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Posted to issues@spark.apache.org by "Liang-Chi Hsieh (JIRA)" <ji...@apache.org> on 2015/06/20 19:31:00 UTC
[jira] [Commented] (SPARK-7626) Actions on DataFrame created from
HIVE table with newly added column throw NPE
[ https://issues.apache.org/jira/browse/SPARK-7626?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14594698#comment-14594698 ]
Liang-Chi Hsieh commented on SPARK-7626:
----------------------------------------
By some testing and searching codes, I just found that this problem is solved in another PR. The reason is described in this PR (#6146). So I think this ticket can be closed now.
> Actions on DataFrame created from HIVE table with newly added column throw NPE
> -------------------------------------------------------------------------------
>
> Key: SPARK-7626
> URL: https://issues.apache.org/jira/browse/SPARK-7626
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.1
> Reporter: Zhiyang Guo
>
> We recently added a new column page_context to a hive table named "clicks", partitioned by data_date. This leads to NPE being thrown on DataFrame created on older partitions without this column populated. For example:
> {code}
> val hc = new HiveContext(sc)
> val clk = hc.sql("select * from clicks where data_date=20150302")
> clk.show()
> {code}
> throws the following error msg:
> {code}
> java.lang.RuntimeException: cannot find field page_context from [0:log_format_number, .....]
> at org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils.getStandardStructFieldRef(ObjectInspectorUtils.java:415)
> at org.apache.hadoop.hive.serde2.lazy.objectinspector.LazySimpleStructObjectInspector.getStructFieldRef(LazySimpleStructObjectInspector.java:173)
> at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$12.apply(TableReader.scala:278)
> at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$12.apply(TableReader.scala:277)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.hive.HadoopTableReader$.fillObject(TableReader.scala:277)
> at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$4$$anonfun$9.apply(TableReader.scala:194)
> at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$4$$anonfun$9.apply(TableReader.scala:188)
> at org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:634)
> at org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:634)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.UnionRDD.compute(UnionRDD.scala:87)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:64)
> {code}
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