Spark: Self-suppression not permitted when writing big file to HDFS - apache-spark

I'm writing a large file to HDFS using spark. Basically what I was doing was to join 3 big files and then convert the result dataframe to json using toJSON() and then use saveAsTextFile to save it to HDFS. The final file to write is approximately 4TB. The application run pretty slow(as I should expected?) and after 6 hours it throwed an exception java.lang.IllegalArgumentException: Self-suppression not permitted. The detailed failure reason are copied from the monitoring page to below:
Job aborted due to stage failure: Task 37 in stage 6.0 failed 4 times, most recent failure: Lost task 37.3 in stage 6.0 (TID 361, 192.168.10.149): java.lang.IllegalArgumentException: Self-suppression not permitted
at java.lang.Throwable.addSuppressed(Throwable.java:1043)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1219)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1116)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1095)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /user/dawei/upid_json_all/_temporary/0/_temporary/attempt_201512210857_0006_m_000037_361/part-00037 could only be replicated to 0 nodes instead of minReplication (=1). There are 5 datanode(s) running and no node(s) are excluded in this operation.
at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1562)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3245)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:663)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:482)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:619)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:962)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2040)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2036)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2034)
at org.apache.hadoop.ipc.Client.call(Client.java:1468)
at org.apache.hadoop.ipc.Client.call(Client.java:1399)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)
at com.sun.proxy.$Proxy14.addBlock(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:399)
at sun.reflect.GeneratedMethodAccessor119.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy15.addBlock(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1532)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1349)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:588)
Driver stacktrace:
can anyone tell me what causes this problem and how could I solve it?

From this error:
Caused by: org.apache.hadoop.ipc.RemoteException(java.io.IOException): File
/user/dawei/upid_json_all/_temporary/0/_temporary/attempt_201512210857_0006_m_000037_361/
part-00037 could only be replicated to 0 nodes instead of minReplication (=1).
There are 5 datanode(s) running and no node(s) are excluded in this operation.
It seems that replication is not happening. If you fix this error, things may fall in right place.
It may be due to below issues:
Inconsistency in your datanodes: Restart your Hadoop cluster and see if this solves your problem
Communication between datanodes and namenode: Network connectivity Issues and permission/firewall access issues related to port accessibility.
Disk space may be full on datanode
Datanode may be busy or unresponsive
Invalid configuration like Negative block size configuration
Have a look at related SE questions too on this topic.
HDFS error: could only be replicated to 0 nodes, instead of 1

The actual error could be hidden behind this weird 'self-supression' error.
When you don't see any clue in the yarn logs, check the Spark UI once. You will have some clue on the stage failures there.
It would more likely be some memory spill or something similar.

Related

How to disable disk writes for shuffle files?

Hi We have spark cluster , during spark job execution , am getting sparkoutofmemory when writing intermediate data to spark.local.dir location , but when am seeing their is more than double memory for executor unused , so instead of writing to that dir , can we store the data into memory itself ?
Below the exception details
Job aborted due to stage failure: Task 134555 in stage 32.0 failed 4 times, most recent failure: Lost task 134555.3 in stage 32.0 (TID 151065, <<some worker node IP>>, executor 318): java.io.FileNotFoundException: /opt/spark/tmp/spark-98331af4-b923-4342-ae3e-93e764b02d4a/executor-a5874092-943d-4b57-b1d0-eab05a3d36c5/blockmgr-17e989d8-4657-4a4e-bc93-ea075cb45f61/0f/temp_shuffle_1f574b0e-617b-46db-a558-9937a911c90a (No space left on device)
at java.io.FileOutputStream.open0(Native Method)
at java.io.FileOutputStream.open(FileOutputStream.java:270)
at java.io.FileOutputStream.<init>(FileOutputStream.java:213)
at org.apache.spark.storage.DiskBlockObjectWriter.initialize(DiskBlockObjectWriter.scala:103)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:116)
at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:249)
at org.apache.spark.shuffle.sort.ShuffleExternalSorter.writeSortedFile(ShuffleExternalSorter.java:211)
at org.apache.spark.shuffle.sort.ShuffleExternalSorter.closeAndGetSpills(ShuffleExternalSorter.java:419)
at org.apache.spark.shuffle.sort.UnsafeShuffleWriter.closeAndWriteOutput(UnsafeShuffleWriter.java:230)
at org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:190)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
Below the screen shot of the failing stage
My understanding is that there's no way to disable disk writes.
ShuffleMapTasks have to write intermediate shuffle map output files (shuffle blocks) to spark.local.dir directory so reducers (of this shuffle stage) can do their job (no pun intended).
You could give External Shuffle Service a try to reduce disk usage (so rather than every executor would manage their own shuffle-related directories they could offload it). You can read about it a bit in Dynamic Resource Allocation.

Unable to save RDD to HDFS in Apache Spark

I am getting the following error while trying to save the RDD to HDFS
17/09/13 17:06:42 WARN TaskSetManager: Lost task 7340.0 in stage 16.0 (TID 100118, XXXXXX.com, executor 2358): java.io.IOException: Failing write. Tried pipeline recovery 5 times without success.
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.processDatanodeError(DFSOutputStream.java:865)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:401)
Suppressed: java.lang.IllegalArgumentException: Self-suppression not permitted
at java.lang.Throwable.addSuppressed(Throwable.java:1043)
at java.io.FilterOutputStream.close(FilterOutputStream.java:159)
at org.apache.hadoop.mapred.TextOutputFormat$LineRecordWriter.close(TextOutputFormat.java:108)
at org.apache.spark.SparkHadoopWriter.close(SparkHadoopWriter.scala:102)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13$$anonfun$apply$8.apply$mcV$sp(PairRDDFunctions.scala:1218)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1359)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1218)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1197)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
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:748)
[CIRCULAR REFERENCE:java.io.IOException: Failing write. Tried pipeline recovery 5 times without success.]
the final task in the stage is .saveAsTextFile(), In the Spark UI i am able to see that other tasks prior to .saveAsTextFile() finishes successfully. Using Spark 2.0.0 in YARN mode.
EDIT:
I have already seen the answer on Spark: Self-suppression not permitted when writing big file to HDFS and i made sure that issues mentioned in that answer were not the case here.

Making Spark app work on m4 instances

I have a pyspark application running on EMR (5.7.0) which processes about 140M json records. Nothing terribly fancy outside of the size of the dataset -- main operations are map, filter, count, repartitionAndSort, and mapPartition.
This app runs on a cluster of 40 m3.2xlarge instances, but I wanted to try it on the m4 family (since I get access to beefier machines that way).
However, the executors fall over the the cluster is rendered inoperable (If I rerun my application, it fails far earlier with no available executors).
Here's the stack trace I get on failure.
17/08/26 15:51:15 WARN TaskSetManager: Lost task 1118.0 in stage 145.0 (TID 72871, ip-172-22-247-134.ec2.internal, executor 91): java.lang.IllegalArgumentException: Self-suppression not permitted
at java.lang.Throwable.addSuppressed(Throwable.java:1043)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1316)
at org.apache.spark.rdd.ReliableCheckpointRDD$.writePartitionToCheckpointFile(ReliableCheckpointRDD.scala:182)
at org.apache.spark.rdd.ReliableCheckpointRDD$$anonfun$writeRDDToCheckpointDirectory$1.apply(ReliableCheckpointRDD.scala:137)
at org.apache.spark.rdd.ReliableCheckpointRDD$$anonfun$writeRDDToCheckpointDirectory$1.apply(ReliableCheckpointRDD.scala:137)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /checkpoints/48b56f21-7f74-429c-934c-0aea983c0175/rdd-359/.part-01118-attempt-0 could only be replicated to 0 nodes instead of minReplication (=1). There are 36 datanode(s) running and no node(s) are excluded in this operation.
at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1580)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getNewBlockTargets(FSNamesystem.java:3107)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3031)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:725)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:492)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:982)
Any help? Seems very weird that this can't run on m4-class machines.

FileNotFoundException during compaction

All of my nodes are throwing a FileNotFoundException during compaction. As such, not a single compaction (auto, manual) can finish and my SSTable count is now in the thousands for a single CF (CQL3).
nodetool compactionstats shows hundreds of pending tasks in each node but nothing is being processed.
Below is an example log of the exception:
Error occurred during compaction
java.util.concurrent.ExecutionException: java.lang.RuntimeException: java.io.FileNotFoundException: /home/cassandra/data/mtg_keywords_v5/keyword_organic_results/mtg_keywords_v5-keyword_organic_results-jb-31111-Data.db (No such file or directory)
at java.util.concurrent.FutureTask.report(FutureTask.java:122)
at java.util.concurrent.FutureTask.get(FutureTask.java:188)
at org.apache.cassandra.db.compaction.CompactionManager.performMaximal(CompactionManager.java:281)
at org.apache.cassandra.db.ColumnFamilyStore.forceMajorCompaction(ColumnFamilyStore.java:1935)
at org.apache.cassandra.service.StorageService.forceKeyspaceCompaction(StorageService.java:2210)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at sun.reflect.misc.Trampoline.invoke(MethodUtil.java:75)
at sun.reflect.GeneratedMethodAccessor14.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at sun.reflect.misc.MethodUtil.invoke(MethodUtil.java:279)
at com.sun.jmx.mbeanserver.StandardMBeanIntrospector.invokeM2(StandardMBeanIntrospector.java:112)
at com.sun.jmx.mbeanserver.StandardMBeanIntrospector.invokeM2(StandardMBeanIntrospector.java:46)
at com.sun.jmx.mbeanserver.MBeanIntrospector.invokeM(MBeanIntrospector.java:237)
at com.sun.jmx.mbeanserver.PerInterface.invoke(PerInterface.java:138)
at com.sun.jmx.mbeanserver.MBeanSupport.invoke(MBeanSupport.java:252)
at com.sun.jmx.interceptor.DefaultMBeanServerInterceptor.invoke(DefaultMBeanServerInterceptor.java:819)
at com.sun.jmx.mbeanserver.JmxMBeanServer.invoke(JmxMBeanServer.java:801)
at javax.management.remote.rmi.RMIConnectionImpl.doOperation(RMIConnectionImpl.java:1487)
at javax.management.remote.rmi.RMIConnectionImpl.access$300(RMIConnectionImpl.java:97)
at javax.management.remote.rmi.RMIConnectionImpl$PrivilegedOperation.run(RMIConnectionImpl.java:1328)
at javax.management.remote.rmi.RMIConnectionImpl.doPrivilegedOperation(RMIConnectionImpl.java:1420)
at javax.management.remote.rmi.RMIConnectionImpl.invoke(RMIConnectionImpl.java:848)
at sun.reflect.GeneratedMethodAccessor40.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at sun.rmi.server.UnicastServerRef.dispatch(UnicastServerRef.java:322)
at sun.rmi.transport.Transport$1.run(Transport.java:177)
at sun.rmi.transport.Transport$1.run(Transport.java:174)
at java.security.AccessController.doPrivileged(Native Method)
at sun.rmi.transport.Transport.serviceCall(Transport.java:173)
at sun.rmi.transport.tcp.TCPTransport.handleMessages(TCPTransport.java:556)
at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.run0(TCPTransport.java:811)
at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.run(TCPTransport.java:670)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException: java.io.FileNotFoundException: /home/cassandra/data/mtg_keywords_v5/keyword_organic_results/mtg_keywords_v5-keyword_organic_results-jb-31111-Data.db (No such file or directory)
at org.apache.cassandra.io.compress.CompressedThrottledReader.open(CompressedThrottledReader.java:52)
at org.apache.cassandra.io.sstable.SSTableReader.openDataReader(SSTableReader.java:1355)
at org.apache.cassandra.io.sstable.SSTableScanner.<init>(SSTableScanner.java:67)
at org.apache.cassandra.io.sstable.SSTableReader.getScanner(SSTableReader.java:1161)
at org.apache.cassandra.io.sstable.SSTableReader.getScanner(SSTableReader.java:1173)
at org.apache.cassandra.db.compaction.AbstractCompactionStrategy.getScanners(AbstractCompactionStrategy.java:252)
at org.apache.cassandra.db.compaction.AbstractCompactionStrategy.getScanners(AbstractCompactionStrategy.java:258)
at org.apache.cassandra.db.compaction.CompactionTask.runWith(CompactionTask.java:126)
at org.apache.cassandra.io.util.DiskAwareRunnable.runMayThrow(DiskAwareRunnable.java:48)
at org.apache.cassandra.utils.WrappedRunnable.run(WrappedRunnable.java:28)
at org.apache.cassandra.db.compaction.CompactionTask.executeInternal(CompactionTask.java:60)
at org.apache.cassandra.db.compaction.AbstractCompactionTask.execute(AbstractCompactionTask.java:59)
at org.apache.cassandra.db.compaction.CompactionManager$6.runMayThrow(CompactionManager.java:296)
at org.apache.cassandra.utils.WrappedRunnable.run(WrappedRunnable.java:28)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
... 3 more
Caused by: java.io.FileNotFoundException: /home/cassandra/data/mtg_keywords_v5/keyword_organic_results/mtg_keywords_v5-keyword_organic_results-jb-31111-Data.db (No such file or directory)
at java.io.RandomAccessFile.open(Native Method)
at java.io.RandomAccessFile.<init>(RandomAccessFile.java:241)
at org.apache.cassandra.io.util.RandomAccessReader.<init>(RandomAccessReader.java:58)
at org.apache.cassandra.io.compress.CompressedRandomAccessReader.<init>(CompressedRandomAccessReader.java:76)
at org.apache.cassandra.io.compress.CompressedThrottledReader.<init>(CompressedThrottledReader.java:34)
at org.apache.cassandra.io.compress.CompressedThrottledReader.open(CompressedThrottledReader.java:48)
... 18 more
I'm currently in the middle of migrating 4.8 billion rows from MySQL which I do via sstableloader in batches of 1 to 4 million rows. Does the exception mean that I've already lost data and must repeat the migration from scratch? So far I don't see any stream error in my logs.
My environment is as follows:
DSE 4.0.1 (Cassandra 2.0.5)
CentOS 6.x x86_64
Java 1.7.0_5x
EDIT:
Some additional info:
During the bulk loading process, I devised a mechanism to kill the sstableloader when the total progress reaches 100%. I also issue a "nodetool stop INDEX_BUILD" to all nodes. The reason for this is because sstableloader waits for the secondary index build to finish and this takes hours to complete (whereas the actual import time is just a fraction of the index build time). I figured out that the imported data remains intact after killing the sstableloader process and cancelling the secondary index build so I wrote a script to automate the mechanism. So far, I have completed more than 200 bulk loads with this trick.
I have paused the migration and restarted the nodes several times in the past week because the OS load reaches high levels (yellow or red in OpsCenter) after finishing several cycles of note #1. It's possible that a compaction is in progress when I restarted the nodes via dse cassandra-stop (yes, we are running DSE as a standalone process)
Could any of these be the cause? How do I get out of this situation? Manual compaction/repair doesn't work because they always throw exceptions. For repair, the exception is different but the meaning is the same - some sstable files are missing:
ERROR [MiscStage:2] 2014-05-03 00:42:10,386 CassandraDaemon.java (line 196) Exception in thread Thread[MiscStage:2,5,main]
java.lang.RuntimeException: Tried to hard link to file that does not exist /home/cassandra/data/mtg_keywords_v5/keyword_organic_results/mtg_keywords_v5-keyword_organic_results-jb-23797-Summary.db
at org.apache.cassandra.io.util.FileUtils.createHardLink(FileUtils.java:76)
at org.apache.cassandra.io.sstable.SSTableReader.createLinks(SSTableReader.java:1215)
at org.apache.cassandra.db.ColumnFamilyStore.snapshotWithoutFlush(ColumnFamilyStore.java:1816)
at org.apache.cassandra.db.ColumnFamilyStore.snapshot(ColumnFamilyStore.java:1849)
at org.apache.cassandra.service.SnapshotVerbHandler.doVerb(SnapshotVerbHandler.java:40)
at org.apache.cassandra.net.MessageDeliveryTask.run(MessageDeliveryTask.java:60)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Have you dropped and recreated the keyspace? If so, it's probably this:
https://issues.apache.org/jira/browse/CASSANDRA-4857
Restart your nodes to clear the bad filename out of memory.

Cassandra 1.1 or 1.2 for production usage?

We are encountering random SSTable corruptions with 1.2.3/1.2.4 (Datastax Community Edition) on single node development machines with a mixed read/write load using a data model with wide rows from a number of columns POV. Writes are more frequent than reads though. The problems manifests with stack traces like:
ERROR [ReadStage:13899] 2013-04-24 07:09:00,770 CassandraDaemon.java (line 132) Exception in thread Thread[ReadStage:13899,5,main]
java.lang.RuntimeException: org.apache.cassandra.io.sstable.CorruptSSTableException: java.io.EOFException
at org.apache.cassandra.service.StorageProxy$DroppableRunnable.run(StorageProxy.java:1582)
at java.util.concurrent.ThreadPoolExecutor$Worker.runTask(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: org.apache.cassandra.io.sstable.CorruptSSTableException: java.io.EOFException
at org.apache.cassandra.db.columniterator.SimpleSliceReader.computeNext(SimpleSliceReader.java:106)
... many more
Caused by: java.io.EOFException
at java.io.RandomAccessFile.readFully(Unknown Source)
... many more
or
java.lang.RuntimeException: org.apache.cassandra.io.sstable.CorruptSSTableException: org.apache.cassandra.db.ColumnSerializer$CorruptColumnException: invalid column name length 0
Unfortunately, we don't have a reproducible test case yet, because this happens randomly (e.g. after a few days) and not immediately.
I have also researched similar issues with 1.2 in this/other forum(s).
The question is: What is your experience with Cassandra 1.2 in production or would you recommend 1.1 being 1.2.4 the most recent release to date in the 1.2 series?
While we encounter these issues on single node development environments, things might get backed up when running the whole stuff in a cluster served by several nodes, but in our opinion things should run on a single node without corruption as well.
Any hints are much appreciated. Thanks.
I have better experience with cassandra-1.1 in production. Current version 1.2.6 still do not passes our heavy preproduction testing.

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