I need to configure Kafka appender using log4j2.xml, the setup worked fine local, but server I am getting below error.
Local Kafka: kafka_2.11-0.10.2.0
Kafka Appender: 0.9.0.0
Local worked fine.
Server Kafka: 0.8
Kafka Appender: 0.9.0.0
On the server I got the following error:
2017-03-09 21:19:18,255 main ERROR Unable to write to Kafka [kafkaAppender] for appender [kafkaAppender]. java.util.concurrent.ExecutionException: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.
at org.apache.kafka.clients.producer.KafkaProducer$FutureFailure.<init>(KafkaProducer.java:730)
at org.apache.kafka.clients.producer.KafkaProducer.doSend(KafkaProducer.java:483)
at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:430)
at org.apache.kafka.clients.producer.KafkaProducer.send(KafkaProducer.java:353)
at org.apache.logging.log4j.core.appender.mom.kafka.KafkaManager.send(KafkaManager.java:81)
at org.apache.logging.log4j.core.appender.mom.kafka.KafkaAppender.append(KafkaAppender.java:85)
at org.apache.logging.log4j.core.config.AppenderControl.tryCallAppender(AppenderControl.java:155)
at org.apache.logging.log4j.core.config.AppenderControl.callAppender0(AppenderControl.java:128)
at org.apache.logging.log4j.core.config.AppenderControl.callAppenderPreventRecursion(AppenderControl.java:119)
at org.apache.logging.log4j.core.config.AppenderControl.callAppender(AppenderControl.java:84)
at org.apache.logging.log4j.core.config.LoggerConfig.callAppenders(LoggerConfig.java:390)
at org.apache.logging.log4j.core.config.LoggerConfig.processLogEvent(LoggerConfig.java:375)
at org.apache.logging.log4j.core.config.LoggerConfig.log(LoggerConfig.java:359)
at org.apache.logging.log4j.core.config.LoggerConfig.log(LoggerConfig.java:349)
at org.apache.logging.log4j.core.config.AwaitCompletionReliabilityStrategy.log(AwaitCompletionReliabilityStrategy.java:63)
at org.apache.logging.log4j.core.Logger.logMessage(Logger.java:146)
at org.apache.logging.slf4j.Log4jLogger.log(Log4jLogger.java:376)
at org.apache.commons.logging.impl.SLF4JLocationAwareLog.info(SLF4JLocationAwareLog.java:155)
at org.springframework.boot.SpringApplication.logStartupProfileInfo(SpringApplication.java:665)
at org.springframework.boot.SpringApplication.prepareContext(SpringApplication.java:353)
at org.springframework.boot.SpringApplication.run(SpringApplication.java:313)
at org.springframework.boot.SpringApplication.run(SpringApplication.java:1186)
at org.springframework.boot.SpringApplication.run(SpringApplication.java:1175)
at com.charter.kafka.proxy.app.ProxyApplication.main(ProxyApplication.java:21)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.springframework.boot.loader.MainMethodRunner.run(MainMethodRunner.java:48)
at org.springframework.boot.loader.Launcher.launch(Launcher.java:87)
at org.springframework.boot.loader.Launcher.launch(Launcher.java:50)
at org.springframework.boot.loader.JarLauncher.main(JarLauncher.java:51)
Caused by: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 60000 ms.
My bad, I wrote value for bootstrap.servers property with extra space in log4j2.xml, after removing the space, I could connect to Kafka. Thanks.
You are unable to get the metadata , check that the kafka cluster is up and running and that there is no connectivity issue
Related
I have setup a Hadoop cluster with 1 name node and 2 data nodes. I've also installed Yarn and Spark on top of that in the name node.
I notice that whenever I try run the example jar here:
spark-submit --deploy-mode cluster --class org.apache.spark.examples.SparkPi $SPARK_HOME/examples/jars/spark-examples_*.jar 10
I will always get the no route to host exception:
Uncaught exception: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:301)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:102)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:110)
at org.apache.spark.deploy.yarn.ApplicationMaster.runExecutorLauncher(ApplicationMaster.scala:558)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:277)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:926)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:925)
at java.base/java.security.AccessController.doPrivileged(Native Method)
at java.base/javax.security.auth.Subject.doAs(Subject.java:423)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1878)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:925)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:957)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Caused by: java.io.IOException: Failed to connect to lnx-pen205/xx.xx.xx.xx:9222
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:288)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:218)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:230)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:204)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:202)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:198)
at java.base/java.util.concurrent.FutureTask.run(FutureTask.java:264)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: io.netty.channel.AbstractChannel$AnnotatedNoRouteToHostException: No route to host: lnx-pen205/xx.xx.xx.xx:9222
Caused by: java.net.NoRouteToHostException: No route to host
at java.base/sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at java.base/sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:777)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:330)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:334)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:710)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:658)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:584)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:496)
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:829)
I noticed that the port being used will be randomly assigned during the runtime, the example .jar will work if for example I set the spark.driver.port as 9222 then opening said port with the firewall. But then if any other session is started (for example, pyspark shell), it wouldn't start as the port is already in use.
My question is: How do I allow connections to the ports dynamically defined by Spark/Yarn? I read somewhere that I should disable the firewall, but that does not sound like a good idea.. Thanks in advance.
There's spark.driver.port as well as spark.driver.blockManager.port. Both are starting ranges to spark.port.maxRetries (default 16).
So, you'll need to open at least 32 ports for these.
I did some testing with dynamic Spark ports in Mesos + Docker a few years ago - https://stackoverflow.com/a/56486271/2308683
I'm trying to issue spark submit from Azure Databricks jobs scheduler, currently stuck with the below error. Error says: File file:/tmp/spark-events does not exist. I need some pointers to understand do we need to create this directory in Azure blob location(which is my storage Layer) or in Azure DBFS location.
As per the below link, not so clear where to create the directory when running the spark-submit from Azure Databricks jobs scheduler.
SparkContext Error - File not found /tmp/spark-events does not exist
Error:
OpenJDK 64-Bit Server VM warning: ignoring option MaxPermSize=512m; support was removed in 8.0
Warning: Ignoring non-Spark config property: eventLog.rolloverIntervalSeconds
Exception in thread "main" java.lang.ExceptionInInitializerError
at com.dta.dl.ct.qm.hbase.reverse.pipeline.HBaseVehicleMasterLoad.main(HBaseVehicleMasterLoad.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:845)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:161)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:184)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:920)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:929)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.io.FileNotFoundException: File file:/tmp/spark-events does not exist
at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:611)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:824)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:601)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
at org.apache.spark.scheduler.EventLoggingListener.start(EventLoggingListener.scala:97)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:580)
at com.dta.dl.ct.qm.hbase.reverse.pipeline.HBaseVehicleMasterLoad$.<init>(HBaseVehicleMasterLoad.scala:32)
at com.dta.dl.ct.qm.hbase.reverse.pipeline.HBaseVehicleMasterLoad$.<clinit>(HBaseVehicleMasterLoad.scala)
... 13 more
You need to create this folder on the driver node before collecting event logs (that's by design).
To do so, one way could be adding the property spark.history.fs.logDirectory (present at the spark-defaults.conf file) on a global init script as described here.
Please make sure that the folder defined on that property exist and can be accessed from the driver node
I'm trying to deploy ignite so that I can use the shared RDD/Dataframe cache for my spark cluster. I've followed the spark install instructions and choose to deploy into my existing yarn cluster running spark. I'm using HDP to deploy spark.
I've already verified that Resource Manager and History server are listening on the ports below and I can telnet to each port. What am I doing wrong? Am I not deploying this the way it is intended?
I'm running:
yarn jar ignite-yarn-2.6.0.jar ./ignite-yarn-2.6.0.jar ../../../cluster.properties
Error below:
18/09/24 22:13:38 INFO client.RMProxy: Connecting to ResourceManager at dev01clus02.dna.local/172.31.31.5:8050
18/09/24 22:13:38 INFO client.AHSProxy: Connecting to Application History server at dev01clus02.dna.local/172.31.31.5:10200
Exception in thread "main" java.lang.RuntimeException: Failed update ignite.
at org.apache.ignite.yarn.IgniteProvider.updateIgnite(IgniteProvider.java:243)
at org.apache.ignite.yarn.IgniteProvider.getIgnite(IgniteProvider.java:93)
at org.apache.ignite.yarn.IgniteYarnClient.getIgnite(IgniteYarnClient.java:194)
at org.apache.ignite.yarn.IgniteYarnClient.main(IgniteYarnClient.java:84)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:233)
at org.apache.hadoop.util.RunJar.main(RunJar.java:148)
Caused by: java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:209)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:246)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:286)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at sun.net.www.http.HttpClient.parseHTTPHeader(HttpClient.java:704)
at sun.net.www.http.HttpClient.parseHTTP(HttpClient.java:647)
at sun.net.www.http.HttpClient.parseHTTP(HttpClient.java:675)
at sun.net.www.protocol.http.HttpURLConnection.getInputStream0(HttpURLConnection.java:1569)
at sun.net.www.protocol.http.HttpURLConnection.getInputStream(HttpURLConnection.java:1474)
at java.net.HttpURLConnection.getResponseCode(HttpURLConnection.java:480)
at org.apache.ignite.yarn.IgniteProvider.updateIgnite(IgniteProvider.java:220)
... 9 more
It looks like a piece of insfrastructure, provided by GridGain for Apache Ignite project, does not work currently. I'll raise the issue.
In the meantime, you can provide IGNITE_PATH property (in config, system properties or env) pointed to unzipped Apache Ignite 2.6 distribution directory to avoid downloading attempts altogether.
After running the command
spark-submit --class org.apache.spark.examples.SparkPi --proxy-user yarn --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 2g --executor-cores 1 --queue default ./examples/jars/spark-examples_2.11-2.3.0.jar 10000
I get this in the output and it keeps on retrying. Where am I going wrong? Am I missing some configuration?
I have created a new user for yarn and running that user.
WARN Utils:66 - Your hostname, ukaleem-HP-EliteBook-850-G3 resolves to a loopback address: 127.0.1.1; using 10.XX.XX.XX instead (on interface enp0s31f6)
2018-06-14 16:50:41 WARN Utils:66 - Set SPARK_LOCAL_IP if you need to bind to another address
Warning: Local jar /home/yarn/Documents/Scala-Examples/./examples/jars/spark-examples_2.11-2.3.0.jar does not exist, skipping.
2018-06-14 16:50:42 INFO RMProxy:98 - Connecting to ResourceManager at /0.0.0.0:8032
2018-06-14 16:50:44 INFO Client:871 - Retrying connect to server: 0.0.0.0/0.0.0.0:8032. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
And in the end, it gives the exception
Exception in thread "main" java.net.ConnectException: Call From ukaleem-HP-EliteBook-850-G3/127.0.1.1 to 0.0.0.0:8032 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.GeneratedConstructorAccessor4.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy8.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationClientProtocolPBClientImpl.getClusterMetrics(ApplicationClientProtocolPBClientImpl.java:206)
at sun.reflect.GeneratedMethodAccessor7.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy9.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.getYarnClusterMetrics(YarnClientImpl.java:487)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.internal.Logging$class.logInfo(Logging.scala:54)
at org.apache.spark.deploy.yarn.Client.logInfo(Client.scala:59)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:154)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1146)
at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1518)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:879)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:179)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:177)
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.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:177)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:227)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:136)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 28 more
2018-06-14 17:10:53 INFO ShutdownHookManager:54 - Shutdown hook called
2018-06-14 17:10:53 INFO ShutdownHookManager:54 - Deleting directory /tmp/spark-5bddb7f3-165f-451c-8ab4-bb7729f4237c
EDIT : After adding config files to my spark/conf dir, I get this error now.
The files I added are
*core-site.xml
dfs.hosts
masters
slaves
yarn-site.xml*
And some more. What I understand is that I only need yarn-site.xml to tell spark the location of the yarn cluster. (ids, address, hostname etc).
All this time I had been thinking that even we want to submit a job on Yarn these config need to go in /etc/Hadoop dir not in Spark/conf. Whats the purpose of installing hadoop then (other than communicating)?
And following this question. If the config need to go in spark/conf then HADOOP_CONF_DIR & YARN_CONF_DIR should point to etc/hadoop dir or spark/conf?
INFO client.ConfiguredRMFailoverProxyProvider: Failing over to rm2
18/06/19 11:04:50 INFO retry.RetryInvocationHandler: Exception while invoking getClusterMetrics of class ApplicationClientProtocolPBClientImpl over rm2 after 1 fail over attempts. Trying to fail over after sleeping for 38176ms.
java.net.ConnectException: Call From ukaleem-HP-EliteBook-850-G3/127.0.1.1 to svc-hadoop-mgnt-pre-c2-01.jamba.net:8032 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy13.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationClientProtocolPBClientImpl.getClusterMetrics(ApplicationClientProtocolPBClientImpl.java:206)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy14.getClusterMetrics(Unknown Source)
at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.getYarnClusterMetrics(YarnClientImpl.java:487)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.deploy.yarn.Client$$anonfun$submitApplication$1.apply(Client.scala:155)
at org.apache.spark.internal.Logging$class.logInfo(Logging.scala:54)
at org.apache.spark.deploy.yarn.Client.logInfo(Client.scala:59)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:154)
at org.apache.spark.deploy.yarn.Client.run(Client.scala:1146)
at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1518)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:879)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:179)
at org.apache.spark.deploy.SparkSubmit$$anon$1.run(SparkSubmit.scala:177)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:177)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:227)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:136)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 29 more
Assuming you have a fully distributed yarn cluster: your spark-submit script is unable to find the configuration for the yarn resourcemanager (basically the yarn master node). Ensure you have HADOOP_CONF_DIR properly set in your environment, and that it points to your cluster's configuration. Specifically your yarn-site.xml.
Edit: more detail
The hadoop package comes with both server and client software. The server software would be the many daemons that run that make up the cluster. If your workstation is acting as a client (using that term loosely, not fully related to sparks --deploy-mode), then the hadoop client software must know the network locations of the server daemons running in the cluster. If your yarn-site.xml is empty, then it is pulling it's default values from yarn-defauls.xml (which is hard-coded, I believe).
Assuming your cluster is not running in HA mode, and is a mostly default configuration, then your workstation's yarn-site.xml should contain at least an entry like the following:
<property>
<name>yarn.resourcemanager.hostname</name>
<value>rm-host.yourdomain.com</value>
</property>
Obviously, replace the hostname with the hostname where your actual resource manager is running. Of course, any spark interaction with HDFS will require a properly configured hdfs-site.xml, etc.
Some cluster managing software will have something like "generate client configs" (thinking of my cloudera experience specifically), which will give you a .tar.gz with all of the config files correctly populated to access the cluster from an external workstation.
Further recommendations:
If you plan to do spark on yarn a lot in this cluster, spark recommends making sure that you have the external shuffle service configured to launch with your yarn node managers. (Please bear in mind, this config directive would have to be present in the yarn-site.xml where yarn's node manager services are running, not on your workstation.
If you are running this on your local machine,
Update your /etc/hosts file, Enter 127.0.0.1 against your hostname.
Use this list of jars, I can successfully connect SQuirrel SQL to Spark 2.2.1:
commons-logging-1.1.3.jar
hadoop-common-2.7.3.jar
hive-exec-1.2.1.spark2.jar
hive-jdbc-1.2.1.spark2.jar
hive-metastore-1.2.1.spark2.jar
http-client-1.0.4.jar
httpclient-4.5.2.jar
httpcore-4.4.4.jar
libfb303-0.9.3.jar
libthrift-0.9.3.jar
log4j-1.2.17.jar
slf4j-api-1.7.16.jar
slf4j-log4j12-1.7.16.jar
spark-hive-thriftserver_2.11-2.2.1.jar
spark-hive_2.11-2.2.1.jar
spark-network-common_2.11-2.2.1.jar
I think the above jars are more than necessary. But when trying to connect JMeter 3.3 to same Spark 2.2.1 ThriftServer with them, I got below error message
enter code here Cannot create PoolableConnectionFactory (Method not supported)
The JDBC configuration is here:
The full response at Jmeter is here:
Thread Name: test 1-1
Sample Start: 2018-04-03 13:34:43 CST
Load time: 511
Connect Time: 510
Latency: 0
Size in bytes: 62
Sent bytes:0
Headers size in bytes: 0
Body size in bytes: 62
Sample Count: 1
Error Count: 1
Data type ("text"|"bin"|""): text
Response code: null 0
Response message: java.sql.SQLException: Cannot create PoolableConnectionFactory (Method not supported)
Response headers:
SampleResult fields:
ContentType: text/plain
DataEncoding: UTF-8
I also try to use newer Hive JDBC driver 2.3.0, but it is obviously that is not worked with Spark 2.2.1 either on beeline or any others including Jmeter.
Error message when using beeline with Hive JDBC driver 2.3.0 is here:
$ beeline -u jdbc:hive2://<hostip>:10000/tpch_sf100_orc -n rxxxds
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/apache-hive-2.3.0-bin/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/apache-tez-0.9.0-bin/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/hadoop-2.9.0/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Connecting to jdbc:hive2://<hostip>:10000/tpch_sf100_orc
18/04/03 13:41:58 [main]: ERROR jdbc.HiveConnection: Error opening session
org.apache.thrift.TApplicationException: Required field 'client_protocol' is unset! Struct:TOpenSessionReq(client_protocol:null, configuration:{set:hiveconf:hive.server2.thrift.resultset.default.fetch.size=1000, use:database=tpch_sf100_orc})
at org.apache.thrift.TApplicationException.read(TApplicationException.java:111) ~[hive-exec-2.3.0.jar:2.3.0]
at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:79) ~[hive-exec-2.3.0.jar:2.3.0]
at org.apache.hive.service.rpc.thrift.TCLIService$Client.recv_OpenSession(TCLIService.java:168) ~[hive-exec-2.3.0.jar:2.3.0]
at org.apache.hive.service.rpc.thrift.TCLIService$Client.OpenSession(TCLIService.java:155) ~[hive-exec-2.3.0.jar:2.3.0]
at org.apache.hive.jdbc.HiveConnection.openSession(HiveConnection.java:680) [hive-jdbc-2.3.0.jar:2.3.0]
at org.apache.hive.jdbc.HiveConnection.<init>(HiveConnection.java:200) [hive-jdbc-2.3.0.jar:2.3.0]
at org.apache.hive.jdbc.HiveDriver.connect(HiveDriver.java:107) [hive-jdbc-2.3.0.jar:2.3.0]
at java.sql.DriverManager.getConnection(DriverManager.java:664) [?:1.8.0_112]
at java.sql.DriverManager.getConnection(DriverManager.java:208) [?:1.8.0_112]
at org.apache.hive.beeline.DatabaseConnection.connect(DatabaseConnection.java:145) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.DatabaseConnection.getConnection(DatabaseConnection.java:209) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.Commands.connect(Commands.java:1641) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.Commands.connect(Commands.java:1536) [hive-beeline-2.3.0.jar:2.3.0]
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[?:1.8.0_112]
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:1.8.0_112]
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:1.8.0_112]
at java.lang.reflect.Method.invoke(Method.java:498) ~[?:1.8.0_112]
at org.apache.hive.beeline.ReflectiveCommandHandler.execute(ReflectiveCommandHandler.java:56) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.execCommandWithPrefix(BeeLine.java:1274) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.dispatch(BeeLine.java:1313) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.connectUsingArgs(BeeLine.java:867) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.initArgs(BeeLine.java:776) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.begin(BeeLine.java:1010) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.mainWithInputRedirection(BeeLine.java:519) [hive-beeline-2.3.0.jar:2.3.0]
at org.apache.hive.beeline.BeeLine.main(BeeLine.java:501) [hive-beeline-2.3.0.jar:2.3.0]
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[?:1.8.0_112]
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:1.8.0_112]
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:1.8.0_112]
at java.lang.reflect.Method.invoke(Method.java:498) ~[?:1.8.0_112]
at org.apache.hadoop.util.RunJar.run(RunJar.java:239) [hadoop-common-2.9.0.jar:?]
at org.apache.hadoop.util.RunJar.main(RunJar.java:153) [hadoop-common-2.9.0.jar:?]
18/04/03 13:41:58 [main]: WARN jdbc.HiveConnection: Failed to connect to <hostip>:10000
Error: Could not open client transport with JDBC Uri: jdbc:hive2://<hostip>:10000/tpch_sf100_orc: Could not establish connection to jdbc:hive2://<hostip>:10000/tpch_sf100_orc: Required field 'client_protocol' is unset! Struct:TOpenSessionReq(client_protocol:null, configuration:{set:hiveconf:hive.server2.thrift.resultset.default.fetch.size=1000, use:database=tpch_sf100_orc}) (state=08S01,code=0)
Beeline version 2.3.0 by Apache Hive
What else can be done to connect JMeter to Spark?
Most probably this is due to client and server libraries mismatch, you need to use the same version as on the server.
So identify which version of hive is running on your server and download appropriate hive-jdbc jar and all the dependencies (you can retrieve them using i.e. Maven Dependency Plugin) and update the ones in JMeter Classpath with the correct versions.
It might be better to use "clean" JMeter installation for this to avoid possible jar hell so it is a good time to upgrade to JMeter 4.0
You could also build your own "JDBC sampler" and add/adapt just few line of code from the original to make it works. I had to do that for Hive and Phoenix support 4 years ago and it worked. It required a Timeout method that was not implemented back then.
Here are the sources:
https://github.com/csalperwyck/JMeterJDBCSamplerWithOutTimeOut