hadoop sample projects

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CentOS7 installation configuration Hadoop 2.8.x, JDK installation, password-free login, Hadoop Java sample program run

Protoc (requires compiling the specified compiled path./configure--prefix=/usr/app/protoc)Config/etc/profileMvn-v OKProtoc--version OK    SVN download Source Compile HadoopMVN Package-dskiptests-pdist,native,docs-dtar (-dtar comes with generating a. Tar installation package)SVN checkout http://svn.apache.org/repos/asf/hadoop/common/trunk/(Hadoop trunk or/common/tags/x.x.x for oldVersionThe compiled storage

Build Hadoop projects with Maven

; - exclusion> About Artifactid>Hadoop-commonArtifactid> $ groupId>Org.apache.hadoopgroupId> - exclusion> - Exclusions> - Dependency> A Dependency> + groupId>Jdk.toolsgroupId> the Artifactid>Jdk.toolsArtifactid> - version>1.7version> $ Scope>SystemScope> the Systempath>${java_home}/lib/tools.jarSystempath> the Dependency> the Dependenc

Eclipse puts Hadoop projects in the cluster

1, add the configuration file to the project source directory (SRC) mapreduce.framework.name yarn Read the contents of the configuration file so that the project knows to submit to the cluster to run2, package the project into the Project source directory (SRC) 3, add a sentence in Java code Configuration conf = new Configuration(); conf.set("mapreduce.job.jar", "wc.jar"); Note: These are intended to allow the cluste

Hadoop 2.8.x Distributed Storage HDFs basic features, Java sample connection HDFs

requireHdfs-site.xml configuration (multiple Namenode)Formatting multiple NamenodeHDFs Namenode-format[-clusterid HDFs Namenode-format-clusterid 2.x supports multiple namenode to distribute load and achieve performance assuranceNamespace Management-Client Side Mount TableAdd a new Datanode nodeInstall Hadoop on new datanode and copy config from NamenodeUpdate Masters and slaves file on all Namenode and DatanodeConfig no pwd accessStart Datanode and N

Learning the learning notes series of OpenCV (2) source code compilation and sample projects, opencv learning notes

Learning the learning notes series of OpenCV (2) source code compilation and sample projects, opencv learning notesDownload and install CMake3.0.1 To compile the source code of OpenCV2.4.9 by yourself, you must first download the compilation tool. CMake is the most widely used compilation tool. The following is an introduction to CMake: CMake is a cross-platform installation (Compilation) tool. You can use

[Hadoop Series] Pig Installation and Simple Demo sample

Inkfish original, do not reprint the commercial nature, reproduced please indicate the source (http://blog.csdn.net/inkfish). (Source: http://blog.csdn.net/inkfish)Pig is a project that Yahoo! has donated to Apache, and is currently in the Apache Incubator (incubator) stage, with the version number v0.5.0. Pig is a Hadoop-based, large-scale data analysis platform that provides the sql-like language called Pig Latin, which translates the data analysis

Hadoop sample Program WordCount detailed and examples

exampleclass), jobconf (Configuration conf), etc. */ jobconf conf = new jobconf (wordcount.class); Conf.setjobname ("WordCount"); Set a user-defined job name Conf.setoutputkeyclass (Text.class); Set the key class for the job's output data Conf.setoutputvalueclass (Intwritable.class); Set the value class for the job output Conf.setmapperclass (Map.class); Set the Mapper class for the job Conf.setcombinerclass (Reduce.class); Set the Combiner class for the job Conf.setreducerclass

Reproduced Hadoop Sample Program WordCount detailed

* Construction Method: jobconf (), jobconf (Class exampleclass), jobconf (Configuration conf), etc. - */ the jobconf conf = new jobconf (wordcount.class); the conf.setjobname ("WordCount"); Set a user-defined job name the 94 Conf.setoutputkeyclass (Text.class); Set the key class for the job's output data the Conf.setoutputvalueclass (Intwritable.class); Set the value class for the job output the the Conf.setmapperclass (Map.class); Set the Mapper class for the job98 Conf.setcombinercl

Eclipse Configuration Execute Hadoop 2.7 Program sample steps

records=131Reduce Input groups=131Reduce Shuffle bytes=1836Reduce Input records=131Reduce Output records=131For:warn-unable to load Native-hadoop library for your platform ... using Builtin-java classes where applicable this warning is fine, performed at Linu X will not be reported.8.last. Attempts to split the wordcount into subclasses. Try to move the mapper out, because sometimes multiple classes will prompt for an error:Delete the output folder a

Apache Hadoop Zookeeper Sample __java

Article from: https://examples.javacodegeeks.com/enterprise-java/apache-hadoop/apache-hadoop-zookeeper-example/ = = = Article using Google Translator=====google translation: suggest first read the original. In this example, we'll explore the Apache zookeeper, starting with the introduction and then the steps to set up the zookeeper and make it run. 1. Introduce The Apache zookeeper is a building block for d

Hadoop Auxiliary Sorting sample One

specify the data transfer order and cache the pending records in memory, you should try to avoid this situation, because the number of records in any of these groups can be very large, far beyond the reducer available */public class Textpair Implements writablecomparable Import Org.apache.hadoop.io.longwritable;import Org.apache.hadoop.io.text;import Org.apache.hadoop.mapreduce.mapper;import java.io.ioexception;/** * Flag Station recorded Mapper */public class Joinstationmapper Extends mapp

Hadoop Auxiliary Sorting sample Two

Org.apache.hadoop.fs.path;import Org.apache.hadoop.io.intwritable;import org.apache.hadoop.io.LongWritable; Import Org.apache.hadoop.io.nullwritable;import Org.apache.hadoop.io.text;import Org.apache.hadoop.io.writablecomparable;import Org.apache.hadoop.io.writablecomparator;import Org.apache.hadoop.io.writableutils;import Org.apache.hadoop.mapreduce.job;import Org.apache.hadoop.mapreduce.mapper;import Org.apache.hadoop.mapreduce.partitioner;import Org.apache.hadoop.mapreduce.reducer;import Org

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