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Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2015/04/15 22:04:59 UTC
[jira] [Resolved] (SPARK-6887) ColumnBuilder misses FloatType
[ https://issues.apache.org/jira/browse/SPARK-6887?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Armbrust resolved SPARK-6887.
-------------------------------------
Resolution: Fixed
Issue resolved by pull request 5499
[https://github.com/apache/spark/pull/5499]
> ColumnBuilder misses FloatType
> ------------------------------
>
> Key: SPARK-6887
> URL: https://issues.apache.org/jira/browse/SPARK-6887
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.0
> Reporter: Yin Huai
> Assignee: Yin Huai
> Fix For: 1.4.0
>
>
> To reproduce ...
> {code}
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.Row
> val schema = StructType(StructField("c", FloatType, true) :: Nil)
> val rdd = sc.parallelize(1 to 100).map(i => Row(i.toFloat))
> sqlContext.createDataFrame(rdd, schema).registerTempTable("test")
> sqlContext.sql("cache table test")
> sqlContext.table("test").show
> {code}
> The exception is ...
> {code}
> 15/04/13 15:00:12 INFO DAGScheduler: Job 0 failed: collect at SparkPlan.scala:88, took 0.474392 s
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 5 in stage 0.0 failed 1 times, most recent failure: Lost task 5.0 in stage 0.0 (TID 5, localhost): java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.MutableFloat cannot be cast to org.apache.spark.sql.catalyst.expressions.MutableLong
> at org.apache.spark.sql.catalyst.expressions.SpecificMutableRow.setLong(SpecificMutableRow.scala:292)
> at org.apache.spark.sql.columnar.compression.LongDelta$Decoder.next(compressionSchemes.scala:539)
> at org.apache.spark.sql.columnar.compression.CompressibleColumnAccessor$class.extractSingle(CompressibleColumnAccessor.scala:37)
> at org.apache.spark.sql.columnar.NativeColumnAccessor.extractSingle(ColumnAccessor.scala:64)
> at org.apache.spark.sql.columnar.BasicColumnAccessor.extractTo(ColumnAccessor.scala:54)
> at org.apache.spark.sql.columnar.NativeColumnAccessor.org$apache$spark$sql$columnar$NullableColumnAccessor$$super$extractTo(ColumnAccessor.scala:64)
> at org.apache.spark.sql.columnar.NullableColumnAccessor$class.extractTo(NullableColumnAccessor.scala:52)
> at org.apache.spark.sql.columnar.NativeColumnAccessor.extractTo(ColumnAccessor.scala:64)
> at org.apache.spark.sql.columnar.InMemoryColumnarTableScan$$anonfun$8$$anonfun$13$$anon$2.next(InMemoryColumnarTableScan.scala:295)
> at org.apache.spark.sql.columnar.InMemoryColumnarTableScan$$anonfun$8$$anonfun$13$$anon$2.next(InMemoryColumnarTableScan.scala:290)
> at scala.collection.Iterator$$anon$13.next(Iterator.scala:372)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$6.apply(Aggregate.scala:130)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$6.apply(Aggregate.scala:126)
> at org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:640)
> at org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:640)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:64)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:210)
> 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)
> {code}
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