yarn | 易学教程

Flink1.6系列之—Flink on yarn流程详解

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本篇我们介绍下，Flink在YARN上运行流程：当开始一个新的Flink yarn 会话时，客户端首先检查所请求的资源（containers和内存）是否可用。如果资源够用，之后，上传一个jar包，包含Flink和HDFS的配置。客户端向yarn resource manager发送请求，申请一个yarn container去启动ApplicationMaster。 yarn resource manager会在nodemanager上分配一个container，去启动ApplicationMaster yarn nodemanager会将配置文件和jar包下载到对应的container中，进行container容器的初始化。初始化完成后，ApplicationMaster构建完成。ApplicationMaster会为TaskManagers生成新的Flink配置文件（使得TaskManagers根据配置文件去连接到JobManager），配置文件会上传到HDFS。 ApplicationMaster开始为该Flink应用的TaskManagers分配containers，这个过程会从HDFS上下载jar和配置文件（此处的配置文件是AM修改过的，包含了JobManager的一些信息，比如说JobManager的地址）一旦上面的步骤完成，Flink已经建立并准备好接受jobs

Is there a way to change the replication factor of RDDs in Spark?

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问题 From what I understand, there are multiple copies of data in RDDs in the cluster, so that in case of failure of a node, the program can recover. However, in cases where chance of failure is negligible, it would be costly memory-wise to have multiple copies of data in the RDDs. So, my question is, is there a parameter in Spark, which can be used to reduce the replication factor of the RDDs? 回答1: First, note Spark does not automatically cache all your RDD s, simply because applications may

CDH5.2: MR, Unable to initialize any output collector

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问题 Cloudera CDH5.2 Quickstart VM Cloudera Manager showing all nodes state = GREEN I've jared on Eclipse a MR job including all relevant cloudera jars in the Build Path: avro-1.7.6-cdh5.2.0.jar, avro-mapred-1.7.6-cdh5.2.0-hadoop2.jar, hadoop-common-2.5.0-cdh5.2.0.jar, hadoop-mapreduce-client-core-2.5.0-cdh5.2.0.jar I've run the following job hadoop jar jproject1.jar avro00.AvroUserPrefCount -libjars ${LIBJARS} avro/00/in avro/00/out I get the following error, is it a Java heap problem, any

Hadoop全分布式配置

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改时间 clock --set --date="02/22/19 10:50" #改时间 clock --hctosys #同步硬件时间 clock --show 展示硬件时间配置主节点名 vi /etc/sysconfig/network 添加： NETWORKING=yes HOSTNAME=master 重启即可永久生效（hostname xxx可以临时修改）配置host ./bin/hostname master 使生效配置ssh免密码登录在root用户下输入ssh-keygen -t rsa 一路回车秘钥生成后在~/.ssh/目录下，有两个文件id_rsa(私钥)和id_rsa.pub（公钥），三个系统都生成好之后，slave1和slave2将公钥传给master，master追加到authorized_keys后，在分发给slave1和slave2 [root@master .ssh]# cat id_rsa_slave1.pub >> authorized_keys [root@master .ssh]# cat id_rsa_slave2.pub >> authorized_keys 将公钥复制到authorized_keys并赋予authorized_keys 600权限（cp id_rsa.pub authorized_keys）或者

Hive无法执行MapReduce任务

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检查HDFS和yarn集群否工作正常，基本都是yarn没启动或者服务挂掉了，实在不行重启hadoop集群即可，保证HDFS和yarn集群的工作正常来源： CSDN 作者： MCY-- 链接： https://blog.csdn.net/qq_39211575/article/details/103840400

spark - java heap space issue - ExecutorLostFailure - container exited with status 143

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问题 I am reading the string which is of length more than 100k bytes and splitting the columns based on width. I have close to 16K columns which I split from above string based on width. but while writing into parquet i am using below code rdd1=spark.sparkContext.textfile("file1") { var now=0 { val collector= new array[String] (ColLenghth.length) val recordlength=line.length for (k<- 0 to colLength.length -1) { collector(k) = line.substring(now,now+colLength(k)) now =now+colLength(k) } collector

Hadoop 2.2.0 jobtracker is not starting

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问题 It seems I have no jobtracker with Hadoop 2.2.0. JPS does not show it, there is no one listening on port 50030, and there are no logs about the jobtracker inside the logs folder. Is this because of YARN? How can I configure and start the job tracker? 回答1: If you are using YARN framework, there is no jobtracker in it. Its functionality is split and replaced by ResourceManager and ApplicationMaste r. Here is expected jps prinout while running YARN $jps 18509 Jps 17107 NameNode 17170 DataNode

Why there is a mapreduce.jobtracker.address configuration on YARN?

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问题 YARN is the Hadoop second generation that not use the jobtracker daemon anymore, and substitute it with resource manager. But why, on mapred-site.xml hadoop 2 there is an mapreduce.jobtracker.address property? 回答1: You are correct. In YARN, jobtracker no longer exists. So as part of client configuration you don't have to to specify the property mapreduce.jobtracker.address . In YARN, you should specify the property mapreduce.framework.name to yarn in the config file. Instead of setting up

How to run 2 EMR Spark Step Concurrently?

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问题 I am trying to have 2 steps run concurrent in EMR. However I always get the first step running and the second pending. Part of my Yarn configuration is as follows: { "Classification": "capacity-scheduler", "Properties": { "yarn.scheduler.capacity.resource-calculator": "org.apache.hadoop.yarn.util.resource.DominantResourceCalculator", "yarn.scheduler.capacity.maximum-am-resource-percent": "0.5" } } When I run on my local Mac I am able to run the 2 application on Yarn with similar configuration

yarn的安装与使用

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yarn的安装: 在node.js用npm下载： npm install -g yarn 查看版本： yarn --version Yarn 淘宝源安装，分别复制粘贴以下代码行到黑窗口运行即可 yarn config set registry https://registry.npm.taobao.org -g yarn config set sass_binary_site http://cdn.npm.taobao.org/dist/node-sass -g yarn的使用: 在项目上就一个命令，所有的包自动下载 yarn 安装指定的包： yarn add packageName 删除已安装的包： yarn remove packageName 运行项目：(2种方式) yarn start yarn run 项目打包：回生成一个文件夹 yarn build 来源： CSDN 作者：踩前端的坑链接： https://blog.csdn.net/Imagirl1/article/details/103887623