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From Andrew Or <and...@databricks.com>
Subject Re: Yarn configuration file doesn't work when run with yarn-client mode
Date Tue, 20 May 2014 18:25:50 GMT
Hi Gaurav and Arun,

Your settings seem reasonable; as long as YARN_CONF_DIR or HADOOP_CONF_DIR
is properly set, the application should be able to find the correct RM
port. Have you tried running the examples in yarn-client mode, and your
custom application in yarn-standalone (now yarn-cluster) mode?



2014-05-20 5:17 GMT-07:00 gaurav.dasgupta <gaurav.dg19@gmail.com>:

> Few more details I would like to provide (Sorry as I should have provided
> with the previous post):
>
>  *- Spark Version = 0.9.1 (using pre-built spark-0.9.1-bin-hadoop2)
>  - Hadoop Version = 2.4.0 (Hortonworks)
>  - I am trying to execute a Spark Streaming program*
>
> Because I am using Hortornworks Hadoop (HDP), YARN is configured with
> different port numbers than the default Apache's default configurations.
> For
> example, *resourcemanager.address* is <IP>:8050 in HDP whereas it defaults
> to <IP>:8032.
>
> When I run the Spark examples using bin/run-example, I can see in the
> console logs, that it is connecting to the right port configured by HDP,
> i.e., 8050. Please refer the below console log:
>
> */[root@host spark-0.9.1-bin-hadoop2]# SPARK_YARN_MODE=true
>
> SPARK_JAR=assembly/target/scala-2.10/spark-assembly_2.10-0.9.1-hadoop2.2.0.jar
>
> SPARK_YARN_APP_JAR=examples/target/scala-2.10/spark-examples_2.10-assembly-0.9.1.jar
> bin/run-example org.apache.spark.examples.HdfsTest yarn-client
> /user/root/test
> SLF4J: Class path contains multiple SLF4J bindings.
> SLF4J: Found binding in
>
> [jar:file:/usr/local/spark-0.9.1-bin-hadoop2/examples/target/scala-2.10/spark-examples_2.10-assembly-0.9.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
> SLF4J: Found binding in
>
> [jar:file:/usr/local/spark-0.9.1-bin-hadoop2/assembly/target/scala-2.10/spark-assembly_2.10-0.9.1-hadoop2.2.0.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.slf4j.impl.Log4jLoggerFactory]
> 14/05/20 06:55:29 INFO slf4j.Slf4jLogger: Slf4jLogger started
> 14/05/20 06:55:29 INFO Remoting: Starting remoting
> 14/05/20 06:55:29 INFO Remoting: Remoting started; listening on addresses
> :[akka.tcp://spark@<IP:60988]
> 14/05/20 06:55:29 INFO Remoting: Remoting now listens on addresses:
> [akka.tcp://spark@&lt;IP>:60988]
> 14/05/20 06:55:29 INFO spark.SparkEnv: Registering BlockManagerMaster
> 14/05/20 06:55:29 INFO storage.DiskBlockManager: Created local directory at
> /tmp/spark-local-20140520065529-924f
> 14/05/20 06:55:29 INFO storage.MemoryStore: MemoryStore started with
> capacity 4.2 GB.
> 14/05/20 06:55:29 INFO network.ConnectionManager: Bound socket to port
> 35359
> with id = ConnectionManagerId(<IP>,35359)
> 14/05/20 06:55:29 INFO storage.BlockManagerMaster: Trying to register
> BlockManager
> 14/05/20 06:55:29 INFO storage.BlockManagerMasterActor$BlockManagerInfo:
> Registering block manager <IP>:35359 with 4.2 GB RAM
> 14/05/20 06:55:29 INFO storage.BlockManagerMaster: Registered BlockManager
> 14/05/20 06:55:29 INFO spark.HttpServer: Starting HTTP Server
> 14/05/20 06:55:29 INFO server.Server: jetty-7.x.y-SNAPSHOT
> 14/05/20 06:55:29 INFO server.AbstractConnector: Started
> SocketConnector@0.0.0.0:59418
> 14/05/20 06:55:29 INFO broadcast.HttpBroadcast: Broadcast server started at
> http://<IP>:59418
> 14/05/20 06:55:29 INFO spark.SparkEnv: Registering MapOutputTracker
> 14/05/20 06:55:29 INFO spark.HttpFileServer: HTTP File server directory is
> /tmp/spark-fc34fdc8-d940-420b-b184-fc7a8a65501a
> 14/05/20 06:55:29 INFO spark.HttpServer: Starting HTTP Server
> 14/05/20 06:55:29 INFO server.Server: jetty-7.x.y-SNAPSHOT
> 14/05/20 06:55:29 INFO server.AbstractConnector: Started
> SocketConnector@0.0.0.0:53425
> 14/05/20 06:55:29 INFO server.Server: jetty-7.x.y-SNAPSHOT
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/storage/rdd,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/storage,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/stages/stage,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/stages/pool,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/stages,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/environment,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/executors,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/metrics/json,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/static,null}
> 14/05/20 06:55:29 INFO handler.ContextHandler: started
> o.e.j.s.h.ContextHandler{/,null}
> 14/05/20 06:55:29 INFO server.AbstractConnector: Started
> SelectChannelConnector@0.0.0.0:4040
> 14/05/20 06:55:29 INFO ui.SparkUI: Started Spark Web UI at http://
> <IP>:4040
> 14/05/20 06:55:29 WARN util.NativeCodeLoader: Unable to load native-hadoop
> library for your platform... using builtin-java classes where applicable
> 14/05/20 06:55:29 INFO spark.SparkContext: Added JAR
>
> /usr/local/spark-0.9.1-bin-hadoop2/examples/target/scala-2.10/spark-examples_2.10-assembly-0.9.1.jar
> at http://<IP>:53425/jars/spark-examples_2.10-assembly-0.9.1.jar with
> timestamp 1400586929921
> 14/05/20 06:55:30 INFO client.RMProxy: Connecting to ResourceManager at
> <IP>:8050
> 14/05/20 06:55:30 INFO yarn.Client: Got Cluster metric info from
> ApplicationsManager (ASM), number of NodeManagers: 9
> 14/05/20 06:55:30 INFO yarn.Client: Queue info ... queueName: default,
> queueCurrentCapacity: 0.0, queueMaxCapacity: 1.0,/*
>
> But, when I running my own custom spark streaming code, it is trying to
> connect to port number 8032 instead and hence unable to connect. Refer the
> below log:
>
> */[root@host spark-0.9.1-bin-hadoop2]# SPARK_YARN_MODE=true
>
> SPARK_JAR=assembly/target/scala-2.10/spark-assembly_2.10-0.9.1-hadoop2.2.0.jar
> SPARK_YARN_APP_JAR=/home/gaurav/SparkStreamExample.jar java -cp
>
> /home/gaurav/SparkStreamExample.jar:assembly/target/scala-2.10/spark-assembly_2.10-0.9.1-hadoop2.2.0.jar
> SparkStreamExample yarn-client <IP> 9999
> log4j:WARN No appenders could be found for logger
> (akka.event.slf4j.Slf4jLogger).
> log4j:WARN Please initialize the log4j system properly.
> log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for
> more info.
> 14/05/20 07:04:38 INFO SparkEnv: Using Spark's default log4j profile:
> org/apache/spark/log4j-defaults.properties
> 14/05/20 07:04:38 INFO SparkEnv: Registering BlockManagerMaster
> 14/05/20 07:04:38 INFO DiskBlockManager: Created local directory at
> /tmp/spark-local-20140520070438-5eae
> 14/05/20 07:04:38 INFO MemoryStore: MemoryStore started with capacity 4.2
> GB.
> 14/05/20 07:04:38 INFO ConnectionManager: Bound socket to port 49869 with
> id
> = ConnectionManagerId(<IP>,49869)
> 14/05/20 07:04:38 INFO BlockManagerMaster: Trying to register BlockManager
> 14/05/20 07:04:38 INFO BlockManagerMasterActor$BlockManagerInfo:
> Registering
> block manager <IP>:49869 with 4.2 GB RAM
> 14/05/20 07:04:38 INFO BlockManagerMaster: Registered BlockManager
> 14/05/20 07:04:38 INFO HttpServer: Starting HTTP Server
> 14/05/20 07:04:38 INFO HttpBroadcast: Broadcast server started at
> http://<IP>:36946
> 14/05/20 07:04:38 INFO SparkEnv: Registering MapOutputTracker
> 14/05/20 07:04:38 INFO HttpFileServer: HTTP File server directory is
> /tmp/spark-414ba274-adc0-4a0e-b1a4-9c1f048cbf37
> 14/05/20 07:04:38 INFO HttpServer: Starting HTTP Server
> 14/05/20 07:04:38 INFO SparkUI: Started Spark Web UI at http://<IP>:4040
> 14/05/20 07:04:38 WARN NativeCodeLoader: Unable to load native-hadoop
> library for your platform... using builtin-java classes where applicable
> 14/05/20 07:04:38 INFO SparkContext: Added JAR
> /home/gaurav/SparkStreamExample.jar at
> http://<IP>:40053/jars/SparkStreamExample.jar with timestamp 1400587478500
> 14/05/20 07:04:38 INFO RMProxy: Connecting to ResourceManager at
> /0.0.0.0:8032
> 14/05/20 07:04:39 INFO Client: 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=1 SECONDS)
> 14/05/20 07:04:40 INFO Client: Retrying connect to server:
> 0.0.0.0/0.0.0.0:8032. Already tried 1 time(s); retry policy is
> RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1 SECONDS)
> 14/05/20 07:04:41 INFO Client: Retrying connect to server:
> 0.0.0.0/0.0.0.0:8032. Already tried 2 time(s); retry policy is
> RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1 SECONDS)
> 14/05/20 07:04:42 INFO Client: Retrying connect to server:
> 0.0.0.0/0.0.0.0:8032. Already tried 3 time(s); retry policy is
> RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1 SECONDS)/*
>
> Do I need to specify the YARN ports configured by HDP to Spark somehow? How
> the example jobs can detect the correct YARN ports?
>
> Thanks in advance.
>
> -- Gaurav
>
>
>
> --
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