: Failed to create file system watcher service: User limit of inotify instances reached or too many open files

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: Failed to create file system watcher service: User limit of inotify instances reached or too many open files

Polisetti, Venkata Siva Rama Gopala Krishna

Hi,

 

When I am doing calculations for example 700 listID’s it is saving only some 50 rows and then getting some random exceptions

 

Getting below exception when I try to do calculations on huge data and try to save huge data . Please let me know if any suggestions.

 

Sample Code :

 

    I have some lakhs ListID’s making group of RDD  rdd.groupBy(row => row.getInt(6)).  And then using .map doing all ranking calculations

 

Step1 : groupedPartitionRdd =  rdd.groupBy(row => row.getInt(6))

Step2 :  val outputObjectForGainersAndLosers =  groupedPartitionRdd.map(grp =>

      {

                                                //ranking logic and some calculations

 

      }

Step 3 :    outputObjectForGainersAndLosers.saveToCassandra("tablename“,somecolumns ).

 

 

Am getting some random exceptions every time in spark- submit not able to debug and facing lot of issues.

 

Caused by: java.lang.RuntimeException: Failed to create file system watcher service: User limit of inotify instances reached or too many open files

Caused by: java.io.IOException: User limit of inotify instances reached or too many open files

Failed to create file system watcher service: User limit of inotify instances reached or too many open files

 

Error while invoking RpcHandler#receive() for one-way message.

org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.

        at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:154)

        at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:134)

        at org.apache.spark.rpc.netty.NettyRpcHandler.receive(NettyRpcEnv.scala:644)

        at org.apache.spark.network.server.TransportRequestHandler.processOneWayMessage(TransportRequestHandler.java:178)

        at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:107)

        at org.apache.spark.network.server.TransportChannelHandler.channelRead

 

Thanks,

Gopi




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