hadoop prerequisites

Now that namenode and datanode1 are available, add the node datanode2 first step: Modify the Host Name of the node to be added hadoop @ datanode1 :~ $ Vimetchostnamedatanode2 Step 2: Modify the host file hadoop @ datanode1 :~ $ Vimetchosts192.168.8.4datanode2127.0.0.1localhost127.0 Now that namenode and datanode1 are available, add the node datanode2 first step: Modify the Host Name of the node to be added

Hadoop (13), hadoop 1. mahout introduction: Mahout is a powerful data mining tool and a collection of distributed machine learning algorithms, including the implementation, classification, and clustering of distributed collaborative filtering called Taste. The biggest advantage of Mahout is its hadoop-based implementation, which converts many previous algorithms

(1) First create Java projectSelect File->new->java Project on the Eclipse menu.and is named UploadFile.(2) Add the necessary Hadoop jar packagesRight-click the JRE System Library and select Configure build path under Build path.Then select Add External Jars. Add the jar package and all the jar packages under Lib to your extracted Hadoop source directory.All jar packages in the Lib directory.(3) Join the Up

This article has agreed:Dn:datanodeTt:tasktrackerNn:namenodeSnn:secondry NameNodeJt:jobtrackerThis article describes the communication protocol between the Hadoop nodes and the client.Hadoop communication is based on RPC, a detailed introduction to RPC you can refer to "Hadoop RPC mechanism introduce Avro into the Hadoop RPC mechanism"Communication between nodes

This article will go on to the wordcount example in the previous article to abstract the simplest process and explore how the System Scheduling works in the mapreduce operation process. Scenario 1: Separate data from operations Wordcount is the hadoop helloworld program. It counts the number of times each word appears. The process is as follows: Now I will describe this process in text. 1. The client submits a job and sends mapreduce programs and dat

) Configure masters and slaves Add the corresponding machine IP address to the corresponding configuration file. 3.2.3 configuration of nutch $ Nutch_home/conf directory (1) nutch-site.xml documents (2)regex-urlfilter.txt Add the URL to be retrieved +^http://([a-z0-9]*\.)*nutch.apache.org/ (3) Put the modified file in the maid/runtime/deploy/nutch-*. Job. 3.3 start running 3.3.1 start hadoop 1. format the namenode Node Bin/

Inkfish original, do not reprint commercial nature, reproduced please indicate the source (http://blog.csdn.net/inkfish). Hadoop is an open source cloud computing platform project under the Apache Foundation. Currently the latest version is Hadoop 0.20.1. The following is a blueprint for Hadoop 0.20.1, which describes how to install

Currently in Hadoop used more than lzo,gzip,snappy,bzip2 these 4 kinds of compression format, the author based on practical experience to introduce the advantages and disadvantages of these 4 compression formats and application scenarios, so that we in practice according to the actual situation to choose different compression format. 1 gzip compression Advantages: The compression ratio is high, and the compression/decompression speed is relatively fas

to facilitate the MapReduce direct access to the relational database (mysql,oracle). Hadoop offers two classes of Dbinputformat and Dboutputformat. Through the Dbinputformat class, the database table data is read into HDFs, and the result set generated by MapReduce is imported into the database table according to the Dboutputformat class.error when executing mapreduce: java.io.IOException:com.mysql.jdbc.Driver, usually because the program cannot find

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

Hadoop FS: Use the widest range of surfaces to manipulate any file system.Hadoop DFS and HDFs DFS: can only operate on HDFs file system-related (including operations with local FS), which is already deprecated, typically using the latter.The following reference is from StackOverflowFollowing is the three commands which appears same but has minute differences Hadoop fs {args}

The debug run in Eclipse and "run on Hadoop" are only run on a single machine by default, because in order to let the program distributed running in the cluster also undergoes the process of uploading the class file, distributing it to each node, etc.A simple "run on Hadoop" just launches the local Hadoop class library to run your program,No job information is vi

The compilation process is very long, the mistakes are endless, need patience and patience!! 1. Preparation of the environment and software Operating system: Centos6.4 64-bit JDK:JDK-7U80-LINUX-X64.RPM, do not use 1.8 Maven:apache-maven-3.3.3-bin.tar.gz protobuf:protobuf-2.5.0.tar.gz Note: Google's products, preferably in advance Baidu prepared this document Hadoop src:hadoop-2.5

Hadoop exception and handling Summary-01 (pony-original), hadoop-01 Test environment: Local: MyEclipse Cluster: Vmware 11 + 6 Centos 6.5 Hadoop version: 2.4.0 (configured as automatic HA) Test Background: After four normal tests of the MapReduce Program (hereinafter referred to as MapReduce), a new MR program is executed, and the console information of MyEclipse

Hadoop learning 2: hadoop LearningAfter building a pseudo-distributed system:Introduction to pseudo distributed installation: http://www.powerxing.com/install-hadoop/ Exercise 1 compile a Java program to implement the followingFunction: 1. In HDFSUpload files 2. From HDFSDownload filesTo local 3.Show file directory 4.Move files 5.Create folder 6.Remove folder