(1)控制台Yarn(Cluster模式)打印的异常日志: client token: N/A         diagnostics: Application application_1584359355781_0002 failed 2 times due to AM Container for appattempt_1584359355781_0002_000002 exited with  exitCode: -1000 due to: File does not exist: hdfs…

spark任务提交到yarn上命令总结 1. 使用spark-submit提交任务 集群模式执行 SparkPi 任务,指定资源使用,指定eventLog目录 spark-submit --class org.apache.spark.examples.SparkPi \ --master yarn \ --conf spark.eventLog.dir=hdfs://dbmtimehadoop/tmp/spark2 \ --deploy-mode cluster \ --driver-memo…

标签(空格分隔): Spark 作业提交 先回顾一下WordCount的过程: sc.textFile("README.rd").flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_+_) 步骤一:val rawFile = sc.textFile("README.rd") texyFile先生成HadoopRDD --> MappedRDD:…

当spark跑在yarn上时 单个executor执行时,数据量过大时会导致executor的memory不足而使得rdd  最后lost,最终导致任务执行失败 其中会抛出如图异常信息 如图中异常所示 对应解决方法可以加上对应的参数调优(这个配置可以在总的处理数据量在几百TB或者1~3PB级别的数据处理时解决executor-memory不足问题) --num-executors=512 --executor-cores=8 --executor-memory=32g --driver-memo…

通过oozie job id可以查看流程详细信息,命令如下: oozie job -info 0012077-180830142722522-oozie-hado-W 流程详细信息如下: Job ID : 0012077-180830142722522-oozie-hado-W --------------------------------------------------------------------------------------------------------------…

Exception 1:当我们将任务提交给Spark Yarn集群时,大多会出现以下异常,如下: 14/08/09 11:45:32 WARN component.AbstractLifeCycle: FAILED SelectChannelConnector@0.0.0.0:4040: java.net.BindException: Address already in use java.net.BindException: Address already in use at sun.nio.…

来源:https://www.cnblogs.com/arachis/p/spark_parameters.html 摘要 1.num-executors 2.executor-memory 3.executor-cores 4.driver-memory 5.spark.default.parallelism 6.spark.storage.memoryFraction 7.spark.shuffle.memoryFraction 8.total-executor-cores 9.资源参数参考…

架构图 yarn-cluster yarn-client 区别 Yarn-cluster spark的driver运行在applicationMaster内,启动流程为: 这张图可能比较直观 Yarn-client Spark client向yarn的RM申请资源容器,得到AM,但是这个AM运行在其他nodemanager,并得到其他executor的运行容器.而spark的driver运行在client中. 总结 Yarn-client有单点故障的问题,当client意外死亡后,spark的d…

kafka-topics.sh --describe --zookeeper xxxxx:2181 --topic testkafka-run-class.sh kafka.tools.GetOffsetShell --topic test --broker-list xxxxxx:9092 --time -1 SPARK_CLASSPATH=$SPARK_CLASSPATH:/data/lib/* mvn dependency:copy-dependencies DEP_JARS=""…

一.作业提交 1.1 spark-submit Spark所有模式均使用spark-submit命令提交作业,其格式如下: ./bin/spark-submit \ --class <main-class> \ # 应用程序主入口类 --master <master-url> \ # 集群的Master Url --deploy-mode <deploy-mode> \ # 部署模式 --conf <key>=<value> \ # 可选配置 .…