[ 
https://issues.apache.org/jira/browse/SPARK-12947?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Sam Stoelinga updated SPARK-12947:
----------------------------------
    Component/s: SQL

> Spark with Swift throws EOFException when reading parquet file
> --------------------------------------------------------------
>
>                 Key: SPARK-12947
>                 URL: https://issues.apache.org/jira/browse/SPARK-12947
>             Project: Spark
>          Issue Type: Bug
>          Components: ML, SQL
>    Affects Versions: 1.6.0
>         Environment: Spark 1.6.0-SNAPSHOT
>            Reporter: Sam Stoelinga
>
> I'm using Swift as underlying storage for my spark jobs but it sometimes 
> throws EOFExceptions for some parts of the data.
> Another user has hit the same issue: 
> http://stackoverflow.com/questions/32400137/spark-swift-integration-parquet
> Code to reproduce:
> ```
>     val features = sqlContext.read.parquet(featurePath)
>     // Flatten the features into the array exploded
>     val exploded = 
> features.select(explode(features("features"))).toDF("features")
>     val kmeans = new KMeans()
>       .setK(k)
>       .setFeaturesCol("features")
>       .setPredictionCol("prediction")
>     val model = kmeans.fit(exploded)
> ```
> val features is a dataframe with 2 columns: 
> image: String, features: Array[Vector]
> val exploded is a dataframe with a single column:
> features: Vector
> The following exception is shown when running takeSample on a large dataset 
> saved as parquet file (~1+GB):
> java.io.EOFException
>       at java.io.DataInputStream.readFully(DataInputStream.java:197)
>       at java.io.DataInputStream.readFully(DataInputStream.java:169)
>       at 
> org.apache.parquet.hadoop.ParquetFileReader$ConsecutiveChunkList.readAll(ParquetFileReader.java:756)
>       at 
> org.apache.parquet.hadoop.ParquetFileReader.readNextRowGroup(ParquetFileReader.java:494)
>       at 
> org.apache.parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:127)
>       at 
> org.apache.parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:208)
>       at 
> org.apache.parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:201)
>       at 
> org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.hasNext(SqlNewHadoopRDD.scala:168)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>       at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
>       at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:350)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>       at 
> org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$30$$anon$1.hasNext(RDD.scala:827)
>       at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>       at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1563)
>       at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1119)
>       at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1119)
>       at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1840)
>       at 
> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1840)
>       at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>       at org.apache.spark.scheduler.Task.run(Task.scala:88)
>       at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>       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)



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to