[jira] [Comment Edited] (SPARK-20880) When spark SQL is used with Avro-backed HIVE tables, NPE from org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories.
[ https://issues.apache.org/jira/browse/SPARK-20880?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16957491#comment-16957491 ] Benjamyn Ward edited comment on SPARK-20880 at 10/23/19 2:05 AM: - Gentle ping. While the description states that the issue is fixed in Hive 2.2, based on the Hive Jira, the issue was fixed in version 2.3.0. * https://issues.apache.org/jira/browse/HIVE-16175 I am also running into this issue. I am going to try to work around the issue by using the **extraClassPath** that includes Hive SerDe 2.3.x, but I'm not sure if this will work or not. A much better solution would be to upgrade Spark's library dependencies. was (Author: errorsandglitches): Gentle ping. While the description states that the issue is fixed in Hive 2.2, based on the Hive Jira, the issue was fixed in version 2.3. * https://issues.apache.org/jira/browse/HIVE-16175 I am also running into this issue. I am going to try to work around the issue by using the **extraClassPath** that includes Hive SerDe 2.3.x, but I'm not sure if this will work or not. A much better solution would be to upgrade Spark's library dependencies. > 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 race condition in hive 1.2.1 jar used in Spark SQL . > In HIVE 2.2 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.(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
[jira] [Commented] (SPARK-20880) When spark SQL is used with Avro-backed HIVE tables, NPE from org.apache.hadoop.hive.serde2.avro.AvroObjectInspectorGenerator.supportedCategories.
[ https://issues.apache.org/jira/browse/SPARK-20880?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16957491#comment-16957491 ] Benjamyn Ward commented on SPARK-20880: --- Gentle ping. While the description states that the issue is fixed in Hive 2.2, based on the Hive Jira, the issue was fixed in version 2.3. * https://issues.apache.org/jira/browse/HIVE-16175 I am also running into this issue. I am going to try to work around the issue by using the **extraClassPath** that includes Hive SerDe 2.3.x, but I'm not sure if this will work or not. A much better solution would be to upgrade Spark's library dependencies. > 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 race condition in hive 1.2.1 jar used in Spark SQL . > In HIVE 2.2 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.(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
