无论用YARN cluster和YARN client来跑,均会出现如下问题。

[spark@master spark-1.6.1-bin-hadoop2.6]$ jps
2049 NameNode
2706 Jps
2372 ResourceManager
2660 Master
2203 SecondaryNameNode
[spark@master spark-1.6.1-bin-hadoop2.6]$ $SPARK_HOME/bin/spark-submit \
> --master yarn\
> --deploy-mode client \
> --name javawordcount \
> --num-executors 1 \
> --driver-memory 512m \
> --executor-memory 512m \
> --executor-cores 1 \
> --class zhouls.bigdata.MyJavaWordCount \
> /home/spark/testspark/mySpark-1.0-SNAPSHOT.jar \
> hdfs://master:9000/testspark/inputData/wordcount/wc.txt \
> hdfs://master:9000/testspark/outData/MyJavaWordCount
17/03/30 20:36:57 INFO spark.SparkContext: Running Spark version 1.6.1
17/03/30 20:36:58 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/03/30 20:36:59 INFO spark.SecurityManager: Changing view acls to: spark
17/03/30 20:36:59 INFO spark.SecurityManager: Changing modify acls to: spark
17/03/30 20:36:59 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(spark); users with modify permissions: Set(spark)
17/03/30 20:37:01 INFO util.Utils: Successfully started service 'sparkDriver' on port 54074.
17/03/30 20:37:03 INFO slf4j.Slf4jLogger: Slf4jLogger started
17/03/30 20:37:03 INFO Remoting: Starting remoting
17/03/30 20:37:04 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.80.10:52224]
17/03/30 20:37:04 INFO util.Utils: Successfully started service 'sparkDriverActorSystem' on port 52224.
17/03/30 20:37:04 INFO spark.SparkEnv: Registering MapOutputTracker
17/03/30 20:37:04 INFO spark.SparkEnv: Registering BlockManagerMaster
17/03/30 20:37:04 INFO storage.DiskBlockManager: Created local directory at /tmp/blockmgr-b6575213-cc8e-4a50-bc83-6ab089a65341
17/03/30 20:37:04 INFO storage.MemoryStore: MemoryStore started with capacity 146.2 MB
17/03/30 20:37:05 INFO spark.SparkEnv: Registering OutputCommitCoordinator
17/03/30 20:37:06 INFO server.Server: jetty-8.y.z-SNAPSHOT
17/03/30 20:37:06 INFO server.AbstractConnector: Started SelectChannelConnector@0.0.0.0:4040
17/03/30 20:37:06 INFO util.Utils: Successfully started service 'SparkUI' on port 4040.
17/03/30 20:37:06 INFO ui.SparkUI: Started SparkUI at http://192.168.80.10:4040
17/03/30 20:37:06 INFO spark.HttpFileServer: HTTP File server directory is /tmp/spark-fdfdb880-f6cf-47eb-8981-1176e657d466/httpd-f5d25b97-30bd-4f13-b925-d96026063a63
17/03/30 20:37:06 INFO spark.HttpServer: Starting HTTP Server
17/03/30 20:37:06 INFO server.Server: jetty-8.y.z-SNAPSHOT
17/03/30 20:37:06 INFO server.AbstractConnector: Started SocketConnector@0.0.0.0:54651
17/03/30 20:37:06 INFO util.Utils: Successfully started service 'HTTP file server' on port 54651.
17/03/30 20:37:07 INFO spark.SparkContext: Added JAR file:/home/spark/testspark/mySpark-1.0-SNAPSHOT.jar at http://192.168.80.10:54651/jars/mySpark-1.0-SNAPSHOT.jar with timestamp 1490877427613
17/03/30 20:37:08 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.80.10:8032
17/03/30 20:37:09 INFO yarn.Client: Requesting a new application from cluster with 2 NodeManagers
17/03/30 20:37:09 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container)
17/03/30 20:37:09 INFO yarn.Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
17/03/30 20:37:09 INFO yarn.Client: Setting up container launch context for our AM
17/03/30 20:37:09 INFO yarn.Client: Setting up the launch environment for our AM container
17/03/30 20:37:09 INFO yarn.Client: Preparing resources for our AM container
17/03/30 20:37:14 INFO yarn.Client: Uploading resource file:/usr/local/spark/spark-1.6.1-bin-hadoop2.6/lib/spark-assembly-1.6.1-hadoop2.6.0.jar -> hdfs://master:9000/user/spark/.sparkStaging/application_1490877371054_0001/spark-assembly-1.6.1-hadoop2.6.0.jar
17/03/30 20:37:36 INFO yarn.Client: Uploading resource file:/tmp/spark-fdfdb880-f6cf-47eb-8981-1176e657d466/__spark_conf__3748671039525906996.zip -> hdfs://master:9000/user/spark/.sparkStaging/application_1490877371054_0001/__spark_conf__3748671039525906996.zip
17/03/30 20:37:38 INFO spark.SecurityManager: Changing view acls to: spark
17/03/30 20:37:38 INFO spark.SecurityManager: Changing modify acls to: spark
17/03/30 20:37:38 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(spark); users with modify permissions: Set(spark)
17/03/30 20:37:38 INFO yarn.Client: Submitting application 1 to ResourceManager
17/03/30 20:37:39 INFO impl.YarnClientImpl: Submitted application application_1490877371054_0001
17/03/30 20:37:40 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:40 INFO yarn.Client:
     client token: N/A     client token: N/A
     diagnostics: N/A
     ApplicationMaster host: N/A
     ApplicationMaster RPC port: -1
     queue: default
     start time: 1490877458881
     final status: UNDEFINED
     tracking URL: http://master:8088/proxy/application_1490877371054_0001/
     user: spark
17/03/30 20:37:41 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:42 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:43 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:44 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:45 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:46 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:47 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:48 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:49 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:50 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:51 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:52 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:53 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:54 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:55 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:56 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:57 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:58 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:37:59 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:00 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:01 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:02 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:03 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:04 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:05 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:06 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:07 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:08 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:09 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:10 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:12 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:13 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:14 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:15 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:16 INFO yarn.Client: Application report for application_1490877371054_0001 (state: ACCEPTED)
17/03/30 20:38:17 INFO yarn.Client: Application report for application_1490877371054_0001 (state: FAILED)
17/03/30 20:38:17 INFO yarn.Client:
     client token: N/A
     diagnostics: Application application_1490877371054_0001 failed 2 times due to AM Container for appattempt_1490877371054_0001_000002 exited with  exitCode: -103
For more detailed output, check application tracking page:http://master:8088/proxy/application_1490877371054_0001/Then, click on links to logs of each attempt.
Diagnostics: Container [pid=2417,containerID=container_1490877371054_0001_02_000001] is running beyond virtual memory limits. Current usage: 79.2 MB of 1 GB physical memory used; 2.2 GB of 2.1 GB virtual memory used. Killing container.
Dump of the process-tree for container_1490877371054_0001_02_000001 :
    |- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE
    |- 2421 2417 2417 2417 (java) 283 147 2256482304 19967 /usr/local/jdk/jdk1.8.0_60/bin/java -server -Xmx512m -Djava.io.tmpdir=/usr/local/hadoop/hadoop-2.6.0/tmp/nm-local-dir/usercache/spark/appcache/application_1490877371054_0001/container_1490877371054_0001_02_000001/tmp -Dspark.yarn.app.container.log.dir=/usr/local/hadoop/hadoop-2.6.0/logs/userlogs/application_1490877371054_0001/container_1490877371054_0001_02_000001 org.apache.spark.deploy.yarn.ExecutorLauncher --arg 192.168.80.10:54074 --executor-memory 512m --executor-cores 1 --properties-file /usr/local/hadoop/hadoop-2.6.0/tmp/nm-local-dir/usercache/spark/appcache/application_1490877371054_0001/container_1490877371054_0001_02_000001/__spark_conf__/__spark_conf__.properties
    |- 2417 2415 2417 2417 (bash) 0 1 108650496 305 /bin/bash -c /usr/local/jdk/jdk1.8.0_60/bin/java -server -Xmx512m -Djava.io.tmpdir=/usr/local/hadoop/hadoop-2.6.0/tmp/nm-local-dir/usercache/spark/appcache/application_1490877371054_0001/container_1490877371054_0001_02_000001/tmp -Dspark.yarn.app.container.log.dir=/usr/local/hadoop/hadoop-2.6.0/logs/userlogs/application_1490877371054_0001/container_1490877371054_0001_02_000001 org.apache.spark.deploy.yarn.ExecutorLauncher --arg '192.168.80.10:54074' --executor-memory 512m --executor-cores 1 --properties-file /usr/local/hadoop/hadoop-2.6.0/tmp/nm-local-dir/usercache/spark/appcache/application_1490877371054_0001/container_1490877371054_0001_02_000001/__spark_conf__/__spark_conf__.properties 1> /usr/local/hadoop/hadoop-2.6.0/logs/userlogs/application_1490877371054_0001/container_1490877371054_0001_02_000001/stdout 2> /usr/local/hadoop/hadoop-2.6.0/logs/userlogs/application_1490877371054_0001/container_1490877371054_0001_02_000001/stderr Container killed on request. Exit code is 143
Container exited with a non-zero exit code 143
Failing this attempt. Failing the application.
     ApplicationMaster host: N/A
     ApplicationMaster RPC port: -1
     queue: default
     start time: 1490877458881
     final status: FAILED
     tracking URL: http://master:8088/cluster/app/application_1490877371054_0001
     user: spark
17/03/30 20:38:17 INFO yarn.Client: Deleting staging directory .sparkStaging/application_1490877371054_0001
17/03/30 20:38:17 ERROR spark.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:124)
    at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:64)
    at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:530)
    at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
    at zhouls.bigdata.MyJavaWordCount.main(MyJavaWordCount.java:31)
    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:497)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages/stage/kill,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/api,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/static,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/executors/threadDump/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/executors/threadDump,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/executors/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/executors,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/environment/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/environment,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/storage/rdd/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/storage/rdd,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/storage/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/storage,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages/pool/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages/pool,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages/stage/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages/stage,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/stages,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/jobs/job/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/jobs/job,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/jobs/json,null}
17/03/30 20:38:17 INFO handler.ContextHandler: stopped o.s.j.s.ServletContextHandler{/jobs,null}
17/03/30 20:38:17 INFO ui.SparkUI: Stopped Spark web UI at http://192.168.80.10:4040
17/03/30 20:38:17 INFO cluster.YarnClientSchedulerBackend: Shutting down all executors
17/03/30 20:38:17 INFO cluster.YarnClientSchedulerBackend: Asking each executor to shut down
17/03/30 20:38:17 INFO cluster.YarnClientSchedulerBackend: Stopped
17/03/30 20:38:17 INFO spark.MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/03/30 20:38:17 INFO storage.MemoryStore: MemoryStore cleared
17/03/30 20:38:17 INFO storage.BlockManager: BlockManager stopped
17/03/30 20:38:17 INFO storage.BlockManagerMaster: BlockManagerMaster stopped
17/03/30 20:38:17 WARN metrics.MetricsSystem: Stopping a MetricsSystem that is not running
17/03/30 20:38:17 INFO scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/03/30 20:38:17 INFO spark.SparkContext: Successfully stopped SparkContext
Exception in thread "main" 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:124)
    at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:64)
    at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:530)
    at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:59)
    at zhouls.bigdata.MyJavaWordCount.main(MyJavaWordCount.java:31)
    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:497)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
17/03/30 20:38:17 INFO remote.RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
17/03/30 20:38:18 INFO util.ShutdownHookManager: Shutdown hook called
17/03/30 20:38:18 INFO remote.RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
17/03/30 20:38:18 INFO util.ShutdownHookManager: Deleting directory /tmp/spark-fdfdb880-f6cf-47eb-8981-1176e657d466
17/03/30 20:38:18 INFO util.ShutdownHookManager: Deleting directory /tmp/spark-fdfdb880-f6cf-47eb-8981-1176e657d466/httpd-f5d25b97-30bd-4f13-b925-d96026063a63
[spark@master spark-1.6.1-bin-hadoop2.6]

解决思路

  第一种解决版本:首先想到是集群中内存资源不足,可以检查下每台机器是否有足够剩余内存( free -g);也可能是其他已经提交的Spark应用占了大部分资源;

  第二种解决办法:如果1>正常,我们可以看看YARN集群是否启动成功。注意“坑”可能就在这里: 即使Slave上的nodemanager进程存在,要注意检查resource manager日志,看看各个node manager是否启动成功,我的问题就出现在这里:进程在,但是日志显示node manager状态为UNHEALTHY,所以YARN集群能识别到的总内存资源为0。。。

  检查了UNHEALTHY的原因,是因为/tmp下一个目录被识别为bad, 因为是临时目录,我把每个node manager的对应目录删掉,然后重启YARN集群,最终问题解决。

Spark通过YARN提交任务不成功(包含YARN cluster和YARN client)的更多相关文章

  1. 【原创】大叔经验分享(19)spark on yarn提交任务之后执行进度总是10%

    spark 2.1.1 系统中希望监控spark on yarn任务的执行进度,但是监控过程发现提交任务之后执行进度总是10%,直到执行成功或者失败,进度会突然变为100%,很神奇, 下面看spark ...

  2. Spark集群之yarn提交作业优化案例

    Spark集群之yarn提交作业优化案例 作者:尹正杰 版权声明:原创作品,谢绝转载!否则将追究法律责任. 一.启动Hadoop集群 1>.自定义批量管理脚本 [yinzhengjie@s101 ...

  3. spark利用yarn提交任务报:YARN application has exited unexpectedly with state UNDEFINED

    spark用yarn提交任务会报ERROR cluster.YarnClientSchedulerBackend: YARN application has exited unexpectedly w ...

  4. spark on yarn提交任务时报ClosedChannelException解决方案

    spark2.1出来了,想玩玩就搭了个原生的apache集群,但在standalone模式下没有任何问题,基于apache hadoop 2.7.3使用spark on yarn一直报这个错.(Jav ...

  5. spark各种模式提交任务介绍

    前言 本文章部分内容翻译自: http://spark.apache.org/docs/latest/submitting-applications.html 应用提交 Spark的bin目录中的sp ...

  6. Kafka:ZK+Kafka+Spark Streaming集群环境搭建(六)针对spark2.2.1以yarn方式启动spark-shell抛出异常:ERROR cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Sending RequestExecutors(0,0,Map(),Set()) to AM was unsuccessful

    Spark以yarn方式运行时抛出异常: [spark@master bin]$ cd /opt/spark--bin-hadoop2./bin [spark@master bin]$ ./spark ...

  7. yarn是什么?为什么会产生yarn,它解决了什么问题?以及yarn的执行流程

       yarn是什么?为什么会产生yarn,它解决了什么问题? 答:yarn是作业调度和集群资源管理的一个框架. 首先对之前的Hadoop 和 MRv1 简单介绍如下: Hadoop 集群可从单一节点 ...

  8. spark跑YARN模式或Client模式提交任务不成功(application state: ACCEPTED)

    不多说,直接上干货! 问题详情 电脑8G,目前搭建3节点的spark集群,采用YARN模式. master分配2G,slave1分配1G,slave2分配1G.(在安装虚拟机时) export SPA ...

  9. spark跑YARN模式或Client模式提交任务不成功(application state: ACCEPTED)(转)

    不多说,直接上干货! 问题详情 电脑8G,目前搭建3节点的spark集群,采用YARN模式. master分配2G,slave1分配1G,slave2分配1G.(在安装虚拟机时) export SPA ...

随机推荐

  1. 一种基于RBAC模型的动态访问控制改进方法

    本发明涉及一种基于RBAC模型的动态访问控制改进方法,属于访问控制领域.对原有RBAC模型进行了权限的改进和约束条件的改进,具体为将权限分为静态权限和动态权限,其中静态权限是非工作流的权限,动态权限是 ...

  2. 洛谷 P3068 [USACO13JAN]派对邀请函Party Invitations

    P3068 [USACO13JAN]派对邀请函Party Invitations 题目描述 Farmer John is throwing a party and wants to invite so ...

  3. error:assign attribute must be unsafeunretained

    今天在使用协议的过程中.偶然发现这样使用 ? 1 2 3 4 5 6 7 8 9 10 @interface AppDelegate (){     id<chatdelegate>  t ...

  4. 高性能网络编程 - select系统调用

         IO复用使得程序可以同一时候监听多个文件描写叙述符,比方client须要同一时候处理用户输入和网络连接,server端须要同一时候处理监听套接字和连接套接字,select系统调用可以使得我们 ...

  5. Exchange2003迁移2010DAG的权限问题

    exchange2010无法删除用户.在2010的控制台中新建一个通讯组.然后将它删除就会报告下面错误. MicrosoftExchange 错误:无法对对象"test"执行&qu ...

  6. BZOJ 1305 二分+网络流

    思路: 建图我根本没有想到啊--. (我是不会告诉你我借鉴了一下题解的思路) 把每个人拆成喜欢的和不喜欢的点 男 喜欢 向 男 不喜欢 连 边权为k的边 如果男喜欢女 那么 男喜欢向 女喜欢 连 1 ...

  7. NET Native

    起因源自于微软在 MSDN 博客上宣布了 .NET Native 的开发者预览版..NET Native 可以将 C# 代码编译成本地机器码.有了它,开发者将不仅能享受 C# 的高生产力,而且能拥有 ...

  8. Linux PuTTY 更改字体

    Linux PuTTY默认的字体比较小看着比较不舒服,Linux PuTTY的字体更改与Windows下的设置有所不同 1.Linux PuTTY默认的字体 ,Font used for ordina ...

  9. [Python] Find available methods and help in REPL

    For example you want to know what methods are available in Python for String, you can do : dir(" ...

  10. PIM-DM协议内核触发机制及协议执行机制记录

    PIM-DM和PIM-SM是组播路由ASM(随意信源组播)中的两种不同模式.相对PIM-SM的组播注冊机制.PIM-DM的扩散机制显得更加粗犷. 一.PIM-DM无需向内核注冊pimreg虚接口. 可 ...