Hello, Spark community! I've been struggling with my job which constantly fails due to inability to uncompress some previously compressed blocks while shuffling data. I use spark 2.2.0 with all the configuration settings left by default (no specific compression codec is specified). I've ascertained that LZ4CompressionCodec is used as a default codec. The job fails as soon as the limit of attempts exceeded with the following message:
Caused by: java.io.IOException: Stream is corrupted at org.apache.spark.io.LZ4BlockInputStream.refill(LZ4BlockInputStream.java:211) at org.apache.spark.io.LZ4BlockInputStream.read(LZ4BlockInputStream.java:125) at org.apache.spark.io.LZ4BlockInputStream.read(LZ4BlockInputStream.java:137) at org.apache.spark.util.Utils$$anonfun$copyStream$1.apply$mcJ$sp(Utils.scala:340) at org.apache.spark.util.Utils$$anonfun$copyStream$1.apply(Utils.scala:327) at org.apache.spark.util.Utils$$anonfun$copyStream$1.apply(Utils.scala:327) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1337) at org.apache.spark.util.Utils$.copyStream(Utils.scala:348) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:395) ... 28 more Caused by: net.jpountz.lz4.LZ4Exception: Error decoding offset 14649 of input buffer Actually, I've stumbled upon a bug [1] as a not fixed yet. Any clue on how to workaround this issue? I've tried the Snappy codec but it fails likewise with a bit different message) org.apache.spark.shuffle.FetchFailedException: failed to uncompress the chunk: FAILED_TO_UNCOMPRESS(5) at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:442) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:403) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:59) at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434) at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395) at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439) at scala.collection.Iterator$JoinIterator.hasNext(Iterator.scala:211) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.Task.run(Task.scala:108) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: java.io.IOException: failed to uncompress the chunk: FAILED_TO_UNCOMPRESS(5) at org.xerial.snappy.SnappyInputStream.hasNextChunk(SnappyInputStream.java:361) at org.xerial.snappy.SnappyInputStream.rawRead(SnappyInputStream.java:158) at org.xerial.snappy.SnappyInputStream.read(SnappyInputStream.java:142) at java.io.InputStream.read(InputStream.java:101) at org.apache.spark.util.Utils$$anonfun$copyStream$1.apply$mcJ$sp(Utils.scala:340) at org.apache.spark.util.Utils$$anonfun$copyStream$1.apply(Utils.scala:327) at org.apache.spark.util.Utils$$anonfun$copyStream$1.apply(Utils.scala:327) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1337) at org.apache.spark.util.Utils$.copyStream(Utils.scala:348) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:395) ... 27 more The option of using no compression seems the only feasible for me at this point. I really need your expert assistance, thank you very much in advance! Any help is greatly appreciated! [1] https://issues.apache.org/jira/browse/SPARK-18105 Cheers, Mike Pryakhin
smime.p7s
Description: S/MIME cryptographic signature