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DATA ANALYTICS WITH SPARK USING PYTHON (pb) 2019
Author: JEFFREY AVEN
ISBN: 9789353068455
Year: 2019
Publisher: PEARSON EDUCATION ASIA
Category: PROGRAMMING / LANGUAGE
Edition: 1
Format: Paperback
Language: English
Pages: 320
 ABOUT THE TITLE
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 students 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 students at various levels of experience-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. Students will 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.



Salient Features:

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.




Author: Jeffrey Aven
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 TABLE OF CONTENTS
PART I: SPARK FOUNDATIONS
Chapter 1: Introducing Big Data, Hadoop, and Spark
Chapter 2: Deploying Spark
Chapter 3: Understanding the Spark Cluster Architecture
Chapter 4: Learning Spark Programming Basics
PART II: BEYOND THE BASICS
Chapter 5: Advanced Programming Using the Spark Core API
Chapter 6: SQL and NoSQL Programming with Spark
Chapter 7: Stream Processing and Messaging Using Spark
Chapter 7 Stream Processing and Messaging Using Spark
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