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https://issues.apache.org/jira/browse/SPARK-22558?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16259472#comment-16259472
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KhajaAsmath Mohammed commented on SPARK-22558:
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any suggestions for this issue?
> 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
> Original Estimate: 12h
> Remaining Estimate: 12h
>
> 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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