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Title | Views | Posted |
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923 | 12-04-2020 07:46 AM | |
1198 | 11-01-2019 12:19 PM | |
1631 | 11-01-2019 09:07 AM | |
2552 | 10-30-2019 06:10 AM | |
1280 | 10-28-2019 10:03 AM |
10-31-2019
09:47 AM
Thank you very much. It helped me to find the error, in the end my provider had in the DC a schedule different from the host. synchronize and work. Greetings
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10-28-2019
10:03 AM
If clusterusers is a group then you should have a space separator between users and groups in acl config. Something like yarn.scheduler.capacity.root.default.acl_submit_applications=yarn,ambari-qa clusterusers
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10-24-2019
09:42 AM
@rguruvannagari Thanks for the quick reply and i able to start the process based on your inputs. While running the spark application i am getting the below issue, Help to fix the issue. 19/10/24 16:36:09 INFO ContextHandler: Started o.s.j.s.ServletContextHandler@4a0df195{/history,null,AVAILABLE,@Spark} 19/10/24 16:36:09 INFO HistoryServer: Bound HistoryServer to 0.0.0.0, and started at http://hadoop02.prod.phenom.local:18081 [murali.kumpatla@hadoop02 spark2]$ spark-shell Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 19/10/24 16:37:20 ERROR SparkContext: Error initializing SparkContext. org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master. at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:89) at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:63) at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:164) at org.apache.spark.SparkContext.<init>(SparkContext.scala:500) at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2498) at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:934) at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:925) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:925) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:103) at $line3.$read$$iw$$iw.<init>(<console>:15) at $line3.$read$$iw.<init>(<console>:43) at $line3.$read.<init>(<console>:45) at $line3.$read$.<init>(<console>:49) at $line3.$read$.<clinit>(<console>) at $line3.$eval$.$print$lzycompute(<console>:7) at $line3.$eval$.$print(<console>:6) at $line3.$eval.$print(<console>) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:793) at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1054) at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:645) at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:644) at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31) at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19) at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:644) at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:576) at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:572) at scala.tools.nsc.interpreter.IMain$$anonfun$quietRun$1.apply(IMain.scala:231) at scala.tools.nsc.interpreter.IMain$$anonfun$quietRun$1.apply(IMain.scala:231) at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:221) at scala.tools.nsc.interpreter.IMain.quietRun(IMain.scala:231) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply(SparkILoop.scala:88) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1$$anonfun$apply$mcV$sp$1.apply(SparkILoop.scala:88) at scala.collection.immutable.List.foreach(List.scala:392) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:88) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:88) at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:88) at scala.tools.nsc.interpreter.ILoop.savingReplayStack(ILoop.scala:91) at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:87) at org.apache.spark.repl.SparkILoop$$anonfun$process$1$$anonfun$org$apache$spark$repl$SparkILoop$$anonfun$$loopPostInit$1$1.apply$mcV$sp(SparkILoop.scala:170) at org.apache.spark.repl.SparkILoop$$anonfun$process$1$$anonfun$org$apache$spark$repl$SparkILoop$$anonfun$$loopPostInit$1$1.apply(SparkILoop.scala:158) at org.apache.spark.repl.SparkILoop$$anonfun$process$1$$anonfun$org$apache$spark$repl$SparkILoop$$anonfun$$loopPostInit$1$1.apply(SparkILoop.scala:158) at scala.tools.nsc.interpreter.ILoop$$anonfun$mumly$1.apply(ILoop.scala:189) at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:221) at scala.tools.nsc.interpreter.ILoop.mumly(ILoop.scala:186) at org.apache.spark.repl.SparkILoop$$anonfun$process$1.org$apache$spark$repl$SparkILoop$$anonfun$$loopPostInit$1(SparkILoop.scala:158) at org.apache.spark.repl.SparkILoop$$anonfun$process$1$$anonfun$startup$1$1.apply(SparkILoop.scala:226) at org.apache.spark.repl.SparkILoop$$anonfun$process$1$$anonfun$startup$1$1.apply(SparkILoop.scala:206) at org.apache.spark.repl.SparkILoop$$anonfun$process$1.withSuppressedSettings$1(SparkILoop.scala:194) at org.apache.spark.repl.SparkILoop$$anonfun$process$1.startup$1(SparkILoop.scala:206) at org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply$mcZ$sp(SparkILoop.scala:241) at org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:141) at org.apache.spark.repl.SparkILoop$$anonfun$process$1.apply(SparkILoop.scala:141) at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97) at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:141) at org.apache.spark.repl.Main$.doMain(Main.scala:76) at org.apache.spark.repl.Main$.main(Main.scala:56) at org.apache.spark.repl.Main.main(Main.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:904) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 19/10/24 16:37:20 WARN YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request executors before the AM has registered! 19/10/24 16:37:20 WARN MetricsSystem: Stopping a MetricsSystem that is not running org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master. at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:89) at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:63) at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:164) at org.apache.spark.SparkContext.<init>(SparkContext.scala:500) at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2498) at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:934) at org.apache.spark.sql.SparkSession$Builder$$anonfun$7.apply(SparkSession.scala:925) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:925) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:103) ... 62 elided <console>:14: error: not found: value spark import spark.implicits._ ^ <console>:14: error: not found: value spark import spark.sql ^ Welcome to ____
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10-22-2019
12:06 PM
Check the config property hadoop.http.authentication.type, if this is set to kerberos , then accessing UIs would need kerberos credentials on client. By default this is et to kerberos in HDP 3.x version when cluster is kerberized. If you want to disable kerberos auth then change below config properties. -> Ambari > HDFS> Configs> in core-site hadoop.http.authentication.type=simple hadoop.http.authentication.simple.anonymous.allowed=true
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07-16-2018
06:23 AM
Thank you @rguruvannagari I just enabled SolrCloud and restarted. I don't see audit error anymore.
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04-16-2017
06:00 PM
@rguruvannagari Thank you it works. I followed the hortonworks hello wold tutorial. it doesn't mentioned that.
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04-13-2017
12:27 PM
Yes, this node was part of one of the old HDP installations. However we have uninstalled that now and shifted to 2.5.3, a more stabler release. Have undertaken the current steps : 1) Deleted old 2.3.4 and current folder under /usr/hdp 2) Restarted the ambari agent 3) Added the new host again and took care of host run check issues (like pre-existing old 2.3.4 packages and users and folders. Have removed them) 4) Node was successfully added. But had to install a new rpm python-argparse 5) Added DataNode, Node Manager and clients in the new node successfully Through ambari I can now see this node added successfully with required services.
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04-18-2017
10:01 AM
Finally this problem is solved by change the hostname format. the hostname could not contain "_" tag.
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05-03-2017
05:47 PM
hello i hit the same error and ambari-server.log shows "ERROR [ambari-client-thread-25] HostImpl:1374 - Config inconsistency exists: unknown configType"
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04-17-2017
07:16 PM
And also, we had to change another default configuration for Ambari Metrics: You can see that by default, the HBase temporary directory is created inside /usr/hdp/, which should not.
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