[
https://issues.apache.org/jira/browse/SPARK-8165?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
David Berger closed SPARK-8165.
-------------------------------
> sqlContext.createDataFrame(dataWithoutHeader, csvSchema) type conversion
> error after .cache
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-8165
> URL: https://issues.apache.org/jira/browse/SPARK-8165
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.1
> Reporter: David Berger
> Priority: Major
>
> I create a DF from a simple redshift extract and I use the struct below to
> define the schema:
> val ophanAdImpressions = StructType(Array(
>
> StructField("ad_impression_timestamp",StringType,true),
>
> StructField("page_view_id",StringType,true),
>
> StructField("ad_impression_key",LongType,true),
>
> StructField("ad_position",StringType,true)
> ))
> Before caching the dataframe works fine and I can access the data via the
> schema I've defined.
> BUT once I cache the dataframe I get conversion errors on any datatype apart
> from StringType.
> See below:
> scala> :load dfp_ophan.scalascript
> Loading dfp_ophan.scalascript...
> import com.gu.dfp._
> import com.gu.vladetl._
> Unloading from Redshift with Query:'select
> ad_impression_timestamp,
> rtrim(page_view_id, ophan_visitor_id) as
> page_view_id,
> ad_impression_key,
> ad_position
> from vlad.ad_impression_fact
> where ad_impression_timestamp
> between \'2015-06-07 22:00:00\'
> and \'2015-06-07 23:00:00\''
> Creating Dataframe from CSV without header
> ophanDF: org.apache.spark.sql.DataFrame = [ad_impression_timestamp: string,
> page_view_id: string, ad_impression_key: bigint, ad_position: string]
> scala> ophanDF.schema
> res0: org.apache.spark.sql.types.StructType =
> StructType(StructField(ad_impression_timestamp,StringType,true),
> StructField(page_view_id,StringType,true),
> StructField(ad_impression_key,LongType,true),
> StructField(ad_position,StringType,true))
> scala> ophanDF.count
> res2: Long = 1460053
>
>
>
> scala> ophanDF.select('ad_impression_key).show(5)
> ad_impression_key
> 39470392965
> 39470389269
> 39470389521
> 39470397417
> 39470393217
> scala> ophanDF.cache
> res4: ophanDF.type = [ad_impression_timestamp: string, page_view_id: string,
> ad_impression_key: bigint, ad_position: string]
> scala> ophanDF.select('ad_impression_key).show(5)
> 15/06/08 15:27:30 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 86)
> java.lang.ClassCastException: java.lang.String cannot be cast to
> java.lang.Long
> at scala.runtime.BoxesRunTime.unboxToLong(BoxesRunTime.java:110)
> at
> org.apache.spark.sql.catalyst.expressions.GenericRow.getLong(rows.scala:88)
> at
> org.apache.spark.sql.columnar.LongColumnStats.gatherStats(ColumnStats.scala:140)
>
> at
> org.apache.spark.sql.columnar.NullableColumnBuilder$class.appendFrom(NullableColumnBuilder.scala:56)
>
> at
> org.apache.spark.sql.columnar.NativeColumnBuilder.org$apache$spark$sql$columnar$compression$CompressibleColumnBuilder$$super$appendFrom(ColumnBuilder.scala:87)
>
> at
> org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder$class.appendFrom(CompressibleColumnBuilder.scala:78)
>
> at
> org.apache.spark.sql.columnar.NativeColumnBuilder.appendFrom(ColumnBuilder.scala:87)
>
> at
> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:141)
>
> at
> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:117)
>
> at
> org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:249)
> at
> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:172)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:79)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:242)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:64)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>
> at java.lang.Thread.run(Thread.java:745)
> 15/06/08 15:27:30 ERROR TaskSetManager: Task 0 in stage 3.0 failed 1 times;
> aborting job
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage 3.0
> (TID 86, localhost): java.lang.ClassCastException: java.lang.String cannot be
> cast to java.lang.Long
> at scala.runtime.BoxesRunTime.unboxToLong(BoxesRunTime.java:110)
> at
> org.apache.spark.sql.catalyst.expressions.GenericRow.getLong(rows.scala:88)
> at
> org.apache.spark.sql.columnar.LongColumnStats.gatherStats(ColumnStats.scala:140)
>
> at
> org.apache.spark.sql.columnar.NullableColumnBuilder$class.appendFrom(NullableColumnBuilder.scala:56)
>
> at
> org.apache.spark.sql.columnar.NativeColumnBuilder.org$apache$spark$sql$columnar$compression$CompressibleColumnBuilder$$super$appendFrom(ColumnBuilder.scala:87)
>
> at
> org.apache.spark.sql.columnar.compression.CompressibleColumnBuilder$class.appendFrom(CompressibleColumnBuilder.scala:78)
>
> at
> org.apache.spark.sql.columnar.NativeColumnBuilder.appendFrom(ColumnBuilder.scala:87)
>
> at
> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:141)
>
> at
> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.next(InMemoryColumnarTableScan.scala:117)
>
> at
> org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:249)
> at
> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:172)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:79)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:242)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:64)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1204)
>
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
>
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
>
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
>
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
>
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
>
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
>
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
>
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> scala>
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