Enterprise-Class Hadoop 2.x introductory series Apache Hadoop 2.x Introduction and version _ Cloud Sail Big Data College

1.1 Hadoop Introduction

Introduction to Hadoop from the Hadoop website: http://hadoop.apache.org/

(1) What is Apache Hadoop?

Theapache Hadoop Project develops open-source software for reliable, scalable, distributed Computing.

Theapache Hadoop Software Library is a framework this allows for the distributedprocessing of large data sets across Clust ERs of computers using simpleprogramming models. It is the designed to scale up from the single servers to thousandsof machines, each offering local computation and storage. Rather than rely onhardware to deliver high-availability, the library itself are designed to detectand handle failures at t He application layer, so delivering a highly-availableservice on top of a cluster of computers, each of the which may be prone Tofailures.

(2) The Project Includesthese modules:

- Hadoop Common: The Common utilities, the other Hadoop modules.

- Hadoop Distributed File System (HDFS): A Distributed File system, Provideshigh-throughput access to APPL Ication data.

- Hadoop YARN: A framework for job scheduling and cluster resource management.

- Hadoop MapReduce: A yarn-based system for parallel processing of large data sets.

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(3) Other hadoop-relatedprojects at Apache include:

Ambari: A web-based tool for provisioning,managing, and monitoring Apache Hadoop clusters which includes support Forhadoop HDFS, Hadoop MapReduce, Hive, Hcatalog, HBase, ZooKeeper, Oozie, Pig Andsqoop. Ambari also provides a dashboard for viewing cluster health such asheatmaps and ability to view MapReduce, Pig and Hive APs Plications Visuallyalongwith features to diagnose their performance characteristics in a user-friendlymanner.

Avro: A data serialization system.

Cassandra: A Scalable multi-master database with nosingle points of failure.

Chukwa: A data collection system for Managinglarge distributed systems.

HBase: A Scalable, distributed database, supportsstructured data storage for large tables.

Hive: A Data Warehouse infrastructure Thatprovides data summarization and ad hoc querying.

Mahout: A Scalable machine learning and datamining library.

Pig: A high-level Data-flow Language andexecution framework for parallel computation.

Spark : A Fast and general compute engine FORHADOOP data. Spark provides a simple and expressive programming model thatsupports a wide range of applications, including ETL, machine Learning, streamprocessing, and graph computation.

Tez: A generalized data-flow programmingframework, built on Hadoop YARN, which provides A powerful and flexible E Ngineto execute an arbitrary DAG of the tasks to process data for both batch andinteractive use-cases. Tez is being adopted by Hive, Pig and other frameworksin the Hadoop ecosystem, and also by other commercial software (e.g. Etltools), to replace Hadoop MapReduce as the underlying execution engine.

ZooKeeper: A high-performance Coordination ServiceFor distributed applications.

1.2 Hadoop Origins (1) Overview

U Apache Lucene

Open source High performance Full-Text Search Toolkit

U Apache Nutch

Open-source Web search engine

U Google three major papers

Mapreduce/gfs/bigtable

U Apache Hadoop

Large-scale data processing

(2) Lucene

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(3) from Lucene to Nutch, from Nutch to Hadoop

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1.3 Hadoop version Evolution

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It is divided into 3 main versions:

(1) with 0.20.x and 1.x.x-bit main branch

-2010:0.20. Version 2 adds append and security features

-Version 1.0 released at the end of 2011

(2) The main 0.23.x

-The 0.23.0 version was released in October 2011, adding YARN

(3) mainly 2.x.x

-March 2012 release of 2.0, solved single point of failure

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Enterprise-Class Hadoop 2.x introductory series Apache Hadoop 2.x Introduction and version _ Cloud Sail Big Data College