Question

我在单个Ubuntu 14.04服务器上安装了一个新的Cloudera 5.4实例，并希望运行一个spark应用程序。

这是命令：

sudo -uhdfs spark-submit --class org.apache.spark.examples.SparkPi --deploy-mode cluster --master yarn /opt/cloudera/parcels/CDH-5.4.5-1.cdh5.4.5.p0.7/jars/spark-examples-1.3.0-cdh5.4.5-hadoop2.6.0-cdh5.4.5.jar

这是输出：

SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/cloudera/parcels/CDH-5.4.5-1.cdh5.4.5.p0.7/jars/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/cloudera/parcels/CDH-5.4.5-1.cdh5.4.5.p0.7/jars/avro-tools-1.7.6-cdh5.4.5.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]
15/08/29 12:07:56 INFO RMProxy: Connecting to ResourceManager at chd2.moneyball.guru/104.131.78.0:8032
15/08/29 12:07:56 INFO Client: Requesting a new application from cluster with 1 NodeManagers
15/08/29 12:07:56 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (1750 MB per container)
15/08/29 12:07:56 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
15/08/29 12:07:56 INFO Client: Setting up container launch context for our AM
15/08/29 12:07:56 INFO Client: Preparing resources for our AM container
15/08/29 12:07:57 INFO Client: Uploading resource file:/opt/cloudera/parcels/CDH-5.4.5-1.cdh5.4.5.p0.7/jars/spark-examples-1.3.0-cdh5.4.5-hadoop2.6.0-cdh5.4.5.jar -> hdfs://chd2.moneyball.guru:8020/user/hdfs/.sparkStaging/application_1440861466017_0007/spark-examples-1.3.0-cdh5.4.5-hadoop2.6.0-cdh5.4.5.jar
15/08/29 12:07:57 INFO Client: Setting up the launch environment for our AM container
15/08/29 12:07:57 INFO SecurityManager: Changing view acls to: hdfs
15/08/29 12:07:57 INFO SecurityManager: Changing modify acls to: hdfs
15/08/29 12:07:57 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hdfs); users with modify permissions: Set(hdfs)
15/08/29 12:07:57 INFO Client: Submitting application 7 to ResourceManager
15/08/29 12:07:57 INFO YarnClientImpl: Submitted application application_1440861466017_0007
15/08/29 12:07:58 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:07:58 INFO Client: 
     client token: N/A
     diagnostics: N/A
     ApplicationMaster host: N/A
     ApplicationMaster RPC port: -1
     queue: root.hdfs
     start time: 1440864477580
     final status: UNDEFINED
     tracking URL: http://chd2.moneyball.guru:8088/proxy/application_1440861466017_0007/
     user: hdfs
15/08/29 12:07:59 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:00 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:01 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:02 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:03 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:04 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:05 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:06 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED)
15/08/29 12:08:07 INFO Client: Application report for application_1440861466017_0007 (state: ACCEPTED
.....

它将显示循环中的最后一行。你能帮帮忙吗？如果您还有其他需要，请告诉我。

Answer 1

我增加了yarn.nodemanager.resource.memory-mb。现在一切都好了

Answer 2

当Yarn的插槽被其他作业占用且集群处于其容量时，就会发生这种情况。作业停留在ACCEPTED状态，等待轮到它运行。您是否可以从Yarn Resource Manager UI查看是否在集群上运行了其他任何可能会降低此应用程序速度的内容？假设您的RM地址仍为104.131.78.0（如日志中所示），可以访问http://104.131.78.0:8088来访问RM UI。您应该能够看到1）如果您的群集上正在运行任何其他应用程序，并且2）导航到http://ApplicationMasterAddress:4040上运行的Spark UI以进行进一步分析。

Answer 3

我在Spark 1.5.2上遇到了类似的问题，并且能够通过使用Scala object来包含我的main函数而不是Scala class <来解决这个问题。 / p>

Spark应用程序处于ACCEPTED状态

3 个答案: