Apache Hadoop

Apache Hadoop is a framework for running applications on large cluster built of commodity hardware. The Hadoop framework transparently provides applications both reliability and data motion. Hadoop implements a computational paradigm named Map/Reduce, where the application is divided into many small fragments of work, each of which may be executed or re-executed on any node in the cluster. In addition, it provides a distributed file system (HDFS) that stores data on the compute nodes, providing very high aggregate bandwidth across the cluster. Both MapReduce and the Hadoop Distributed File System are designed so that node failures are automatically handled by the framework.

General Information

• Official Apache Hadoop Website: download, bug-tracking, mailing-lists, etc.
• Overview of Apache Hadoop
• FAQ Frequently Asked Questions.
• What Hadoop is not
• Distributions and Commercial Support for Hadoop (RPMs, Debs, AMIs, etc)
• Presentations, books, articles and papers about Hadoop
• PoweredBy, a growing list of sites and applications powered by Apache Hadoop
• Support
  • Getting help from the hadoop community.
  • People and companies for hire.
• Hadoop Community Events and Conferences
• HadoopUserGroups (HUGs)

Related-Projects

• HBase, a Bigtable-like structured storage system for Hadoop HDFS
• Apache Pig is a high-level data-flow language and execution framework for parallel computation. It is built on top of Hadoop Core.
• Hive a data warehouse infrastructure which allows sql-like adhoc querying of data (in any format) stored in Hadoop
• ZooKeeper is a high-performance coordination service for distributed applications.
• Hama, a Google's Pregel-like distributed computing framework based on BSP (Bulk Synchronous Parallel) computing techniques for massive scientific computations.
• Mahout, scalable Machine Learning algorithms using Hadoop
• Hadoop Compatible FileSystems (HCFS)
• Apache Gora, open source framework provides an in-memory data model and persistence for big data. Gora supports persisting to column stores, key value stores, document stores and RDBMSs, and analyzing the data with extensive Apache Hadoop MapReduce support.

User Documentation

• Available Java Runtime Environments for Hadoop
• ImportantConcepts
• GettingStartedWithHadoop (lots of details and explanation)
• QuickStart (for those who just want it to work now)
• Command Line Options for the Hadoop shell scripts.
• Hadoop Code Overview
• Troubleshooting What do when things go wrong

Setting up a Hadoop Cluster

• Starting a Single-Node Hadoop Cluster
• HowToConfigure Hadoop software
• WebApps for monitoring your system
• Configure NameNode High-Availability
• How to get metrics into ganglia
• Tips for managing a large cluster
• Disk Setup: some suggestions
• Topology Scripts / Rack Awareness
• Build and Install Hadoop 2.2 or newer on Windows
• Virtual Clusters including Amazon AWS
  • Virtual Hadoop - the theory
  • How to set up a Virtual Cluster
  • Running Hadoop on AmazonEC2
  • Running Hadoop with AmazonS3
    
    

Tutorials

• Running Hadoop On Ubuntu Linux (Single-Node_Cluster) Tutorial by Michael Noll on installing, configuring and running Hadoop on a single Ubuntu Linux machine.
• Running Hadoop On Ubuntu Linux (Multi-Node Cluster) Tutorial by Michael Noll on how to setup a multi-node Hadoop cluster.
• Cloudera basic training
• Hadoop Windows/Eclipse Tutorial: How to develop Hadoop with Eclipse on Windows.
• Yahoo! Hadoop Tutorial: Hadoop setup, HDFS, and MapReduce
• Running Hadoop on Mac OSX (Multi-Node Cluster) Tutorial on how to setup a multi-node Hadoop cluster on Macintosh OSX (Lion).
  
  

MapReduce

The MapReduce algorithm is the foundational algorithm of Hadoop, and is critical to understand.

• HadoopMapReduce
• HadoopMapRedClasses
• HowManyMapsAndReduces
• TaskExecutionEnvironment
• HowToDebugMapReducePrograms
• Examples
  • WordCount
  • Python Word Count
  • C/C++ Word Count
  • Grep
  • Sort
  • RandomWriter
  • How to read from and write to HDFS
• Benchmarks
  • Hardware benchmarks
  • Data processing benchmarks
    
    

Contributed parts of the Hadoop codebase

These are independent modules that are in the Hadoop codebase but not tightly integrated with the main project -yet.

• HadoopStreaming (Useful for using Hadoop with other programming languages)
• DistributedLucene, a Proposal for a distributed Lucene index in Hadoop
• MountableHDFS, Fuse-DFS & other Tools to mount HDFS as a standard filesystem on Linux (and some other Unix OSs)
• HDFS-APIs in Perl, Python, PHP and other languages.
• Chukwa a data collection, storage, and analysis framework
• The Apache Hadoop Plugin for Eclipse (An Eclipse plug-in that simplifies the creation and deployment of MapReduce programs with an HDFS Administrative feature)
• HDFS-RAID Erasure Coding in HDFS

Developer Documentation

• Roadmap, listing release plans.
• HowToContribute
• HowToUseInjectionFramework
• HowToUseSystemTestFramework
• HowToSetupYourDevelopmentEnvironment
• HowToUseConcurrencyAnalysisTools
• GithubIntegration
• HowToUseJCarder
• HowToCodeReview
• Jira usage guidelines
• HowToCommit
• HowToRelease
• HudsonBuildServer
• HowToSetupUbuntuBuildMachine
• DevelopmentHints
• ProjectSuggestions
• Building/Testing under IntelliJ IDEA
• Git And Hadoop
• ProjectSplit

Related Resources

• Nutch Hadoop Tutorial (Useful for understanding Hadoop in an application context)
• IBM MapReduce Tools for Eclipse - Out of date. Use the Eclipse Plugin in the MapReduce/Contrib instead
• Hadoop IRC channel is #hadoop at irc.freenode.net.
• Using Spring and Hadoop (Discussion of possibilities to use Hadoop and Dependency Injection with Spring)
• Univa Grid Engine Integration A blog post about the integration of Hadoop with the Grid Engine successor Univa Grid Engine
• Hadoop Grid Engine Integration Open Grid Scheduler/Grid Engine Hadoop integration setup instructions.
• Hadoop Tutorial Series Learning progressively important core Hadoop concepts with hands-on experiments using the Cloudera Virtual Machine
• Pydoop A Python MapReduce and HDFS API for Hadoop (tutorial).
• Dumbo Dumbo is a project that allows you to easily write and run Hadoop programs in Python.
• Hadoop distributed file system New Hadoop Connector Enables Ultra-Fast Transfer of Data between Hadoop and Aster Data's MPP Data Warehouse.
• Hadoop + CUDA
• Hadoop on ARM cluster A study that compares Hadoop MapReduce applications' energy consumption and performance between ARM cluster and general X86_64 cluster
• HDFS Architecture Documentation An overview of the HDFS architecture, intended for contributors.

CategoryHomepage