Gatling: Executor not accepting task when polling - kotlin

I have a gatling scenario in which I need to poll a specific endpoint for the duration of the test. However when polling the request it results in an and illegal state exception with the error executor not accepting task when polling.
I've had a look at the docs here, but Im not sure where I'm going wrong.
The snippet looks like this:
.exec(
poll()
.every(5)
.exec(http("getWingboard")
.get(WingboardEnpoints.Wingboard)
.headers(Config.header)
.check(status().`is`(200))
))
Errors look like this:
[gatling-1-2] DEBUG i.g.h.client.impl.DefaultHttpClient - Failed to connect to remoteAddress=xxxx/108.156.28.72:443 from localAddress=null
java.lang.IllegalStateException: executor not accepting a task
at io.netty.resolver.AddressResolverGroup.getResolver(AddressResolverGroup.java:61)
at io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:194)
at io.netty.bootstrap.Bootstrap.doResolveAndConnect(Bootstrap.java:162)
at io.netty.bootstrap.Bootstrap.connect(Bootstrap.java:148)
at io.gatling.http.client.impl.DefaultHttpClient.openNewChannelRec(DefaultHttpClient.java:809)
at io.gatling.http.client.impl.DefaultHttpClient.lambda$openNewChannelRec$12(DefaultHttpClient.java:843)
at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:578)
at io.netty.util.concurrent.DefaultPromise.notifyListeners0(DefaultPromise.java:571)
at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:550)
at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:491)
at io.netty.util.concurrent.DefaultPromise.setValue0(DefaultPromise.java:616)
at io.netty.util.concurrent.DefaultPromise.setFailure0(DefaultPromise.java:609)
at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:117)
at io.netty.channel.nio.AbstractNioChannel.doClose(AbstractNioChannel.java:502)
at io.netty.channel.socket.nio.NioSocketChannel.doClose(NioSocketChannel.java:342)
at io.netty.channel.AbstractChannel$AbstractUnsafe.doClose0(AbstractChannel.java:754)
at io.netty.channel.AbstractChannel$AbstractUnsafe.close(AbstractChannel.java:731)
at io.netty.channel.AbstractChannel$AbstractUnsafe.close(AbstractChannel.java:620)
at io.netty.channel.nio.NioEventLoop.closeAll(NioEventLoop.java:772)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:529)
at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:986)
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.base/java.lang.Thread.run(Thread.java:833)
Im using Gatling gradle plugin v3.7.4 with Kotlin.

polling is a background task that only lasts as long as the virtual user is performing its main scenario. I suspect your users don't perform anything else than the polling.
Otherwise, please provide a full reproducer.

Related

How can I run various tests for Quarkus Kafka Stream with Testcontainer?

Following the steps described here https://quarkus.io/guides/kafka#testing-using-a-kafka-broker it's possible to define quarkus tests using a "real" Kafka broker.
#QuarkusTest instantiate all the resources needed, including KafkaStrems and during the individual tests (#Test) we can limit ourselves to produce records for input topics and consume results from output topics.
The current stream Topology include steps of groupBy, aggregation, join, ...
During test, the problem is that, after first one, all other tests have "dirty aggregates". A kafkaStreams.cleanUp() might solve the problem but produce an error:
Caused by: java.lang.IllegalStateException: Cannot clean up while running.
at org.apache.kafka.streams.KafkaStreams.cleanUp(KafkaStreams.java:1486)
at eu.reply.lea.visibility.unieuro.stream.TopologyProducerIT.setup(TopologyProducerIT.java:70)
at eu.reply.lea.visibility.unieuro.stream.TopologyProducerIT_Bean.create(Unknown Source)
at eu.reply.lea.visibility.unieuro.stream.TopologyProducerIT_Bean.get(Unknown Source)
at eu.reply.lea.visibility.unieuro.stream.TopologyProducerIT_Bean.get(Unknown Source)
at io.quarkus.arc.impl.InstanceImpl.getBeanInstance(InstanceImpl.java:225)
at io.quarkus.arc.impl.InstanceImpl.getInternal(InstanceImpl.java:211)
at io.quarkus.arc.impl.InstanceImpl.get(InstanceImpl.java:97)
... 73 more
The question is: what is the correct approch to run KafkaStream testing in quarkus (the "traditional" approach of: perform a test, perform rollback and continue with the next ones seems not applicable).
Also the following approach fails:
// test 1
kafkaStreams.close();
kafkaStreams.cleanUp();
kafkaStreams.start();
// test 2
kafkaStreams.close();
kafkaStreams.cleanUp();
kafkaStreams.start();
// ...

How to handle reactor-netty terminating a request in spring-webflux?

We have a spring-webflux application running on spring-boot-starter-webflux:jar:2.1.5.RELEASE and reactor-netty:jar:0.8.8.RELEASE. When a reactive client goes away (k8s pod killed or the client subscription is disposed off) before the request is completed, we see the server simply stops processing the request and no more application logs related to that request are seen. However, reactive-netty prints a trace log indicating that the channel is inactive and will be terminated.
Is there anything we can do to handle this termination gracefully? We would ideally like to respond to a cancellation signal from reactor.
2020-03-18T16:46:40.372Z TRACE --- [reactor-http-epoll-2] r.n.c.ChannelOperations : [id: 0x4cad974b, L:/<SERVER_IP_ADDRESS>:8080 ! R:/<SOME_OTHER_IP_ADDRESS>:55436] Disposing ChannelOperation from a channel
java.lang.Exception: ChannelOperation terminal stack
at reactor.netty.channel.ChannelOperations.terminate(ChannelOperations.java:391)
at reactor.netty.channel.ChannelOperations.onInboundClose(ChannelOperations.java:360)
at reactor.netty.channel.ChannelOperationsHandler.channelInactive(ChannelOperationsHandler.java:72)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:257)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:243)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:236)
at io.netty.channel.CombinedChannelDuplexHandler$DelegatingChannelHandlerContext.fireChannelInactive(CombinedChannelDuplexHandler.java:420)
at io.netty.handler.codec.ByteToMessageDecoder.channelInputClosed(ByteToMessageDecoder.java:393)
at io.netty.handler.codec.ByteToMessageDecoder.channelInactive(ByteToMessageDecoder.java:358)
at io.netty.channel.CombinedChannelDuplexHandler.channelInactive(CombinedChannelDuplexHandler.java:223)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:257)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:243)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelInactive(AbstractChannelHandlerContext.java:236)
at io.netty.channel.DefaultChannelPipeline$HeadContext.channelInactive(DefaultChannelPipeline.java:1416)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:257)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelInactive(AbstractChannelHandlerContext.java:243)
at io.netty.channel.DefaultChannelPipeline.fireChannelInactive(DefaultChannelPipeline.java:912)
at io.netty.channel.AbstractChannel$AbstractUnsafe$8.run(AbstractChannel.java:816)
at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:163)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:416)
at io.netty.channel.epoll.EpollEventLoop.run(EpollEventLoop.java:331)
at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:918)
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)
at java.base/java.lang.Thread.run(Thread.java:834)
The doOnCancel operator allows for a callback to be provided when a subscription is cancelled. This is different from the doOnEach operator which is run only when the subscription completes or errors out.
https://projectreactor.io/docs/core/release/api/reactor/core/publisher/Mono.html#doOnCancel-java.lang.Runnable-

async scope is not working in Clustering in mule 3.4.2

async scope is not working in Clustering in mule 3.4.2. we are getting below exception.
Message : Interrupted while queueing event for "SEDA Stage Main_Flow.async1". Message payload is of type: ConfirmReceiveMessageResponse
Code : MULE_ERROR--2
--------------------------------------------------------------------------------
Exception stack is:
1. com.sample.client.ReceiveMessageResponse (java.io.NotSerializableException)
java.io.ObjectOutputStream:1183 (null)
2. java.io.NotSerializableException: com.elexon.bmrs.ecp.client.ReceiveMessageResponse (org.apache.commons.lang.SerializationException)
org.apache.commons.lang.SerializationUtils:111 (null)
3. Interrupted while queueing event for "SEDA Stage Main_Flow.async1". Message payload is of type: ConfirmReceiveMessageResponse (org.mule.api.service.FailedToQueueEventException)
org.mule.processor.SedaStageInterceptingMessageProcessor:92 (http://www.mulesoft.org/docs/site/current3/apidocs/org/mule/api/service/FailedToQueueEventException.html)
--------------------------------------------------------------------------------
Root Exception stack trace:
java.io.NotSerializableException: com.sample.client.ReceiveMessageResponse
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1183)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
at org.apache.commons.collections.map.AbstractHashedMap.doWriteObject(AbstractHashedMap.java:1182)
+ 3 more (set debug level logging or '-Dmule.verbose.exceptions=true' for everything)
After removing the async scope we are able to test the application. Could please help us how to make the application works with async in cluster env?
If the flow ref is using an async processing strategy it will try and persist the event in a cluster I believe. And your object is not Serializable.
You can make com.sample.client.ReceiveMessageResponse implement java.io.Serializable if you want the message to be persisted.
Or you can try forcing the flow that you are flow-ref'ing processingStrategy="synchronous" maybe.

JobTracker - High memory and native thread usage

We are running hadoop on GCE with HDFS default file system, and data input/output from/to GCS.
Hadoop version: 1.2.1
Connector version: com.google.cloud.bigdataoss:gcs-connector:1.3.0-hadoop1
Observed behavior: JT will accumulate threads in waiting state, leading to OOM:
2015-02-06 14:15:51,206 ERROR org.apache.hadoop.mapred.JobTracker: Job initialization failed:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
at java.util.concurrent.ThreadPoolExecutor.addWorker(ThreadPoolExecutor.java:949)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1371)
at com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel.initialize(AbstractGoogleAsyncWriteChannel.java:318)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageImpl.create(GoogleCloudStorageImpl.java:275)
at com.google.cloud.hadoop.gcsio.CacheSupplementedGoogleCloudStorage.create(CacheSupplementedGoogleCloudStorage.java:145)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.createInternal(GoogleCloudStorageFileSystem.java:184)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.create(GoogleCloudStorageFileSystem.java:168)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopOutputStream.<init>(GoogleHadoopOutputStream.java:77)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.create(GoogleHadoopFileSystemBase.java:655)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:564)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:545)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:452)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:444)
at org.apache.hadoop.mapred.JobHistory$JobInfo.logSubmitted(JobHistory.java:1860)
at org.apache.hadoop.mapred.JobInProgress$3.run(JobInProgress.java:709)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1190)
at org.apache.hadoop.mapred.JobInProgress.initTasks(JobInProgress.java:706)
at org.apache.hadoop.mapred.JobTracker.initJob(Jobenter code hereTracker.java:3890)
at org.apache.hadoop.mapred.EagerTaskInitializationListener$InitJob.run(EagerTaskInitializationListener.java:79)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
After looking through the JT logs I found these warnings:
2015-02-06 14:30:17,442 WARN org.apache.hadoop.hdfs.DFSClient: Failed recovery attempt #0 from primary datanode xx.xxx.xxx.xxx:50010
java.io.IOException: Call to /xx.xxx.xxx.xxx:50020 failed on local exception: java.io.IOException: Couldn't set up IO streams
at org.apache.hadoop.ipc.Client.wrapException(Client.java:1150)
at org.apache.hadoop.ipc.Client.call(Client.java:1118)
at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:229)
at com.sun.proxy.$Proxy10.getProtocolVersion(Unknown Source)
at org.apache.hadoop.ipc.RPC.checkVersion(RPC.java:422)
at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:414)
at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:392)
at org.apache.hadoop.hdfs.DFSClient.createClientDatanodeProtocolProxy(DFSClient.java:201)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.processDatanodeError(DFSClient.java:3317)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.access$2200(DFSClient.java:2783)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream$DataStreamer.run(DFSClient.java:2987)
Caused by: java.io.IOException: Couldn't set up IO streams
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:642)
at org.apache.hadoop.ipc.Client$Connection.access$2200(Client.java:205)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1249)
at org.apache.hadoop.ipc.Client.call(Client.java:1093)
... 9 more
Caused by: java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:635)
... 12 more
This appears to be similar to hadoop bug reporter here: https://issues.apache.org/jira/browse/MAPREDUCE-5606
I tried proposed solution by disabling saving job logs into the output path and it solved the problem at the expense of missing logs :)
I also ran jstack on JT and it showed hundreds of WAITING or TIMED_WAITING threads as such:
pool-52-thread-1" prio=10 tid=0x00007feaec581000 nid=0x524f in Object.wait() [0x00007fead39b3000]
java.lang.Thread.State: TIMED_WAITING (on object monitor)
at java.lang.Object.wait(Native Method)
- waiting on <0x000000074d86ba60> (a java.io.PipedInputStream)
at java.io.PipedInputStream.read(PipedInputStream.java:327)
- locked <0x000000074d86ba60> (a java.io.PipedInputStream)
at java.io.PipedInputStream.read(PipedInputStream.java:378)
- locked <0x000000074d86ba60> (a java.io.PipedInputStream)
at com.google.api.client.util.ByteStreams.read(ByteStreams.java:181)
at com.google.api.client.googleapis.media.MediaHttpUploader.setContentAndHeadersOnCurrentReque
st(MediaHttpUploader.java:629)
at com.google.api.client.googleapis.media.MediaHttpUploader.resumableUpload(MediaHttpUploader.
java:409)
at com.google.api.client.googleapis.media.MediaHttpUploader.upload(MediaHttpUploader.java:336)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(Abstr
actGoogleClientRequest.java:419)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(Abstr
actGoogleClientRequest.java:343)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogl
eClientRequest.java:460)
at com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel$UploadOperation.run(AbstractGo
ogleAsyncWriteChannel.java:354)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Locked ownable synchronizers:
- <0x000000074d864918> (a java.util.concurrent.ThreadPoolExecutor$Worker)
It appears JT is having hard time keeping up communicating with GCS via GCS Connector.
Please advise,
Thank you
At the moment, every open FSDataOutputStream in the GCS connector for Hadoop consumes a thread until it's closed, because a separate thread needs to run the "resumable" HttpRequests while the user of the OutputStream writes bytes intermittently. In most cases, (such as in individual Hadoop tasks), there's only ever one long-lived output stream, and possibly a few shorter-lived ones for writing small metadata/marker files, etc.
In general, there are two possible causes for the OOM you're running into:
You have lots of queued up jobs; every submitted job holds an unclosed OutputStream, and thus consumes a "waiting" thread. However, since you mention you only need to queue up ~10 jobs, this shouldn't be the root cause.
Something is causing a "leak" of the PrintWriter objects, originally created in logSubmitted and added to fileManager. Typically, terminal events (like logFinished will correctly close() all the PrintWriters before removing them from the map via markCompleted, but in theory they may be bugs here or there which can cause one of the OutputStreams to leak without being close()'d. For example, while I haven't had a chance to verify this assertion, it seems that IOException trying to do something like logMetaInfo will "removeWriter" without closing it.
I've verified that at least under normal circumstances, the OutputStream seem to get closed correctly, and my sample JobTracker shows a clean jstack after having successfully run a lot of jobs.
TL;DR: There are some working theories as to why some resource may leak and ultimately prevent necessary threads from being created. You should consider changing hadoop.job.history.user.location to some HDFS location in the meantime, as a way to preserve the job logs in the absence of placing them on GCS.

Read Timed Out : sychronous query via Bigquery java API

We are using the big query JAVA API to retrieve results for our analytics reporting frontend. We are trying to retrieve the results synchronously. A lot of times we get Read timed out error, even before the query timeout as specified in the parameters. Here's the stack trace for a sample fail:
java.net.SocketTimeoutException: Read timed out
at java.net.SocketInputStream.socketRead0(Native Method)
at java.net.SocketInputStream.read(SocketInputStream.java:129)
at com.sun.net.ssl.internal.ssl.InputRecord.readFully(InputRecord.java:293)
at com.sun.net.ssl.internal.ssl.InputRecord.read(InputRecord.java:331)
at com.sun.net.ssl.internal.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:830)
at com.sun.net.ssl.internal.ssl.SSLSocketImpl.readDataRecord(SSLSocketImpl.java:787)
at com.sun.net.ssl.internal.ssl.AppInputStream.read(AppInputStream.java:75)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:218)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:258)
at java.io.BufferedInputStream.read(BufferedInputStream.java:317)
at sun.net.www.http.HttpClient.parseHTTPHeader(HttpClient.java:697)
at sun.net.www.http.HttpClient.parseHTTP(HttpClient.java:640)
at sun.net.www.protocol.http.HttpURLConnection.getInputStream(HttpURLConnection.java:1195)
at java.net.HttpURLConnection.getResponseCode(HttpURLConnection.java:379)
at sun.net.www.protocol.https.HttpsURLConnectionImpl.getResponseCode(HttpsURLConnectionImpl.java:318)
at com.google.api.client.http.javanet.NetHttpResponse.<init>(NetHttpResponse.java:36)
at com.google.api.client.http.javanet.NetHttpRequest.execute(NetHttpRequest.java:94)
at com.google.api.client.http.HttpRequest.execute(HttpRequest.java:965)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:410)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:343)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogleClientRequest.java:460)
I am not able to retrieve the job id of the resulting job as the error occurs before I can retrieve a JobReference object. The timeout specified in this case was 300 sec. The query failed well before it. The query contains three JOIN's and several GROUP EACH BY clauses. Can you suggest us a possible way to debug this ?
Adding the code snippet:
QueryRequest queryInfo = new QueryRequest().setQuery(sql)
.setTimeoutMs(timeOutInSec * 1000);
// get project id
BQGameConnectionDetails details = Config
.getBQConnectionDetails(gameId);
String projectId = details.getProjectId();
Bigquery.Jobs.Query queryRequest = getInstance(gameId).jobs()
.query(projectId, queryInfo);
QueryResponse response = queryRequest.execute();
There are two timeouts involved. The first timeout is in the HTTP request you've sent to bigquery. The second is in the bigquery request timeout. It sounds like you've set the latter to a large value, but the former is likely the timeout that you're hitting. If the HTTP request times out before the BigQuery timeout, the connection will be closed and BigQuery won't have a chance to respond.
There are two options: First is to increase the HTTP request timeout (which depends on the libraries you're using, but this page here may be helpful). The second is to decrease the bigquery timeout. This means you'll have to use jobs.getQueryResults() to read the actual results, but this is a more robust method because it doesn't matter how long the query takes, you can just call getQueryResults() in a loop. I would post a link to a good java sample that does this, but I don't know that one exists, unfortunately.