hadoop configuration example

First, compile the Hadoop pluginFirst you need to compile the Hadoop plugin: Hadoop-eclipse-plugin-2.6.0.jar Before you can install it. Third-party compilation tutorial: Https://github.com/winghc/hadoop2x-eclipse-pluginIi. placing plugins and restarting eclipsePut the compiled plugin Hadoop-eclipse-plugin-2.6.0.jar int

Turn from: http://www.cyblogs.com/My own blog ~ first of all, we need 3 machines, and here I created 3 VMs in VMware to ensure my hadoop is fully distributed with the most basic configuration. I chose the CentOS here because the Redhat series, which is popular in the enterprise comparison. After the installation, the final environmental information: IP Address H1H2h3 Here is a small question to see, is to

I. Hadoop-eclipse-plugin-2.7.3.jar plugin download Click to download the plugin into the installation directory of Eclipse DropinsThird, the configuration on eclipse3.1 Opening Window-->persperctive-->other3.2 Select Map\/reduce, click OK3.3 Click the image icon to add a cluster3.4 The Hadoop cluster configuration para

Hadoop User Experience (HUE) Installation and HUE configuration Hadoop HUE: Hadoop User Experience. Hue is a graphical User interface for operating and developing Hadoop applications. The Hue program is integrated into a desktop-like environment and released as a web program

WordCount code in Hadoop-loading Hadoop configuration files directlyIn MyEclipse, write the WordCount code directly, calling the Core-site.xml,hdfs-site.xml,mapred-site.xml configuration file directly in the codePackagecom.apache.hadoop.function;importjava.io.ioexception;importjava.util.iterator;import java.util.String

1. Example of running wordcount After creating a new directory on hadoop, use putprogram to input input1.txtand input2.txt files in linuxto/tmp/input/In the hadoop file system. Hadoopfs-mkdir/tmp/Input Hadoopfs-mkdir/tmp/Output Hadoopfs-put input1.txt/tmp/input/ Hadoop FS-put input2.txt/tmp/input/ Execute the wordcoun

Configure HadoopJDK and SSH have been configured as prerequisites(How to configure jdk:http://www.cnblogs.com/xxx0624/p/4164744.html)(How to configure ssh:http://www.cnblogs.com/xxx0624/p/4165252.html)1. Add a Hadoop usersudo addgroup hadoop sudo adduser--ingroup hadoop Hadoop2. Download the Hadoop file (

/id_rsa.pub >> ~/.ssh/authorized_keyschmod ~/.ssh/authorized_keysSu RootVim/etc/ssh/sshd_config Service sshd RestartTo test the success of a local password-free connection: The id_rsa.pub is then distributed to the SLAVE1 server:SCP ~/.ssh/id_rsa.pub hadoop@slave1:~/On the SLAVE1 host, under the Hadoop User:Su Hadoopmkdir ~/.ssh (if not, you should create a new. SSH folder)chmod ~/.sshCat ~/.ssh/id_rsa.pub

directory and set a link to the version of hadoop we want to use, this reduces the maintenance of the configuration file. In the following sections, you will experience the benefits of such separation and links. SSH installation and Setup After hadoop is started, namenode starts and stops various daemon on each node through SSH (Secure Shell, therefore, you do

/datavalue> Property>Configuration>Run Hadoop after the configuration is complete.Four. Run hadoop4.1 to initialize the HDFS systemExecute the command in the hadop2.7.1 directory:Bin/hdfs Namenode-formatThe following results show that the initialization was successful.4.2 OpenNameNodeAndDataNodeDaemon processExecute the command in the hadop2.7.1 directory:sbin/st

Record the hadoop configuration and description. New configuration items are added and occasionally updated. By configuration file name Take hadoop 1. x configuration as an Example Core

We have introduced the installation and simple configuration of hadoop in Linux, mainly in standalone mode. The so-called standalone Mode means that no daemon process is required ), all programs are executed on a single JVM. Because it is easier to test and debug mapreduce programs in standalone mode, this mode is suitable for use in the development phase. Here we mainly record the process of configuring th

. mapreduce package (and sub-package. Earlier versions of APIs are stored in org. Apache. hadoop. mapred.3. The new API uses context object extensively and allows user code to communicate with the mapreduce system. For example, mapcontext basically acts as outputcollector and reporter of jobconf.4. The new API supports both "push" and "pull" iterations. In the two old and new APIs, key/value record pairs ar