Oozie

Hue是一个轻量级的Web服务器，可让您 直接从浏览器 使用Hadoop 。 Hue只是一个“在任何Hadoop发行版之上的视图”，可以安装在任何机器上。 官方文档在 官方文档 有多种方式（比如 gethue.com的 “下载”部分 ）安装Hue。 下一步就是将Hue配置为指向您的 Hadoop集群 。 默认情况下，Hue假定存在一个本地集群（即只有一台机器）。 为了与真正的集群进行交互，Hue需要知道哪些主机分配了Hadoop服务。 hue.ini在哪里？（配置文件） hue主要配置发生在 hue.ini 文件中。 它列出了很多选项，但本质上什么是HDFS，YARN，Oozie，Hive的地址和端口...根据您安装的ini文件的分布位于： CDH 包: /etc/hue/conf/hue.ini tarball 版本: /usr/share/desktop/conf/hue.ini 开发版本: desktop/conf/pseudo-distributed.ini Cloudera Manager : CM 为你生成所有的hue.ini，所以没有麻烦? /var/run/cloudera-scm-agent/process/`ls -alrt /var/run/cloudera-scm-agent/process | grep HUE | tail -1 | awk ‘

I have a oozie workflow. I am submitting all the hive actions with <name>mapred.job.queue.name</name> <value>${queueName}</value> But for few hive actions, the job launched is not in specified queue; it is invoked in default queue. Please suggest me the cause behind this behavior and solution. Samson Scharfrichter A. Oozie specifics Oozie propagates the "regular" Hadoop properties to a "regular" MapReduce Action. But for other types of Action (Shell, Hive, Java, etc.) where Oozie runs a single Mapper task in YARN, it does not consider that it's a real MapReduce job. Hence it uses a different

I installed oozie 4.1.0 on a Linux machine by following the steps at http://gauravkohli.com/2014/08/26/apache-oozie-installation-on-hadoop-2-4-1/ hadoop version - 2.6.0 maven - 3.0.4 pig - 0.12.0 Cluster Setup - MASTER NODE runnig - Namenode, Resourcemanager ,proxyserver. SLAVE NODE running -Datanode,Nodemanager. When I run single workflow job means it succeeds. But when I try to run more than one Workflow job i.e. both the jobs are in accepted state Inspecting the error log, I drill down the problem as, 014-12-24 21:00:36,758 [JobControl] INFO org.apache.hadoop.ipc.Client - Retrying connect

We have an oozie workflow with a shell action that needs more memory than what a map task is given by Yarn by default. How can we give it more memory? We have tried adding the following configuration to the action: <configuration> <property> <name>mapreduce.map.memory.mb</name> <value>6144</value> <!-- for example --> </property> </configuration> We have both set this as an inline (in the workflow.xml) configuration and as a jobXml. Neither has had any effect. We found the answer: A shell action is executed as an oozie "launcher" map task, and this task does not use the normal configuration

可能是不同版本不同吧，按网友的最终改为： export --connect jdbc:mysql:// 172.16.5.100:3306/dw_test --username testuser --password ****** --table che100kv --export-dir /user/hive/warehouse/che100kv0/000000_0 --input-fields-terminated-by \001 -m 1 报错： Error during export: Export job failed! at org.apache.sqoop.mapreduce.ExportJobBase.runExport(ExportJobBase.java:439) at org.apache.sqoop.manager.SqlManager.exportTable(SqlManager.java:931) at org.apache.sqoop.tool.ExportTool.exportTable(ExportTool.java: <<< Invocation of Sqoop command completed <<< Hadoop Job IDs executed by Sqoop: job_1534936991079_0934 Intercepting