PortadaGruposSe habla deMásVisión actual
Buscar En Este Sitio
Este sitio utiliza cookies para ofrecer nuestros servicios, mejorar el rendimiento, para análisis y (si no está registrado) para publicidad. Al usar LibraryThing reconoces que has leído y comprendido nuestros Términos de Servicio y Política de Privacidad. Su uso del sitio y de los servicios está sujeto a estas políticas y términos.
Hide this

Resultados de Google Books

Pulse en una miniatura para ir a Google Books.

Cargando...

Hadoop: The Definitive Guide

por Tom White

MiembrosReseñasPopularidadValoración promediaMenciones
231289,899 (3.74)1
Hadoop: The Definitive Guide helps you harness the power of your data. Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters.Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you: Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, 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 Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject."Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk."-- Doug Cutting, Hadoop Founder, Yahoo!… (más)
  1. 10
    Data-Intensive Text Processing with MapReduce (Synthesis Lectures on Human Language Technologies) por Jimmy Lin (billmcn)
    billmcn: Once you've mastered the basics with the O'Reilly book, this is a good next step. Lin and Dyer's book covers advanced techniques such as in-mapper combining and secondary sorts, along with discussions of advanced applications like Page Rank and Expectation Maximization.… (más)
Ninguno
Cargando...

Inscríbete en LibraryThing para averiguar si este libro te gustará.

No hay Conversaciones actualmente sobre este libro.

» Ver también 1 mención

Mostrando 2 de 2
Its bible of hadoop. ( )
  madhukaraphatak | Aug 12, 2020 |
A comprehensive review of the Hadoop ecosystem, with plenty of hands-on advice. Some of the content for the various sub-projects (Sqoop, Hive etc) is somewhat repetitive and lacks depth, but these are ancillary to the book's core purpose of explaining what Hadoop is about, which it achieves. ( )
  gbsallery | Mar 3, 2013 |
Mostrando 2 de 2
sin reseñas | añadir una reseña
Debes iniciar sesión para editar los datos de Conocimiento Común.
Para más ayuda, consulta la página de ayuda de Conocimiento Común.
Título canónico
Título original
Títulos alternativos
Fecha de publicación original
Personas/Personajes
Lugares importantes
Eventos importantes
Películas relacionadas
Premios y honores
Epígrafe
Dedicatoria
Información del conocimiento común inglés. Edita para encontrar en tu idioma.
For Eliane, Emilia, and Lottie
Primeras palabras
Información del conocimiento común inglés. Edita para encontrar en tu idioma.
Martin Gardner, the mathematics and science writer, once said in an interview:

"Beyond calculus, I am lost. That was the secret of my column's success. It took me so long to understand what I was writing about that I knew how to write in a way most readers would understand."
Citas
Últimas palabras
Información del conocimiento común inglés. Edita para encontrar en tu idioma.
(Click para mostrar. Atención: puede contener spoilers.)
Aviso de desambigüedad
Editores
Blurbistas
Idioma original
DDC/MDS Canónico

Referencias a esta obra en fuentes externas.

Wikipedia en inglés (5)

Hadoop: The Definitive Guide helps you harness the power of your data. Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters.Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you: Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, 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 Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject."Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk."-- Doug Cutting, Hadoop Founder, Yahoo!

No se han encontrado descripciones de biblioteca.

Descripción del libro
Resumen Haiku

Enlaces rápidos

Cubiertas populares

Valoración

Promedio: (3.74)
0.5
1
1.5
2 1
2.5
3 6
3.5 2
4 11
4.5
5 3

O'Reilly Media

Una edición de este libro fue publicada por O'Reilly Media.

» Página de Información del Editor

GenreThing

No genres

¿Este eres tú?

Conviértete en un Autor de LibraryThing.

 

Acerca de | Contactar | LibraryThing.com | Privacidad/Condiciones | Ayuda/Preguntas frecuentes | Blog | Tienda | APIs | TinyCat | Bibliotecas de Figuras Notables | Primeros Reseñadores | Conocimiento Común | 160,395,395 libros! | Barra superior: Siempre visible