[jira] [Created] (SPARK-22558) SparkHiveDynamicPartition fails when trying to write data from kafka to hive using spark streaming

["KhajaAsmath Mohammed (JIRA)" <ji...@apache.org>]

KhajaAsmath Mohammed created SPARK-22558:
--------------------------------------------

             Summary: SparkHiveDynamicPartition fails when trying to write data from kafka to hive using spark streaming
                 Key: SPARK-22558
                 URL: https://issues.apache.org/jira/browse/SPARK-22558
             Project: Spark
          Issue Type: Bug
          Components: Spark Core, Spark Shell, Spark Submit
    Affects Versions: 2.1.1
            Reporter: KhajaAsmath Mohammed


I am able to write data from kafka into hive table using spark streaming. Batches run successfully for one day and after some successful runs I get below errors. Is there a way to resolve it.

It is dynamic hive partitoon 

Job aborted due to stage failure: Task 0 in stage 381.0 failed 4 times, most recent failure: Lost task 0.3 in stage 381.0 (TID 129383, brksvl255.brk.navistar.com, executor 1): org.apache.spark.SparkException: Task failed while writing rows.
	at org.apache.spark.sql.hive.SparkHiveDynamicPartitionWriterContainer.writeToFile(hiveWriterContainers.scala:328)
	at org.apache.spark.sql.hive.execution.InsertIntoHiveTable$$anonfun$saveAsHiveFile$3.apply(InsertIntoHiveTable.scala:210)
	at org.apache.spark.sql.hive.execution.InsertIntoHiveTable$$anonfun$saveAsHiveFile$3.apply(InsertIntoHiveTable.scala:210)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
	at org.apache.spark.scheduler.Task.run(Task.scala:99)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NullPointerException
	at parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:152)
	at parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:111)
	at parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:112)
	at org.apache.hadoop.hive.ql.io.parquet.write.ParquetRecordWriterWrapper.close(ParquetRecordWriterWrapper.java:102)
	at org.apache.hadoop.hive.ql.io.parquet.write.ParquetRecordWriterWrapper.close(ParquetRecordWriterWrapper.java:119)
	at org.apache.spark.sql.hive.SparkHiveDynamicPartitionWriterContainer.writeToFile(hiveWriterContainers.scala:320)
	... 8 more

I am sure there is some problem with dynamic partion. Here is query executed inside dstream.

insert into bonalab.datapoint_location partition(year,month) 
select vin,utctime,description,descriptionuom,providerdesc,
islocation,latitude,longitude,speed,value, current_timestamp as processed_date,
1 as version, 
year,month from 
bonalab.datapoint_location where
year=2017 
and month=10 
group by year,month,vin,utctime,description,descriptionuom,providerdesc,
islocation,latitude,longitude,speed,value,processed_date limit 15

 val datapointDF = datapointDStream.foreachRDD { rdd =>
if (!runMode.equalsIgnoreCase("local")) {
        sparkSession.sql(s"set hive.exec.dynamic.partition.mode=nonstrict")
        sparkSession.sql("SET hive.exec.max.dynamic.partitions.pernode = 400")
        sparkSession.sql(s"set hive.exec.dynamic.partition = true")
      }
if (!rdd.isEmpty) {
        /*   val sparkSession = SparkSession.builder.enableHiveSupport.getOrCreate
        import sparkSession.implicits._*/
        val datapointDstreamDF = rdd.toDS
        //println("DataPoint data")
        //datapointDstreamDF.show(1)
        datapointDstreamDF.createOrReplaceTempView("datapoint_tmp")
sparkSession.sql(HiveDAO.Geofences.insertLocationDataPoints("datapoint_tmp",hiveDBInstance))
}
}



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