Spark : the definitive guide : big data processing made simple /

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sec...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Chambers, Bill (William Andrew) (Autor), Zaharia, Matei (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, [2018]
Edición:First edition.
Temas:
Spark (Electronic resource : Apache Software Foundation)
Data mining.
Information retrieval.
Big data.
Exploration de données (Informatique)
Recherche de l'information.
Données volumineuses.
information retrieval.
COMPUTERS > Computer Literacy.
COMPUTERS > Computer Science.
COMPUTERS > Data Processing.
COMPUTERS > Hardware > General.
COMPUTERS > Information Technology.
COMPUTERS > Machine Theory.
COMPUTERS > Reference.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You'll explore the basic operations and common functions of Spark's structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark's scalable machine-learning library. Get a gentle overview of big data and Spark. Learn about DataFrames, SQL, and Datasets--Spark's core APIs--through worked examples. Dive into Spark's low-level APIs, RDDs, and execution of SQL and DataFrames. Understand how Spark runs on a cluster. Debug, monitor, and tune Spark clusters and applications. Learn the power of Structured Streaming, Spark's stream-processing engine. Learn how you can apply MLlib to a variety of problems, including classification or recommendation.--Provided by publisher.
Notas:Includes index.
Descripción Física:1 online resource (xxvi, 576 pages) : illustrations
ISBN:9781491912300
1491912308
9781491912294
1491912294
9781491912201
1491912200
1491912219
9781491912218

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