[SPARK-18965] wholeTextFiles() is not able to read large files

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Invalid
• Affects Version/s: 1.6.2
• Component/s: Spark Core
• Labels: ReadFile

Environment

All Platforms

• Flags: Patch, Important
• Assignee: Unassigned
• Reporter: Pradeep Misra
• Shepherd: Pradeep Misra
• Created: 21/Dec/16 15:42
• Updated: 09/Oct/17 12:17
• Resolved: 21/Dec/16 15:43

Description

While working on wholeTextFiles() of size 134738099 (gz compressed) spark throws an OOM error.

ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.OutOfMemoryError
at java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at org.spark-project.guava.io.ByteStreams.copy(ByteStreams.java:211)
at org.spark-project.guava.io.ByteStreams.toByteArray(ByteStreams.java:252)
at org.apache.spark.input.WholeTextFileRecordReader.nextKeyValue(WholeTextFileRecordReader.scala:81)
at org.apache.hadoop.mapreduce.lib.input.CombineFileRecordReader.nextKeyValue(CombineFileRecordReader.java:65)
at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:168)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1631)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1164)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1164)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1882)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1882)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
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)
16/11/30 14:25:36 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[Executor task launch worker-0,5,main]
java.lang.OutOfMemoryError
at java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at org.spark-project.guava.io.ByteStreams.copy(ByteStreams.java:211)
at org.spark-project.guava.io.ByteStreams.toByteArray(ByteStreams.java:252)
at org.apache.spark.input.WholeTextFileRecordReader.nextKeyValue(WholeTextFileRecordReader.scala:81)
at org.apache.hadoop.mapreduce.lib.input.CombineFileRecordReader.nextKeyValue(CombineFileRecordReader.java:65)
at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:168)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1631)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1164)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1164)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1882)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1882)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
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)
16/11/30 14:25:36 INFO SparkContext: Invoking stop() from shutdown hook
16/11/30 14:25:36 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.OutOfMemoryError
at java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at org.spark-project.guava.io.ByteStreams.copy(ByteStreams.java:211)
at org.spark-project.guava.io.ByteStreams.toByteArray(ByteStreams.java:252)
at org.apache.spark.input.WholeTextFileRecordReader.nextKeyValue(WholeTextFileRecordReader.scala:81)
at org.apache.hadoop.mapreduce.lib.input.CombineFileRecordReader.nextKeyValue(CombineFileRecordReader.java:65)
at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:168)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1631)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1164)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1164)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1882)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1882)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
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)