[
https://issues.apache.org/jira/browse/SPARK-20880?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Vinod KC updated SPARK-20880:
-----------------------------
Description:
When spark SQL is used with Avro-backed HIVE tables, intermittently getting NPE
from
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories.
Root cause is due to race condition in hive 1.2.1 jar used in Spark SQL .
In HIVE 2.3 this issue has been fixed (HIVE JIRA:
https://issues.apache.org/jira/browse/HIVE-16175. ), since Spark is still using
Hive 1.2.1 jars we are still getting into a race condition.
One workaround is to run Spark with a single task per executor, however, it
will slow down the jobs.
Exception stack trace
13/05/07 09:18:39 WARN scheduler.TaskSetManager: Lost task 18.0 in stage 0.0
(TID 18, aiyhyashu.dxc.com): java.lang.NullPointerException
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories(AvroObjectInspectorGenerator.java:142)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:91)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:104)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:104)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:120)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspector(AvroObjectInspectorGenerator.java:83)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.<init>(AvroObjectInspectorGenerator.java:56)
at org.apache.hadoop.hive.serde2.avro.AvroSerDe.initialize(AvroSerDe.java:124)
at
org.apache.spark.sql.hive.HadoopTableReader$$anonfun$5$$anonfun$10.apply(TableReader.scala:251)
at
org.apache.spark.sql.hive.HadoopTableReader$$anonfun$5$$anonfun$10.apply(TableReader.scala:239)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:785)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:785)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Note: Similar issues are already reported in past but still no solution
[https://www.mail-archive.com/user@spark.apache.org/msg61566.html]
was:
When spark SQL is used with Avro-backed HIVE tables, intermittently getting NPE
from
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories.
Root cause is due race condition in hive 1.2.1 jar used in Spark SQL .
In HIVE 2.3 this issue has been fixed (HIVE JIRA:
https://issues.apache.org/jira/browse/HIVE-16175. ), since Spark is still using
Hive 1.2.1 jars we are still getting into race condition.
One workaround is to run Spark with a single task per executor, however it
will slow down the jobs.
Exception stack trace
13/05/07 09:18:39 WARN scheduler.TaskSetManager: Lost task 18.0 in stage 0.0
(TID 18, aiyhyashu.dxc.com): java.lang.NullPointerException
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories(AvroObjectInspectorGenerator.java:142)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:91)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:104)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:104)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:120)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspector(AvroObjectInspectorGenerator.java:83)
at
org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.<init>(AvroObjectInspectorGenerator.java:56)
at org.apache.hadoop.hive.serde2.avro.AvroSerDe.initialize(AvroSerDe.java:124)
at
org.apache.spark.sql.hive.HadoopTableReader$$anonfun$5$$anonfun$10.apply(TableReader.scala:251)
at
org.apache.spark.sql.hive.HadoopTableReader$$anonfun$5$$anonfun$10.apply(TableReader.scala:239)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:785)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:785)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Note: Similar issues are already reported in past but still no solution
[https://www.mail-archive.com/user@spark.apache.org/msg61566.html]
> When spark SQL is used with Avro-backed HIVE tables, NPE from
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories.
> ----------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-20880
> URL: https://issues.apache.org/jira/browse/SPARK-20880
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Vinod KC
> Priority: Minor
>
> When spark SQL is used with Avro-backed HIVE tables, intermittently getting
> NPE from
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories.
> Root cause is due to race condition in hive 1.2.1 jar used in Spark SQL .
> In HIVE 2.3 this issue has been fixed (HIVE JIRA:
> https://issues.apache.org/jira/browse/HIVE-16175. ), since Spark is still
> using Hive 1.2.1 jars we are still getting into a race condition.
> One workaround is to run Spark with a single task per executor, however, it
> will slow down the jobs.
> Exception stack trace
> 13/05/07 09:18:39 WARN scheduler.TaskSetManager: Lost task 18.0 in stage 0.0
> (TID 18, aiyhyashu.dxc.com): java.lang.NullPointerException
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories(AvroObjectInspectorGenerator.java:142)
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:91)
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:104)
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:104)
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspectorWorker(AvroObjectInspectorGenerator.java:120)
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.createObjectInspector(AvroObjectInspectorGenerator.java:83)
> at
> org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.<init>(AvroObjectInspectorGenerator.java:56)
> at
> org.apache.hadoop.hive.serde2.avro.AvroSerDe.initialize(AvroSerDe.java:124)
> at
> org.apache.spark.sql.hive.HadoopTableReader$$anonfun$5$$anonfun$10.apply(TableReader.scala:251)
> at
> org.apache.spark.sql.hive.HadoopTableReader$$anonfun$5$$anonfun$10.apply(TableReader.scala:239)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:785)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:785)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:105)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Note: Similar issues are already reported in past but still no solution
> [https://www.mail-archive.com/user@spark.apache.org/msg61566.html]
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