Field Guide to Hadoop. An Introduction to Hadoop, Its Ecosystem, and Aligned Technologies

Par : Kevin Sitto, Marshall Presser
Définitivement indisponible
Cet article ne peut plus être commandé sur notre site (ouvrage épuisé ou plus commercialisé). Il se peut néanmoins que l'éditeur imprime une nouvelle édition de cet ouvrage à l'avenir. Nous vous invitons donc à revenir périodiquement sur notre site.
Disponible dans votre compte client Decitre ou Furet du Nord dès validation de votre commande. Le format Multi-format est :
  • Pour les liseuses autres que Vivlio, vous devez utiliser le logiciel Adobe Digital Edition. Non compatible avec la lecture sur les liseuses Kindle, Remarkable et Sony
Logo Vivlio, qui est-ce ?

Notre partenaire de plateforme de lecture numérique où vous retrouverez l'ensemble de vos ebooks gratuitement

Pour en savoir plus sur nos ebooks, consultez notre aide en ligne ici
C'est si simple ! Lisez votre ebook avec l'app Vivlio sur votre tablette, mobile ou ordinateur :
Google PlayApp Store
  • Nombre de pages132
  • FormatMulti-format
  • ISBN978-1-4919-4787-6
  • EAN9781491947876
  • Date de parution02/03/2015
  • Protection num.NC
  • Infos supplémentairesMulti-format incluant PDF sans p...
  • ÉditeurO'Reilly Media

Résumé

If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You'll quickly understand how Hadoop's projects, subprojects, and related technologies work together. Each chapter introduces a different topic-such as core technologies or data transfer-and explains why certain components may or may not be useful for particular needs.
When it comes to data, Hadoop is a whole new ballgame, but with this handy reference, you'll have a good grasp of the playing field. Topics include: - Core technologies-Hadoop Distributed File System (HDFS), MapReduce, YARN, and Spark - Database and data management-Cassandra, HBase, MongoDB, and Hive - Serialization-Avro, JSON, and Parquet - Management and monitoring-Puppet, Chef, Zookeeper, and Oozie - Analytic helpers-Pig, Mahout, and MLLib - Data transfer-Scoop, Flume, distcp, and Storm - Security, access control, auditing-Sentry, Kerberos, and Knox - Cloud computing and virtualization-Serengeti, Docker, and Whirr
If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You'll quickly understand how Hadoop's projects, subprojects, and related technologies work together. Each chapter introduces a different topic-such as core technologies or data transfer-and explains why certain components may or may not be useful for particular needs.
When it comes to data, Hadoop is a whole new ballgame, but with this handy reference, you'll have a good grasp of the playing field. Topics include: - Core technologies-Hadoop Distributed File System (HDFS), MapReduce, YARN, and Spark - Database and data management-Cassandra, HBase, MongoDB, and Hive - Serialization-Avro, JSON, and Parquet - Management and monitoring-Puppet, Chef, Zookeeper, and Oozie - Analytic helpers-Pig, Mahout, and MLLib - Data transfer-Scoop, Flume, distcp, and Storm - Security, access control, auditing-Sentry, Kerberos, and Knox - Cloud computing and virtualization-Serengeti, Docker, and Whirr