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Posted to issues@spark.apache.org by "Shixiong Zhu (JIRA)" <ji...@apache.org> on 2017/03/09 18:49:38 UTC
[jira] [Created] (SPARK-19885) The config ignoreCorruptFiles
doesn't work for CSV
Shixiong Zhu created SPARK-19885:
------------------------------------
Summary: The config ignoreCorruptFiles doesn't work for CSV
Key: SPARK-19885
URL: https://issues.apache.org/jira/browse/SPARK-19885
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0
Reporter: Shixiong Zhu
CSVFileFormat.inferSchema doesn't use FileScanRDD so the SQL "ignoreCorruptFiles" doesn't work.
{code}
java.io.EOFException: Unexpected end of input stream
at org.apache.hadoop.io.compress.DecompressorStream.decompress(DecompressorStream.java:145)
at org.apache.hadoop.io.compress.DecompressorStream.read(DecompressorStream.java:85)
at java.io.InputStream.read(InputStream.java:101)
at org.apache.hadoop.util.LineReader.fillBuffer(LineReader.java:180)
at org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:216)
at org.apache.hadoop.util.LineReader.readLine(LineReader.java:174)
at org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:248)
at org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:48)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:266)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:211)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.aggregate(TraversableOnce.scala:214)
at scala.collection.AbstractIterator.aggregate(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$aggregate$1$$anonfun$22.apply(RDD.scala:1112)
at org.apache.spark.rdd.RDD$$anonfun$aggregate$1$$anonfun$22.apply(RDD.scala:1112)
at org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1980)
at org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1980)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1981)
at org.apache.spark.rdd.RDD$$anonfun$aggregate$1.apply(RDD.scala:1114)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.aggregate(RDD.scala:1107)
at org.apache.spark.sql.execution.datasources.csv.CSVInferSchema$.infer(CSVInferSchema.scala:47)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:67)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$7.apply(DataSource.scala:174)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$7.apply(DataSource.scala:174)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:173)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:377)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:135)
{code}
Right now a workaround is also setting "spark.files.ignoreCorruptFiles" to true.
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