I encountered the following problem when start running a hama BSP job. This exception occurs when hama tries to load and partition the input data before it actually runs my own code. This is a known problem discussed in some websites but unfortunate without a known cause (eg. see here).
My BSP job works perfectly ok when I only runs part of the data set. However, when I run the full data set, the problem occurs :(
Can I know how to resolve or avoid this problem?
13/11/18 01:19:30 INFO bsp.FileInputFormat: Total input paths to process : 32
13/11/18 01:19:30 INFO bsp.FileInputFormat: Total input paths to process : 32
13/11/18 01:19:30 INFO bsp.BSPJobClient: Running job: job_201311180115_0002
13/11/18 01:19:33 INFO bsp.BSPJobClient: Current supersteps number: 0
13/11/18 01:19:33 INFO bsp.BSPJobClient: Job failed.
13/11/18 01:19:33 ERROR bsp.BSPJobClient: Error partitioning the input path.
java.io.IOException: Runtime partition failed for the job.
at org.apache.hama.bsp.BSPJobClient.partition(BSPJobClient.java:465)
at org.apache.hama.bsp.BSPJobClient.submitJobInternal(BSPJobClient.java:333)
at org.apache.hama.bsp.BSPJobClient.submitJob(BSPJobClient.java:293)
at org.apache.hama.bsp.BSPJob.submit(BSPJob.java:228)
at org.apache.hama.bsp.BSPJob.waitForCompletion(BSPJob.java:235)
at edu.wisc.cs.db.opener.hama.ConnectedEntityBspDriver.main(ConnectedEntityBspDriver.java:183)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hama.util.RunJar.main(RunJar.java:146)
After stuck at this problem for several hours, I found that once the number of input files is greater than the number of allowed bsp tasks, then this error will occur. I think it is probably a bug that Hama should fix in the future.
A quick fix to this problem is to increase the number of maximum bsp tasks, specified by the variable bsp.tasks.maximum in the hama-site.xml file. For example, the following uses 10 instead of the default setting 3:
<property>
<name>bsp.tasks.maximum</name>
<value>10</value>
<description>The maximum number of BSP tasks that will be run simultaneously
by a groom server.</description>
</property>
Related
I have a problem with my cluster.
the cluster have
2 worker primary
2 secondary worker
30 gb di ram
The cluster runs correctly and launches the job hives for at least about 10h.
After 10h I have an error of :Java heap space
at java.lang.Thread.run(Thread.java:748) [?:1.8.0_292]
Caused by: java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[?:1.8.0_292]
at java.io.ByteArrayOutputStream.toByteArray(ByteArrayOutputStream.java:191) ~[?:1.8.0_292]
at org.apache.hadoop.ipc.ResponseBuffer.toByteArray(ResponseBuffer.java:53) ~[hadoop-common-3.2.2.jar:?]
at org.apache.hadoop.ipc.Client$Connection$3.run(Client.java:1159) ~[hadoop-common-3.2.2.jar:?]
... 5 more
ERROR : FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.tez.TezTask
INFO : Completed executing command(queryId=hive_20210923102707_66b4cd11-7cfb-4910-87bc-7f062ce1b00e); Time taken: 75.101 seconds
INFO : Concurrency mode is disabled, not creating a lock manager
Error: Error while processing statement: FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.tez.TezTask (state=08S01,code=1)
i tried to set this cofiguration but it didn't help.
SET hive.execution.engine = tez;
SET hive.exec.dynamic.partition = true;
SET hive.exec.dynamic.partition.mode = nonstrict;
SET mapreduce.job.reduces=1;
SET hive.auto.convert.join=false;
set hive.stats.column.autogather=false;
set hive.optimize.sort.dynamic.partition=true;
is there any way to clean the java heap space or I have got some configuration wrong?
the problem is solved by restarting the cluster
It seems that the default Tez container and heap sizes set by Dataproc are too small for your job. You can update the following Hive properties to increase them:
hive.tez.container.size: The YARN container size in MB for Tez. If set to "-1" (default value), it picks the value of mapreduce.map.memory.mb. Consider increasing the value if the query / Tez app fails with something like "Container is running beyond physical memory limits. Current usage: 4.1 GB of 4 GB physical memory used; 6.0 GB of 20 GB virtual memory used. Killing container.". Example: SET hive.tez.container.size=8192 in Hive, or --properties hive:hive.tez.container.size=8192 when creating the cluster.
hive.tez.java.opts: The JVM options for the Tez YARN application. If not set, it picks the value of mapreduce.map.java.opts. This value should be less or equal to the container size. Consider increasing the JVM heap size if the query / Tez app fails with an OOM exception. Example: SET hive.tez.java.opts=-Xmx8g or --properties hive:hive.tez.java.opts=-Xmx8g when creating the cluster.
You can check /etc/hadoop/conf/mapred-site.xml to get the value of mapreduce.map.java.opts, and /etc/hive/conf/hive-site.xml for the 2 Hive properties mentioned above.
I have a neo4j 3.2.1 multi-labeled multi-properties graph database which has 4M nodes, 15M edges, and 4.8M distinct labels with ~6GB size on the disk.
I've imported the dataset using "neo4j-import" tool using a linux machine.
I can open the dataset, traverse the nodes, edges, and their descriptions well using the Java API. However, once I want to shut it down, it takes a lot of time and finally, it gives me the following log file error:
2017-08-04 07:07:38.189+0000 INFO [o.n.k.i.f.GraphDatabaseFacadeFactory] Shutdown started
2017-08-04 07:07:38.190+0000 INFO [o.n.k.i.f.GraphDatabaseFacadeFactory] Database is now unavailable
2017-08-04 07:07:38.198+0000 INFO [o.n.k.i.t.l.c.CheckPointerImpl] Check Pointing triggered by database shutdown [5399]: Starting check pointing...
2017-08-04 07:07:38.198+0000 INFO [o.n.k.i.t.l.c.CheckPointerImpl] Check Pointing triggered by database shutdown [5399]: Starting store flush...
2017-08-04 07:23:35.022+0000 ERROR [o.n.k.i.t.l.c.CheckPointerImpl] Error performing check point Failed to rotate logs. Expected version: 5399, actual version: 5274, wait timeout (ms): 956815
org.neo4j.kernel.impl.store.kvstore.RotationTimeoutException: Failed to rotate logs. Expected version: 5399, actual version: 5274, wait timeout (ms): 956815
at org.neo4j.kernel.impl.store.kvstore.RotationState$Rotation.rotate(RotationState.java:79)
at org.neo4j.kernel.impl.store.kvstore.RotationState$Rotation.rotate(RotationState.java:52)
at org.neo4j.kernel.impl.store.kvstore.AbstractKeyValueStore$RotationTask.rotate(AbstractKeyValueStore.java:311)
at org.neo4j.kernel.impl.store.kvstore.AbstractKeyValueStore$RotationTask.rotate(AbstractKeyValueStore.java:288)
at org.neo4j.kernel.impl.store.counts.CountsTracker.rotate(CountsTracker.java:154)
at org.neo4j.kernel.impl.store.NeoStores.flush(NeoStores.java:242)
at org.neo4j.kernel.impl.storageengine.impl.recordstorage.RecordStorageEngine.flushAndForce(RecordStorageEngine.java:480)
at org.neo4j.kernel.impl.transaction.log.checkpoint.CheckPointerImpl.doCheckPoint(CheckPointerImpl.java:160)
at org.neo4j.kernel.impl.transaction.log.checkpoint.CheckPointerImpl.forceCheckPoint(CheckPointerImpl.java:88)
at org.neo4j.kernel.NeoStoreDataSource$3.shutdown(NeoStoreDataSource.java:794)
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.shutdown(LifeSupport.java:489)
at org.neo4j.kernel.lifecycle.LifeSupport.shutdown(LifeSupport.java:206)
at org.neo4j.kernel.NeoStoreDataSource.stop(NeoStoreDataSource.java:766)
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.stop(LifeSupport.java:458)
at org.neo4j.kernel.lifecycle.LifeSupport.stopInstances(LifeSupport.java:161)
at org.neo4j.kernel.lifecycle.LifeSupport.stop(LifeSupport.java:143)
at org.neo4j.kernel.impl.transaction.state.DataSourceManager.stop(DataSourceManager.java:120)
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.stop(LifeSupport.java:458)
at org.neo4j.kernel.lifecycle.LifeSupport.stopInstances(LifeSupport.java:161)
at org.neo4j.kernel.lifecycle.LifeSupport.stop(LifeSupport.java:143)
at org.neo4j.kernel.lifecycle.LifeSupport.shutdown(LifeSupport.java:191)
at org.neo4j.kernel.impl.factory.ClassicCoreSPI.shutdown(ClassicCoreSPI.java:159)
at org.neo4j.kernel.impl.factory.GraphDatabaseFacade.shutdown(GraphDatabaseFacade.java:366)
at experiment.caseStudy.TestDatasetHealth.run(TestDatasetHealth.java:70)
at experiment.caseStudy.TestDatasetHealth.main(TestDatasetHealth.java:29)
2017-08-04 07:23:35.665+0000 INFO [o.n.k.i.DiagnosticsManager] --- STOPPING diagnostics START ---
2017-08-04 07:23:35.666+0000 INFO [o.n.k.i.DiagnosticsManager] --- STOPPING diagnostics END ---
In the Java itself, I get the following exception:
Exception in thread "main" org.neo4j.kernel.lifecycle.LifecycleException: Component 'org.neo4j.kernel.NeoStoreDataSource$3#3101ffd3' failed to transition from stopped to shutting_down. Please see the attached cause exception "Failed to rotate logs. Expected version: 5399, actual version: 5274, wait timeout (ms): 956815".
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.shutdown(LifeSupport.java:497)
at org.neo4j.kernel.lifecycle.LifeSupport.shutdown(LifeSupport.java:206)
at org.neo4j.kernel.NeoStoreDataSource.stop(NeoStoreDataSource.java:766)
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.stop(LifeSupport.java:458)
at org.neo4j.kernel.lifecycle.LifeSupport.stopInstances(LifeSupport.java:161)
at org.neo4j.kernel.lifecycle.LifeSupport.stop(LifeSupport.java:143)
at org.neo4j.kernel.impl.transaction.state.DataSourceManager.stop(DataSourceManager.java:120)
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.stop(LifeSupport.java:458)
at org.neo4j.kernel.lifecycle.LifeSupport.stopInstances(LifeSupport.java:161)
at org.neo4j.kernel.lifecycle.LifeSupport.stop(LifeSupport.java:143)
at org.neo4j.kernel.lifecycle.LifeSupport.shutdown(LifeSupport.java:191)
at org.neo4j.kernel.impl.factory.ClassicCoreSPI.shutdown(ClassicCoreSPI.java:159)
at org.neo4j.kernel.impl.factory.GraphDatabaseFacade.shutdown(GraphDatabaseFacade.java:366)
at experiment.caseStudy.TestDatasetHealth.run(TestDatasetHealth.java:70)
at experiment.caseStudy.TestDatasetHealth.main(TestDatasetHealth.java:29)
Caused by: org.neo4j.kernel.impl.store.kvstore.RotationTimeoutException: Failed to rotate logs. Expected version: 5399, actual version: 5274, wait timeout (ms): 956815
at org.neo4j.kernel.impl.store.kvstore.RotationState$Rotation.rotate(RotationState.java:79)
at org.neo4j.kernel.impl.store.kvstore.RotationState$Rotation.rotate(RotationState.java:52)
at org.neo4j.kernel.impl.store.kvstore.AbstractKeyValueStore$RotationTask.rotate(AbstractKeyValueStore.java:311)
at org.neo4j.kernel.impl.store.kvstore.AbstractKeyValueStore$RotationTask.rotate(AbstractKeyValueStore.java:288)
at org.neo4j.kernel.impl.store.counts.CountsTracker.rotate(CountsTracker.java:154)
at org.neo4j.kernel.impl.store.NeoStores.flush(NeoStores.java:242)
at org.neo4j.kernel.impl.storageengine.impl.recordstorage.RecordStorageEngine.flushAndForce(RecordStorageEngine.java:480)
at org.neo4j.kernel.impl.transaction.log.checkpoint.CheckPointerImpl.doCheckPoint(CheckPointerImpl.java:160)
at org.neo4j.kernel.impl.transaction.log.checkpoint.CheckPointerImpl.forceCheckPoint(CheckPointerImpl.java:88)
at org.neo4j.kernel.NeoStoreDataSource$3.shutdown(NeoStoreDataSource.java:794)
at org.neo4j.kernel.lifecycle.LifeSupport$LifecycleInstance.shutdown(LifeSupport.java:489)
In fact, in the Java program, I just read the information and do not write anything on the dataset.
Furthermore, to open the database using the following line of code, it takes 80 seconds on a 3.1GHz Core i7 MacBook with 16GB of Ram with 10GB of JVM arguments.
Is it normal to take this much of time for a dataset with the mentioned size?
GraphDatabaseService dataGraph = new GraphDatabaseFactory().newEmbeddedDatabase(storeDir);
Could you please guide me how can I repair the dataset to be easily shut down?
I have written Map-Reduce code to copy a file from HDFS to Local and when i am running Map-Reduce job it is throwing below error.
Log Upload Time: Thu Jun 29 10:51:22 +0530 2017
Log Length: 78421677
Showing 1000000 bytes of 78421677 total. Click
here
for the full log.
t org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:209)
at org.apache.hadoop.fs.RawLocalFileSystem.createOutputStreamWithMode(RawLocalFileSystem.java:307)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:295)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:328)
at org.apache.hadoop.fs.ChecksumFileSystem$ChecksumFSOutputSummer.<init>(ChecksumFileSystem.java:393)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:456)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:435)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:922)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:903)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:800)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:368)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:341)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:292)
at org.apache.hadoop.fs.FileSystem.copyToLocalFile(FileSystem.java:2016)
at org.apache.hadoop.fs.FileSystem.copyToLocalFile(FileSystem.java:1985)
at org.apache.hadoop.fs.FileSystem.copyToLocalFile(FileSystem.java:1961)
at com.mani.pmml_mr.PMMLMapper.map(PMMLMapper.java:64)
at com.mani.pmml_mr.PMMLMapper.map(PMMLMapper.java:35)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:145)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:787)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)
EPERM: Operation not permitted
at org.apache.hadoop.io.nativeio.NativeIO$POSIX.chmodImpl(Native Method)
at org.apache.hadoop.io.nativeio.NativeIO$POSIX.chmod(NativeIO.java:230)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:708)
at org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:225)
at org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:209)
at org.apache.hadoop.fs.RawLocalFileSystem.createOutputStreamWithMode(RawLocalFileSystem.java:307)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:295)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:328)
at org.apache.hadoop.fs.ChecksumFileSystem$ChecksumFSOutputSummer.<init>(ChecksumFileSystem.java:393)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:456)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:435)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:922)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:903)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:800)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:368)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:341)
at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:292)
at org.apache.hadoop.fs.FileSystem.copyToLocalFile(FileSystem.java:2016)
at org.apache.hadoop.fs.FileSystem.copyToLocalFile(FileSystem.java:1985)
at org.apache.hadoop.fs.FileSystem.copyToLocalFile(FileSystem.java:1961)
In my code i am using copyToLocalFile() method but i am not sure why it is throwing errors. I gave full permissions (777) to the local folder where the file will be copied. But still it is throwing some error.
And another problem i noticed is, even the job is throwing error (Which i noticed from Job Browser of Hue), still in console it is showing job is successful.
17/06/29 10:51:16 INFO mapreduce.Job: Job job_1495430640647_0231 completed successfully
Can someone please help me in this.
I am running a YARN job on CDH 5.3 cluster. I have default configurations.
No of nodes=3
yarn.nodemanager.resource.cpu-vcores=8
yarn.nodemanager.resource.memory-mb=10GB
mapreduce.[map/reduce].cpu.vcores=1
mapreduce.[map/reduce].memory.mb=1GB
mapreduce.[map | reduce].java.opts.max.heap=756MB
While doing a run on 4.5GB csv data spread over 11 files ,I get following error:
2015-10-12 05:21:04,507 FATAL [IPC Server handler 18 on 50388] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Task: attempt_1444634391081_0005_r_000000_0 - exited : org.apache.hadoop.mapreduce.task.reduce.Shuffle$ShuffleError: error in shuffle in fetcher#9
at org.apache.hadoop.mapreduce.task.reduce.Shuffle.run(Shuffle.java:134)
at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:376)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1642)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)
Caused by: java.lang.OutOfMemoryError: Java heap space
at org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:56)
at org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:46)
at org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput.<init>(InMemoryMapOutput.java:63)
at org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.unconditionalReserve(MergeManagerImpl.java:303)
at org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.reserve(MergeManagerImpl.java:293)
at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:511)
at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:329)
at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:193)
Then I tuned mapreduce.reduce.memory.mb=1GB to mapreduce.reduce.memory.mb=3GB and job runned fine.
So how to decide on how much data maximum can be handled by 1 reducer assuming that all the input to mapper have to be processed by 1 reducer only?
Generally there is no limitation on the data that can be processed by a single reducer. The memory allocation can slow down the process but must not restrict or fail to process the data. I believe after allocating minimum memory to reducer the data processing should not be an issue. Can u pls share some code snippet to check for any memory leak issues.
We used to process 6+Gb of file in a single reducer withou any issues. I believe you might be having memory leak issues.
I'm currently trying to implement a Storm topology that integrates with the R language.
As a starting point, i took the following project (https://github.com/allenday/R-Storm) which works by extending the ShellBolt class to implement R integration, as well as an R library to handle communication between the java and R sides.
My problem is that if i create a topology based on regular (java-only) bolts, i can chain them together without issue. However, when one of the bolts in the middle of the chain is an R Shell Bolt, the thing just falls apart with:
5661 [Thread-18] ERROR backtype.storm.util - Async loop died!
java.lang.RuntimeException: java.lang.RuntimeException: java.lang.RuntimeException: Pipe to subprocess seems to be broken! No output read.
Shell Process Exception:
at backtype.storm.utils.DisruptorQueue.consumeBatchToCursor(DisruptorQueue.java:87) ~[storm-0.9.0-wip16.jar:na]
at backtype.storm.utils.DisruptorQueue.consumeBatchWhenAvailable(DisruptorQueue.java:58) ~[storm-0.9.0-wip16.jar:na]
at backtype.storm.disruptor$consume_batch_when_available.invoke(disruptor.clj:62) ~[storm-0.9.0-wip16.jar:na]
at backtype.storm.daemon.executor$fn__3557$fn__3569$fn__3616.invoke(executor.clj:715) ~[storm-0.9.0-wip16.jar:na]
at backtype.storm.util$async_loop$fn__436.invoke(util.clj:377) ~[storm-0.9.0-wip16.jar:na]
at clojure.lang.AFn.run(AFn.java:24) ~[clojure-1.4.0.jar:na]
at java.lang.Thread.run(Unknown Source) ~[na:1.7.0_25]
Caused by: java.lang.RuntimeException: java.lang.RuntimeException: Pipe to subprocess seems to be broken! No output read.
More concrete, the following topology works as expected:
TopologyBuilder builder = new TopologyBuilder();
builder.setSpout("spout", new RandomSentenceSpout(), 1);
builder.setBolt("permutebolt", new PermuteBolt(), 1).shuffleGrouping("spout");
Where PermuteBolt is an R Shell Bolt. The logs for this example show the expected output:
6246 [Thread-18] INFO backtype.storm.daemon.task - Emitting: spout default [four score and seven years ago]
6246 [Thread-16] INFO backtype.storm.daemon.executor - Processing received message source: spout:3, stream: default, id: {}, [four score and seven years ago]
6261 [Thread-23] INFO backtype.storm.daemon.task - Emitting: permutebolt default ["PERMUTE seven years ago and four score"]
If, however i add another bolt that gets its data from the first one, such as:
builder.setBolt("permutebolt", new PermuteBolt(), 1).shuffleGrouping("spout");
builder.setBolt("identity", new IdentityBolt(new Fields("identity")), 1).fieldsGrouping("permutebolt", new Fields("permutation"));
It fails with the trace printed above. Also, what's weird is that this second example which is failing is included with the project.
Is this an issue anyone has faced before ?
UPDATE: I noticed this only occurs when using R Shell Bolts, i have since tried launching bolts that use python scripts and have been able to chain them normally.
#andrei, this is fixed in 1.01 uploaded to github today:
https://github.com/allenday/R-Storm/releases/tag/v1.01
It has been submitted to CRAN and will be available soon.
Thanks for reporting.
-Allen