share_book
Envoyer cet article par e-mail

Hadoop: The Definitive Guide

ou partager sur :

share_comment
Partager ce commentaire par e-mail

ou partager sur :

PRÊT A ACHETER?
(vous pouvez toujours annuler plus tard)


J'aime
Hadoop: The Definitive Guide

Hadoop: The Definitive Guide

  (Auteur)


Prix : Cet article n'a pas encore de prix  ask_price

Demande de cotation sur ""
Ce titre est nouveau dans notre fonds d'ouvrages et nous ne l'avons encore jamais vendu à ce jour.
Notre engagement: Vous obtenir le meilleur prix
Aussi nombreux que soient les titres que nous référençons, absolument rien n'est automatisé dans la fixation de nos prix; et plutôt que de convertir automatiquement le prix en euros et risquer de répercuter sur vous un prix artificiellement élevé, nous vous faisons un devis rapide après avoir vérifié les prix auprès de nos différents fournisseurs.
Cette étape de demande de cotation est rapide (généralement quelques heures) et vise à vous faire bénéficier en permanence du meilleur prix pour vos achats de livres.


Sur commande

Des articles qui pourraient aussi vous intéresser

Description de "Hadoop: The Definitive Guide"

Ready to unleash the power of your massive dataset? With the latest edition of this comprehensive resource, you'll learn how to use Apache Hadoop to build and maintain reliable, scalable, distributed systems. It's ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. This third edition covers recent changes to Hadoop, including new material on the new MapReduce API, as well as version 2 of the MapReduce runtime (YARN) and its more flexible execution model. You'll also find illuminating case studies that demonstrate how Hadoop is used to solve specific problems.Store large datasets with the Hadoop Distributed File System (HDFS), then run distributed computations with MapReduce Use Hadoop's data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Analyze datasets with Hive, Hadoop's data warehousing system Load data from relational databases into HDFS, using Sqoop Take advantage of HBase, the database for structured and semi-structured data Use ZooKeeper, the toolkit for building distributed systems

Détails sur le produit

  • Reliure : Paperback
  • 630  pages
  • Editeur :   O'reilly Media Paru le
  • ISBN :  1449311520
  • EAN13 :  9781449311520
  • Langue : Anglais

Commentaires sur cet article

Personne n'a encore laissé de commentaire. Soyez le premier!

Laisser un commentaire

Rechercher des articles similaires par rayon

Rechercher par thèmes associés

Ready to unleash the power of your massive dataset? With the latest edition of this comprehensive resource, you'll learn how to use Apache Hadoop to build and maintain reliable, scalable, distributed systems. It's ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. This third edition covers recent changes to Hadoop, including new material on the new MapReduce API, as well as version 2 of the MapReduce runtime (YARN) and its more flexible execution model. You'll also find illuminating case studies that demonstrate how Hadoop is used to solve specific problems.Store large datasets with the Hadoop Distributed File System (HDFS), then run distributed computations with MapReduce Use Hadoop's data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Analyze datasets with Hive, Hadoop's data warehousing system Load data from relational databases into HDFS, using Sqoop Take advantage of HBase, the database for structured and semi-structured data Use ZooKeeper, the toolkit for building distributed systems