Hi Sachin,

In your YARN configuration, either yarn.nodemanager.resource.memory-mb is
1024 on your nodes or yarn.scheduler.maximum-allocation-mb is set to 1024.
If you have more than 1024 MB on each node, you should bump these
properties.  Otherwise, you should request fewer resources by setting
--executor-memory and --driver-memory when you launch your Spark job.

-Sandy

On Sat, Feb 7, 2015 at 10:04 AM, sachin Singh <[email protected]>
wrote:

> Hi,
> when I am trying to execute my program as
> spark-submit --master yarn --class com.mytestpack.analysis.SparkTest
> sparktest-1.jar
>
> I am getting error bellow error-
> java.lang.IllegalArgumentException: Required executor memory (1024+384 MB)
> is above the max threshold (1024 MB) of this cluster!
>         at
>
> org.apache.spark.deploy.yarn.ClientBase$class.verifyClusterResources(ClientBase.scala:71)
>         at
> org.apache.spark.deploy.yarn.Client.verifyClusterResources(Client.scala:35)
>         at
> org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:77)
>         at
>
> org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:57)
>         at
>
> org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:140)
>         at org.apache.spark.SparkContext.<init>(SparkContext.scala:335)
>         at
>
> org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:61)
>
> I am new in Hadoop environment,
> Please help how/where need to set memory or any configuration ,thanks in
> advance,
>
>
>
>
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