[
https://issues.apache.org/jira/browse/SPARK-3978?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14791171#comment-14791171
]
Nilesh Barge commented on SPARK-3978:
-------------------------------------
I tested with the latest Spark 1.5 release...
I got the source
(http://www.apache.org/dyn/closer.lua/spark/spark-1.5.0/spark-1.5.0.tgz) and
then build with "mvn -Phadoop-2.6 -Dhadoop.version=2.6.0 -Phive
-Phive-thriftserver -DskipTests clean package" command... and then ran my
original tests...
> Schema change on Spark-Hive (Parquet file format) table not working
> -------------------------------------------------------------------
>
> Key: SPARK-3978
> URL: https://issues.apache.org/jira/browse/SPARK-3978
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.1.0
> Reporter: Nilesh Barge
> Assignee: Alex Rovner
> Fix For: 1.5.0
>
>
> On following releases:
> Spark 1.1.0 (built using sbt/sbt -Dhadoop.version=2.2.0 -Phive assembly) ,
> Apache HDFS 2.2
> Spark job is able to create/add/read data in hive, parquet formatted, tables
> using HiveContext.
> But, after changing schema, spark job is not able to read data and throws
> following exception:
> java.lang.ArrayIndexOutOfBoundsException: 2
> at
> org.apache.hadoop.hive.ql.io.parquet.serde.ArrayWritableObjectInspector.getStructFieldData(ArrayWritableObjectInspector.java:127)
>
> at
> org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$1.apply(TableReader.scala:284)
>
> at
> org.apache.spark.sql.hive.HadoopTableReader$$anonfun$fillObject$1.apply(TableReader.scala:278)
>
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at
> scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at org.apache.spark.rdd.RDD$$anonfun$16.apply(RDD.scala:774)
> at org.apache.spark.rdd.RDD$$anonfun$16.apply(RDD.scala:774)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1121)
>
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1121)
>
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62)
> at org.apache.spark.scheduler.Task.run(Task.scala:54)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177)
> 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:744)
> code snippet in short:
> hiveContext.sql("CREATE EXTERNAL TABLE IF NOT EXISTS people_table (name
> String, age INT) ROW FORMAT SERDE 'parquet.hive.serde.ParquetHiveSerDe'
> STORED AS INPUTFORMAT 'parquet.hive.DeprecatedParquetInputFormat'
> OUTPUTFORMAT 'parquet.hive.DeprecatedParquetOutputFormat'");
> hiveContext.sql("INSERT INTO TABLE people_table SELECT name, age FROM
> temp_table_people1");
> hiveContext.sql("SELECT * FROM people_table"); //Here, data read was
> successful.
> hiveContext.sql("ALTER TABLE people_table ADD COLUMNS (gender STRING)");
> hiveContext.sql("SELECT * FROM people_table"); //Not able to read existing
> data and ArrayIndexOutOfBoundsException is thrown.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
