MapReduce

Hadoop map reduce example stuck on Running job

由 半城伤御伤魂 提交于 2021-01-05 12:19:21
问题 I am trying to run a mapreduce example in hadoop. I am using version 2.7.2. I tried running bin/hadoop jar libexec/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.2.jar grep input output 'dfs[a-z.]+' and the mapreduce stuck at running job and does not advance any further. it shows How to resolve this? 回答1: I got it guys. It as the space problem. My HDD is 500 GB capacity. The used space should not exceed 90%. In my case there was only 30GB left. I cleaned up some spce by deleting Apps

如何在CDH6.0中启用Kerberos

由 柔情痞子 提交于 2021-01-05 03:00:41
温馨提示：如果使用电脑查看图片不清晰，可以使用手机打开文章单击文中的图片放大查看高清原图。 Fayson的github： https://github.com/fayson/cdhproject 提示：代码块部分可以左右滑动查看噢 1.文档编写目的 在前面的文章中，Fayson介绍了《 如何在Redhat7.4安装CDH6.0 》，这里我们基于这个环境开始安装Kerberos。关于CDH启用Kerberos的文章，前面Fayson也介绍过《 如何在CDH集群启用Kerberos 》、《 如何在Redhat7.3的CDH5.14中启用Kerberos 》、《 如何在Redhat7.4的CDH5.15中启用Kerberos 》和《 如何在CDH6.0.0-beta1中启用Kerberos 》，通过本文，我们也可以来看看CDH6启用Kerberos有哪些不一样的地方。 内容概述： 1.如何安装及配置KDC服务 2.如何通过CDH启用Kerberos 3.如何登录Kerberos并访问Hadoop相关服务 4.总结 测试环境： 1.操作系统：Redhat7.4 2.CDH6.0 3.采用root用户进行操作 2.KDC服务安装及配置 本文档中将KDC服务安装在Cloudera Manager Server所在服务器上（KDC服务可根据自己需要安装在其他服务器） 1.在Cloudera

How to flush Hadoop Distributed Cache?

由 孤街浪徒 提交于 2021-01-04 17:01:47
问题 I have added a set of jars to the Distributed Cache using the DistributedCache.addFileToClassPath(Path file, Configuration conf) method to make the dependencies available to a map reduce job across the cluster. Now I would like to remove all those jars from the cache to start clean and be sure I have the right jar versions there. I commented out the code that adds the files to the cache and also removed them from where I had copied them in hdfs. The problem is the jars still appear to be in

How to flush Hadoop Distributed Cache?

由 浪子不回头ぞ 提交于 2021-01-04 16:58:32
问题 I have added a set of jars to the Distributed Cache using the DistributedCache.addFileToClassPath(Path file, Configuration conf) method to make the dependencies available to a map reduce job across the cluster. Now I would like to remove all those jars from the cache to start clean and be sure I have the right jar versions there. I commented out the code that adds the files to the cache and also removed them from where I had copied them in hdfs. The problem is the jars still appear to be in

How to flush Hadoop Distributed Cache?

由 拥有回忆 提交于 2021-01-04 16:53:09
问题 I have added a set of jars to the Distributed Cache using the DistributedCache.addFileToClassPath(Path file, Configuration conf) method to make the dependencies available to a map reduce job across the cluster. Now I would like to remove all those jars from the cache to start clean and be sure I have the right jar versions there. I commented out the code that adds the files to the cache and also removed them from where I had copied them in hdfs. The problem is the jars still appear to be in

Hive Window Function ROW_NUMBER without Partition BY Clause on a large (50 GB) dataset is very slow. Is there a better way to optimize?

由 可紊 提交于 2021-01-04 07:25:26
问题 I have a HDFS file with 50 Million records and raw file size is 50 GB. I am trying to load this in a hive table and create unique id for all rows using the below, while loading. I am using Hive 1.1.0-cdh5.16.1. row_number() over(order by event_id, user_id, timestamp) as id While executing I see that in the reduce step, 40 reducers are assigned. Average time for 39 Reducers is about 2 mins whereas the last reducer takes about 25 mins which clearly makes me believe that most of the data is

Hive Window Function ROW_NUMBER without Partition BY Clause on a large (50 GB) dataset is very slow. Is there a better way to optimize?

由 ￡可爱￡侵袭症＋ 提交于 2021-01-04 07:24:06
问题 I have a HDFS file with 50 Million records and raw file size is 50 GB. I am trying to load this in a hive table and create unique id for all rows using the below, while loading. I am using Hive 1.1.0-cdh5.16.1. row_number() over(order by event_id, user_id, timestamp) as id While executing I see that in the reduce step, 40 reducers are assigned. Average time for 39 Reducers is about 2 mins whereas the last reducer takes about 25 mins which clearly makes me believe that most of the data is

Why is in my case For loop faster vs Map, Reduce and List comprehension

由 北城以北 提交于 2020-12-31 04:48:47
问题 I wrote a simple script that test the speed and this is what I found out. Actually for loop was fastest in my case. That really suprised me, check out bellow (was calculating sum of squares). Is that because it holds list in memory or is that intended? Can anyone explain this. from functools import reduce import datetime def time_it(func, numbers, *args): start_t = datetime.datetime.now() for i in range(numbers): func(args[0]) print (datetime.datetime.now()-start_t) def square_sum1(numbers):

How to find optimal number of mappers when running Sqoop import and export?

由 别来无恙 提交于 2020-12-30 07:50:33
问题 I'm using Sqoop version 1.4.2 and Oracle database. When running Sqoop command. For example like this: ./sqoop import \ --fs <name node> \ --jt <job tracker> \ --connect <JDBC string> \ --username <user> --password <password> \ --table <table> --split-by <cool column> \ --target-dir <where> \ --verbose --m 2 We can specify --m - how many parallel tasks do we want Sqoop to run (also they might be accessing Database at same time). Same option is available for ./sqoop export <...> Is there some

mongodb 基础

由 狂风中的少年 提交于 2020-12-29 11:57:44
一、首先安装mongodb 1.下载地址：http://www.mongodb.org/downloads 2.解压缩到自己想要安装的目录，比如d:\mongodb 3.创建文件夹d:\mongodb\data\db、d:\mongodb\data\log，分别用来安装db和日志文件，在log文件夹下创建一个日志文件MongoDB.log，即d:\mongodb\data\log\MongoDB.log 4.运行cmd.exe进入dos命令界面，执行下列命令 　　> cd d:\mongodb\bin 　　> d:\mongodb\bin>mongod -dbpath "d:\mongodb\data\db" 　看到类似的信息，则说明启动成功，默认MongoDB监听的端口是27017，mysql的是3306 5.测试连接 　新开一个cmd窗口，进入mongodb的bin目录，输入mongo或者mongo.exe，出现如下信息说明测试通过，此时我们已经进入了test这个数据库，如何进入其他数据库下面会说。　 　输入exit或者ctrl+C可退出。 6.当mongod.exe被关闭时，mongo.exe 就无法连接到数据库了，因此每次想使用mongodb数据库都要开启mongod.exe程序，所以比较麻烦，此时我们可以将MongoDB安装为windows服务 　还是运行cmd
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