Hi Andrew, I verified that this is due to thread safety. I changed SPARK_WORKER_CORES to 1 in spark-env.sh, so there is only 1 thread per worker. Then I can load the file without any problem with different values of minPartitions. I will submit a JIRA to both Spark and Hadoop.
Best, Xiangrui On Thu, May 15, 2014 at 3:48 PM, Xiangrui Meng <men...@gmail.com> wrote: > Hi Andrew, > > Could you try varying the minPartitions parameter? For example: > > val r = sc.textFile("/user/aa/myfile.bz2", 4).count > val r = sc.textFile("/user/aa/myfile.bz2", 8).count > > Best, > Xiangrui > > On Tue, May 13, 2014 at 9:08 AM, Xiangrui Meng <men...@gmail.com> wrote: >> Which hadoop version did you use? I'm not sure whether Hadoop v2 fixes >> the problem you described, but it does contain several fixes to bzip2 >> format. -Xiangrui >> >> On Wed, May 7, 2014 at 9:19 PM, Andrew Ash <and...@andrewash.com> wrote: >>> Hi all, >>> >>> Is anyone reading and writing to .bz2 files stored in HDFS from Spark with >>> success? >>> >>> >>> I'm finding the following results on a recent commit (756c96 from 24hr ago) >>> and CDH 4.4.0: >>> >>> Works: val r = sc.textFile("/user/aa/myfile.bz2").count >>> Doesn't work: val r = sc.textFile("/user/aa/myfile.bz2").map((s:String) => >>> s+"| " ).count >>> >>> Specifically, I'm getting an exception coming out of the bzip2 libraries >>> (see below stacktraces), which is unusual because I'm able to read from that >>> file without an issue using the same libraries via Pig. It was originally >>> created from Pig as well. >>> >>> Digging a little deeper I found this line in the .bz2 decompressor's javadoc >>> for CBZip2InputStream: >>> >>> "Instances of this class are not threadsafe." [source] >>> >>> >>> My current working theory is that Spark has a much higher level of >>> parallelism than Pig/Hadoop does and thus I get these wild IndexOutOfBounds >>> exceptions much more frequently (as in can't finish a run over a little 2M >>> row file) vs hardly at all in other libraries. >>> >>> The only other reference I could find to the issue was in presto-users, but >>> the recommendation to leave .bz2 for .lzo doesn't help if I actually do want >>> the higher compression levels of .bz2. >>> >>> >>> Would love to hear if I have some kind of configuration issue or if there's >>> a bug in .bz2 that's fixed in later versions of CDH, or generally any other >>> thoughts on the issue. >>> >>> >>> Thanks! >>> Andrew >>> >>> >>> >>> Below are examples of some exceptions I'm getting: >>> >>> 14/05/07 15:09:49 WARN scheduler.TaskSetManager: Loss was due to >>> java.lang.ArrayIndexOutOfBoundsException >>> java.lang.ArrayIndexOutOfBoundsException: 65535 >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.hbCreateDecodeTables(CBZip2InputStream.java:663) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.createHuffmanDecodingTables(CBZip2InputStream.java:790) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.recvDecodingTables(CBZip2InputStream.java:762) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode(CBZip2InputStream.java:798) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.initBlock(CBZip2InputStream.java:502) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.changeStateToProcessABlock(CBZip2InputStream.java:333) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.read(CBZip2InputStream.java:397) >>> at >>> org.apache.hadoop.io.compress.BZip2Codec$BZip2CompressionInputStream.read(BZip2Codec.java:426) >>> at java.io.InputStream.read(InputStream.java:101) >>> at >>> org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:209) >>> at org.apache.hadoop.util.LineReader.readLine(LineReader.java:173) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:203) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:43) >>> >>> >>> >>> >>> java.lang.ArrayIndexOutOfBoundsException: 900000 >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode(CBZip2InputStream.java:900) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.initBlock(CBZip2InputStream.java:502) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.changeStateToProcessABlock(CBZip2InputStream.java:333) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.read(CBZip2InputStream.java:397) >>> at >>> org.apache.hadoop.io.compress.BZip2Codec$BZip2CompressionInputStream.read(BZip2Codec.java:426) >>> at java.io.InputStream.read(InputStream.java:101) >>> at >>> org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:209) >>> at org.apache.hadoop.util.LineReader.readLine(LineReader.java:173) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:203) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:43) >>> at >>> org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:198) >>> at >>> org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:181) >>> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) >>> at >>> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:35) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$class.foreach(Iterator.scala:727) >>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) >>> at >>> org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$countPartition$1(RDD.scala:868) >>> >>> >>> >>> java.lang.ArrayIndexOutOfBoundsException: -921878509 >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode0(CBZip2InputStream.java:1011) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode(CBZip2InputStream.java:826) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.initBlock(CBZip2InputStream.java:502) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.changeStateToProcessABlock(CBZip2InputStream.java:333) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.read(CBZip2InputStream.java:397) >>> at >>> org.apache.hadoop.io.compress.BZip2Codec$BZip2CompressionInputStream.read(BZip2Codec.java:432) >>> at java.io.InputStream.read(InputStream.java:101) >>> at >>> org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:209) >>> at org.apache.hadoop.util.LineReader.readLine(LineReader.java:173) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:203) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:43) >>> at >>> org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:198) >>> at >>> org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:181) >>> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) >>> at >>> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:35) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$class.foreach(Iterator.scala:727) >>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) >>> at >>> org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$countPartition$1(RDD.scala:868) >>> at org.apache.spark.rdd.RDD$$anonfun$24.apply(RDD.scala:879) >>> at org.apache.spark.rdd.RDD$$anonfun$24.apply(RDD.scala:879) >>> at org.apache.spark.rdd.RDD$$anonfun$12.apply(RDD.scala:548) >>> at org.apache.spark.rdd.RDD$$anonfun$12.apply(RDD.scala:548) >>> >>> >>> >>> java.lang.ArrayIndexOutOfBoundsException: -1321104434 >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode0(CBZip2InputStream.java:1011) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.getAndMoveToFrontDecode(CBZip2InputStream.java:826) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.initBlock(CBZip2InputStream.java:502) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.changeStateToProcessABlock(CBZip2InputStream.java:333) >>> at >>> org.apache.hadoop.io.compress.bzip2.CBZip2InputStream.read(CBZip2InputStream.java:397) >>> at >>> org.apache.hadoop.io.compress.BZip2Codec$BZip2CompressionInputStream.read(BZip2Codec.java:426) >>> at java.io.InputStream.read(InputStream.java:101) >>> at >>> org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:209) >>> at org.apache.hadoop.util.LineReader.readLine(LineReader.java:173) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:203) >>> at >>> org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:43) >>> at >>> org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:198) >>> at >>> org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:181) >>> at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) >>> at >>> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:35) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327) >>> at scala.collection.Iterator$class.foreach(Iterator.scala:727) >>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) >>> at >>> org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$countPartition$1(RDD.scala:868)