hadoop-mapreduce-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Created] (MAPREDUCE-5893) CBZip2InputStream is not threadsafe
Date Fri, 16 May 2014 11:13:09 GMT
Xiangrui Meng created MAPREDUCE-5893:
----------------------------------------

             Summary: CBZip2InputStream is not threadsafe
                 Key: MAPREDUCE-5893
                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-5893
             Project: Hadoop Map/Reduce
          Issue Type: Improvement
          Components: mrv1, mrv2
    Affects Versions: 2.2.0, 1.2.1
            Reporter: Xiangrui Meng


Hadoop uses CBZip2InputStream to decode bzip2 files. However, the implementation is not threadsafe.
This is not a really problem for Hadoop MapReduce because Hadoop runs each task in a separate
JVM. But for other libraries that utilize multithreading and use Hadoop's InputFormat, e.g.,
Spark, it will cause exceptions like the following:

{code}
java.lang.ArrayIndexOutOfBoundsException: 6 org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.recvDecodingTables(CBZip2InputStream.java:729)
org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode(CBZip2InputStream.java:795)
org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.initBlock(CBZip2InputStream.java:499)
org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.changeStateToProcessABlock(CBZip2InputStream.java:330)
org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.read(CBZip2InputStream.java:394) org.apache.hadoop.io.compress.BZip2Codec$BZip2CompressionInputStream.read(BZip2Codec.java:428)
java.io.InputStream.read(InputStream.java:101) org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:205)
org.apache.hadoop.util.LineReader.readLine(LineReader.java:169) org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:176)
org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:43) org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:198)
org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:181) org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71)
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:35) scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1000) org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:847)
org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:847) org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1077)
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1077) org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
org.apache.spark.scheduler.Task.run(Task.scala:51) org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:724)
{code}



--
This message was sent by Atlassian JIRA
(v6.2#6252)

Mime
View raw message