1. Introduction to HadoopHadoop is an open-source distributed computing platform under the Apache Software Foundation, which provides users with a transparent distributed architecture of the underlying details of the system, and through Hadoop, it is possible to organize a large number of inexpensive machine computing resources to solve the problem of massive data processing that cannot be solved by a single machine.
The Hadoop version of this blog is Hadoop 0.20.2.Installing Hadoop-0.20.2-eclipse-plugin.jar
To download the Hadoop-0.20.2-eclipse-plugin.jar file and add it to the Eclipse plug-in library, add a method that is simple: Locate the plugins directory under the Eclipse installation directory, copy directly to this
Prerequisites and design objectivesHardware Error
Hardware errors are normal rather than abnormal. HDFS may consist of hundreds of thousands of servers. Each server stores part of the data in the file system. The reality is that the number of components that constitute the system is huge, and any component may fail, which means that some HDFS components are always not working. Therefore, error detection and fast and automatic recovery are the core arc
The previous installation process to be supplemented, after the installation complete Hadoop installation, began to execute the relevant commands, let Hadoop run up Use the command to start all services: [Email protected]:/usr/local/gz/hadoop-2.4. 1$./sbin/start-all. SHOf course there will be a lot of startup files under directory
Course Outline and Content introduction:About 35 minutes per lesson, no less than 40 lecturesThe first chapter (11 speak)• Distributed and traditional stand-alone mode· Hadoop background and how it works· Analysis of the working principle of MapReduce• Analysis of the second generation Mr--yarn principle· Cloudera Manager 4.1.2 Installation· Cloudera Hadoop 4.1.2 Installation· CM under the cluster managemen
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}
Prepare hadoop streaming
Hadoop streaming allows you to create and run MAP/reduce jobs with any executable or script as the Mapper and/or the CER Cer.
1. Download hadoop streaming fit for your hadoop version
For hadoop2.4.0, you can visit the following website and download the JAR file:
Http://mvnrepository.com/art
DISTCP Parallel replication
The same version of the Hadoop cluster
Hadoop distcp Hdfs//namenode1/foo Hdfs//namenode2/bar
Different versions of the Hadoop cluster (HDFs version), executed on the writing side
Hadoop distcp Hftp://namenode1:50070/foo Hdfs://namenode2/bar
Archive of
Because HDFs is different from a common file system, Hadoop provides a powerful filesystem API to manipulate HDFs.
The core classes are Fsdatainputstream and Fsdataoutputstream.
Read operation:
We use Fsdatainputstream to read the specified file in HDFs (the first experiment), and we also demonstrate the ability to locate the file location of the class, and then start reading the file from the specified location (the second experiment).
The code i
Detailed procedures for starting the HDFS process using start-dfs.sh
The scripts involved are:
Under Bin:
hadoop-config.sh
start-dfs.sh
hadoop-daemons.sh
slaves.sh
hadoop-daemon.sh
Hadoop
Conf under:
hadoop-env.sh
Where both
Preface
The most interesting thing about hadoop is hadoop Job Scheduling. Before introducing how to set up hadoop, it is necessary to have a deep understanding of hadoop job scheduling. We may not be able to use hadoop, but if we understand the Distributed Scheduling Princip
Hadoop distributed platform optimization, hadoop
Hadoop performance tuning is not only its own tuning, but also the underlying hardware and operating system. Next we will introduce them one by one:
1. underlying hardware
Hadoop adopts the master/slave architecture. The master (resourcemanager or namenode) needs to mai
OneEclipse Import Hadoop Source projectBasic steps:1) Create a new Java project "hadoop-1.2.1" in Eclipse2) Copy the Core,hdfs,mapred,tools,example four directory under the directory src of the Hadoop compression package to the SRC directory of the new project above3) Right click to select Build path, modify Java Build path "source", delete src, add src/core,src/
In Hadoop, data processing is resolved through the MapReduce job. Jobs consist of basic configuration information, such as the path of input files and output folders, which perform a series of tasks by the MapReduce layer of Hadoop. These tasks are responsible for first performing the map and reduce functions to convert the input data to the output results.
To illustrate how MapReduce works, consider a simp
Ubuntu System (I use the version number is 140.4)The Ubuntu system is a desktop-based Linux operating system, and Ubuntu is built on the Debian distribution and GNOME desktop environments. The goal of Ubuntu is to provide an up-to-date, yet fairly stable, operating system that is primarily built with free software for the general user, free of charge and with community and professional support.As a Hadoop big data development test environment, it is r
A virtual machine was started on Shanda cloud. The default user is root. An error occurred while running hadoop:
[Error description]
Root @ snda:/data/soft/hadoop-0.20.203.0 # bin/hadoop FS-put conf Input11/08/03 09:58:33 warn HDFS. dfsclient: datastreamer exception: Org. apache. hadoop. IPC. remoteException: Java. io.
Hadoop provides mapreduce with an API that allows you to write map and reduce functions in languages other than Java: hadoop streaming uses standard streamams) as an interface for data transmission between hadoop and applications. Therefore, you can write the map and reduce functions in any language, as long as it can read data from the standard input stream (std
Apache Hadoop and the Hadoop EcosystemHadoop is a distributed system infrastructure developed by the Apache Foundation .The user is able to understand the distributed underlying details. Develop distributed programs. Take advantage of the power of the cluster for fast operations and storage.Hadoop implements a distributed filesystem (Hadoop distributedFile system
Whether you are adding machines and removing machines in a Hadoop cluster, there is no downtime and the entire service is uninterrupted.
Before this operation, the cluster of Hadoop is as follows:
The machine condition for HDFs is as follows:
The machine condition of Mr is as follows:
Adding Machines
In the master machine of the cluster, modify the $hadoop_home/conf/slaves file to add the hostname of the n
Build a Hadoop development environment for Fedora 20
1. configuration information:
Operating System: fedora 20X86
Eclipse version: eclipse-jee-helios-SR2-linux-gtk.tar.gz (preferably use Galileo or Helios, otherwise there may be compatibility issues)
Hadoop version: hadoop-1.1.2.tar.gz
Ant: apache-ant-1.9.3-bin.tar.gz
2. Compile the
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