Data Analytics with Spark Using Python

Jeffrey Aven

ISBN 10: 013484601X / ISBN 13: 9780134846019

Published by Pearson Education, 2018

About this Item

Data Analytics with Spark Using Python | Jeffrey Aven | Taschenbuch | Kartoniert / Broschiert | Englisch | 2018 | Pearson Education | EAN 9780134846019 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Seller Inventory # 109150707

Bibliographic Details

• Title: Data Analytics with Spark Using Python
• Publisher: Pearson Education
• Publication Date: 2018
• Language: English
• ISBN 10: 013484601X
• ISBN 13: 9780134846019
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 179H x 19D millimeters 234 millimeters width by 179 millimeters height by 19 millimeters depth
• Weight: 521 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Solve Data Analytics Problems with Spark, PySpark, and Related Open Source Tools

Spark is at the heart of today’s Big Data revolution, helping data professionals supercharge efficiency and performance in a wide range of data processing and analytics tasks. In this guide, Big Data expert Jeffrey Aven covers all you need to know to leverage Spark, together with its extensions, subprojects, and wider ecosystem.

Aven combines a language-agnostic introduction to foundational Spark concepts with extensive programming examples utilizing the popular and intuitive PySpark development environment. This guide’s focus on Python makes it widely accessible to large audiences of data professionals, analysts, and developers―even those with little Hadoop or Spark experience.

Aven’s broad coverage ranges from basic to advanced Spark programming, and Spark SQL to machine learning. You’ll learn how to efficiently manage all forms of data with Spark: streaming, structured, semi-structured, and unstructured. Throughout, concise topic overviews quickly get you up to speed, and extensive hands-on exercises prepare you to solve real problems.

Coverage includes:
• Understand Spark’s evolving role in the Big Data and Hadoop ecosystems
• Create Spark clusters using various deployment modes
• Control and optimize the operation of Spark clusters and applications
• Master Spark Core RDD API programming techniques
• Extend, accelerate, and optimize Spark routines with advanced API platform constructs, including shared variables, RDD storage, and partitioning
• Efficiently integrate Spark with both SQL and nonrelational data stores
• Perform stream processing and messaging with Spark Streaming and Apache Kafka
• Implement predictive modeling with SparkR and Spark MLlib

About the Author

Jeffrey Aven is an independent Big Data, open source software and cloud computing professional based out of Melbourne, Australia. Jeffrey is a highly regarded consultant and instructor and has authored several other books including Teach Yourself Apache Spark in 24 Hours and Teach Yourself Hadoop in 24 Hours.