster in the last few weeks and everything is
> working, but * I cannot run spark-shell interactively against the cluster
> from a remote host*
>
>    - Deploy .jar to cluster from remote (laptop) spark-submit and have it
>    run – Check
>    - Run .jar on spark-shell locally – Check
>    - Run same .jar on spark-shell on master server – Check
>    - Run spark-shell interactively against cluster on master server –
>    Check
>    - Run spark-shell interactively from remote (laptop) against cluster –
>    *FAIL*
>
>  It seems other people have faced this same issue:
>
> http://apache-spark-user-list.1001560.n3.nabble.com/spark-shell-working-local-but-not-remote-td19727.html
>
>  I’m getting the same warnings about memory, despite plenty of memory
> being available for the job to run (see above working cases)
>
>  "WARN TaskSchedulerImpl: Initial job has not accepted any resources;
> check your cluster UI to ensure that workers are registered and have
> sufficient memory”
>
>  Some have suggested it has to do with conflicts of Jars on the class
> path and that Spark is providing spurious memory error messages while the
> problem is really class path conflicts.
>
> http://apache-spark-user-list.1001560.n3.nabble.com/WARN-ClusterScheduler-Initial-job-has-not-accepted-any-resources-check-your-cluster-UI-to-ensure-thay-td374.html#a396
>
>  Details:
>
>    - Cluster: 1 master, 3 workers on 4GB/4 core Ubuntu 14.04 LTS
>    - Local (aka remote laptop) MacBook Pro 10.10.1
>    - All running HotSpot Java (build 1.8.0_31-b13 and uild 1.8.0_25-b17)
>    - All running spark-1.2.0-bin-hadoop2.4
>    - Using Standalone cluster manager
>
>
>  Cluster UI:
> *
>
>  Even when I clamp down to the most restrictive amounts, 1 core, 1
> executor, 128m (of 3G available), it still says I don’t have the resources:
>
>  >>>> Start Console example
> $ spark-shell --executor-memory 128m --total-executor-cores 1
> --driver-cores 1 --master spark://XXXX:7077
>
>  15/01/24 15:57:29 INFO SparkILoop: Created spark context..
> Spark context available as sc.
>
>  scala> val rdd = sc.parallelize(1 to 1000);
> rdd: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at
> parallelize at <console>:12
> scala> rdd.count
>
>  15/01/24 15:58:20 INFO BlockManagerMaster: Updated info of block
> broadcast_0_piece0
> 15/01/24 15:58:20 INFO SparkContext: Created broadcast 0 from broadcast at
> DAGScheduler.scala:838
> 15/01/24 15:58:20 INFO DAGScheduler: Submitting 2 missing tasks from Stage
> 0 (ParallelCollectionRDD[0] at parallelize at <console>:12)
> 15/01/24 15:58:20 INFO TaskSchedulerImpl: Adding task set 0.0 with 2 tasks
> 15/01/24 15:58:35 WARN TaskSchedulerImpl: Initial job has not accepted any
> resources; check your cluster UI to ensure that workers are registered and
> have sufficient memory
>  >>> End console example
>
>  So, can anyone tell me if remote interactive spark-shell on a Standalone
> cluster even works? Thanks for your help.
>
>  Cluster UI below showing job is running on cluster, is using a driver
> app and worker, and that there are plenty of cores and GB of memory free.
>
>
>  Sincerely,
> Joe Lust
>

Mime
View raw message