hadoop - Spark Streaming with large messages java.lang.OutOfMemoryError: Java heap space -


enter image description herei using spark streaming 1.6.1 kafka0.9.0.1 (createstreams api) hdp 2.4.2, use case sends large messages kafka topics ranges 5mb 30 mb in such cases spark streaming fails complete job , crashes below exception.i doing dataframe operation , saving on hdfs in csv format, below code snippet

reading kafka topic:      val lines = kafkautils.createstream[string, string, stringdecoder, stringdecoder](ssc, kafkaparams, topicmap, storagelevel.memory_and_disk_ser_2/*memory_only_ser_2*/).map(_._2)   writing on hdfs:       val hdfsdf: dataframe = getdf(sqlcontext, eventdf, schema,topicname)       hdfsdf.show       hdfsdf.write         .format("com.databricks.spark.csv")         .option("header", "false")         .save(hdfspath + "/" + "out_" + system.currenttimemillis().tostring())  16/11/11 12:12:35 warn receivertracker: error reported receiver stream 0: error handling message; exiting - java.lang.outofmemoryerror: java heap space     @ java.lang.stringcoding$stringdecoder.decode(stringcoding.java:149)     @ java.lang.stringcoding.decode(stringcoding.java:193)     @ java.lang.string.<init>(string.java:426)     @ java.lang.string.<init>(string.java:491)     @ kafka.serializer.stringdecoder.frombytes(decoder.scala:50)     @ kafka.serializer.stringdecoder.frombytes(decoder.scala:42)     @ kafka.message.messageandmetadata.message(messageandmetadata.scala:32)     @ org.apache.spark.streaming.kafka.kafkareceiver$messagehandler.run(kafkainputdstream.scala:137)     @ java.util.concurrent.executors$runnableadapter.call(executors.java:511)     @ java.util.concurrent.futuretask.run(futuretask.java:266)     @ java.util.concurrent.threadpoolexecutor.runworker(threadpoolexecutor.java:1142)     @ java.util.concurrent.threadpoolexecutor$worker.run(threadpoolexecutor.java:617)     @ java.lang.thread.run(thread.java:745)

followed :

 java.lang.exception: not compute split, block input-0-1478610837000 not found @ org.apache.spark.rdd.blockrdd.compute(blockrdd.scala:51) @ org.apache.spark.rdd.rdd.computeorreadcheckpoint(rdd.scala:313) @ org.apache.spark.rdd.rdd.iterator(rdd.scala:277) @ org.apache.spark.rdd.mappartitionsrdd.compute(mappartitionsrdd.scala:38) @ org.apache.spark.rdd.rdd.computeorreadcheckpoint(rdd.scala:313) @ org.apache.spark.rdd.rdd.iterator(rdd.scala:277) @ org.apache.spark.scheduler.resulttask.runtask(resulttask.scala:66) @ org.apache.spark.scheduler.task.run(task.scala:89) @ org.apache.spark.executor.executor$taskrunner.run(executor.scala:214) @ java.util.concurrent.threadpoolexecutor.runworker(threadpoolexecutor.java:1142) @ java.util.concurrent.threadpoolexecutor$worker.run(threadpoolexecutor.java:617) @ java.lang.thread.run(thread.java:745) driver stacktrace:


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