<rt id="bn8ez"></rt>
<label id="bn8ez"></label>

  • <span id="bn8ez"></span>

    <label id="bn8ez"><meter id="bn8ez"></meter></label>

    posts - 495,comments - 227,trackbacks - 0
    http://www.cnblogs.com/luogankun/p/4191796.html

    今天在測試spark-sql運行在yarn上的過程中,無意間從日志中發現了一個問題:

    spark-sql --master yarn
    復制代碼
    14/12/29 15:23:17 INFO Client: Requesting a new application from cluster with 1 NodeManagers 14/12/29 15:23:17 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container) 14/12/29 15:23:17 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead 14/12/29 15:23:17 INFO Client: Setting up container launch context for our AM 14/12/29 15:23:17 INFO Client: Preparing resources for our AM container 14/12/29 15:23:17 INFO Client: Uploading resource file:/home/spark/software/source/compile/deploy_spark/assembly/target/scala-2.10/spark-assembly-1.3.0-SNAPSHOT-hadoop2.3.0-cdh5.0.0.jar -> hdfs://hadoop000:8020/user/spark/.sparkStaging/application_1416381870014_0093/spark-assembly-1.3.0-SNAPSHOT-hadoop2.3.0-cdh5.0.0.jar 14/12/29 15:23:18 INFO Client: Setting up the launch environment for our AM container
    復制代碼

    再開啟一個spark-sql命令行,從日志中再次發現:

    復制代碼
    14/12/29 15:24:03 INFO Client: Requesting a new application from cluster with 1 NodeManagers 14/12/29 15:24:03 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container) 14/12/29 15:24:03 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead 14/12/29 15:24:03 INFO Client: Setting up container launch context for our AM 14/12/29 15:24:03 INFO Client: Preparing resources for our AM container 14/12/29 15:24:03 INFO Client: Uploading resource file:/home/spark/software/source/compile/deploy_spark/assembly/target/scala-2.10/spark-assembly-1.3.0-SNAPSHOT-hadoop2.3.0-cdh5.0.0.jar -> hdfs://hadoop000:8020/user/spark/.sparkStaging/application_1416381870014_0094/spark-assembly-1.3.0-SNAPSHOT-hadoop2.3.0-cdh5.0.0.jar 14/12/29 15:24:05 INFO Client: Setting up the launch environment for our AM container
    復制代碼

    然后查看HDFS上的文件:

    hadoop fs -ls hdfs://hadoop000:8020/user/spark/.sparkStaging/
    drwx------   - spark supergroup          0 2014-12-29 15:23 hdfs://hadoop000:8020/user/spark/.sparkStaging/application_1416381870014_0093 drwx------   - spark supergroup          0 2014-12-29 15:24 hdfs://hadoop000:8020/user/spark/.sparkStaging/application_1416381870014_0094

    每個Application都會上傳一個spark-assembly-x.x.x-SNAPSHOT-hadoopx.x.x-cdhx.x.x.jar的jar包,影響HDFS的性能以及占用HDFS的空間。

     

    在Spark文檔(http://spark.apache.org/docs/latest/running-on-yarn.html)中發現spark.yarn.jar屬性,將spark-assembly-xxxxx.jar存放在hdfs://hadoop000:8020/spark_lib/下

    在spark-defaults.conf添加屬性配置:

    spark.yarn.jar hdfs://hadoop000:8020/spark_lib/spark-assembly-1.3.0-SNAPSHOT-hadoop2.3.0-cdh5.0.0.jar

    再次啟動spark-sql --master yarn觀察日志:

    復制代碼
    14/12/29 15:39:02 INFO Client: Requesting a new application from cluster with 1 NodeManagers 14/12/29 15:39:02 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container) 14/12/29 15:39:02 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead 14/12/29 15:39:02 INFO Client: Setting up container launch context for our AM 14/12/29 15:39:02 INFO Client: Preparing resources for our AM container 14/12/29 15:39:02 INFO Client: Source and destination file systems are the same. Not copying hdfs://hadoop000:8020/spark_lib/spark-assembly-1.3.0-SNAPSHOT-hadoop2.3.0-cdh5.0.0.jar 14/12/29 15:39:02 INFO Client: Setting up the launch environment for our AM container
    復制代碼

    觀察HDFS上文件

    hadoop fs -ls hdfs://hadoop000:8020/user/spark/.sparkStaging/application_1416381870014_0097

    該Application對應的目錄下沒有spark-assembly-xxxxx.jar了,從而節省assembly包上傳的過程以及HDFS空間占用。

     

    我在測試過程中遇到了類似如下的錯誤:

    Application application_xxxxxxxxx_yyyy failed 2 times due to AM Container for application_xxxxxxxxx_yyyy 

    exited with exitCode: -1000 due to: java.io.FileNotFoundException: File /tmp/hadoop-spark/nm-local-dir/filecache does not exist

    在/tmp/hadoop-spark/nm-local-dir路徑下創建filecache文件夾即可解決報錯問題。

    posted on 2016-05-26 14:11 SIMONE 閱讀(1078) 評論(0)  編輯  收藏 所屬分類: spark

    只有注冊用戶登錄后才能發表評論。


    網站導航:
     
    主站蜘蛛池模板: 国产精品四虎在线观看免费| 99久久99这里只有免费费精品| 国内自产拍自a免费毛片| 亚洲资源在线视频| 日本人的色道免费网站| 亚洲综合一区二区精品久久| 99re在线免费视频| 中文无码亚洲精品字幕| 色妞WWW精品免费视频| 色婷婷六月亚洲综合香蕉| 四虎影视永久免费观看网址| 国产大陆亚洲精品国产| 亚洲一区二区视频在线观看| 人碰人碰人成人免费视频| 亚洲精品亚洲人成在线观看| 野花香高清视频在线观看免费 | 国产亚洲精久久久久久无码AV| 尤物视频在线免费观看| 亚洲欧洲日产国码无码网站| 一个人免费日韩不卡视频| 亚洲午夜在线一区| 国产成人免费a在线视频色戒| igao激情在线视频免费| 亚洲AV无码久久| 性感美女视频免费网站午夜 | 亚洲熟妇无码av另类vr影视| 免费人妻av无码专区| 三根一起会坏掉的好痛免费三级全黄的视频在线观看 | 亚洲精品GV天堂无码男同| 亚洲AV网站在线观看| 成人A片产无码免费视频在线观看| 亚洲黄色在线视频| 国产jizzjizz免费视频| 久久国产精品成人免费| 亚洲日韩一区二区三区| 亚洲人精品午夜射精日韩| 999国内精品永久免费视频| 污污视频免费观看网站| 91亚洲一区二区在线观看不卡 | 免费无码黄网站在线观看| 国内精品99亚洲免费高清|