Beginning Apache Spark 2

1. Front Matter

   Pages i-xi

   PDF

2. Introduction to Apache Spark

   • Hien Luu

   Pages 1-13

3. Working with Apache Spark

   • Hien Luu

   Pages 15-49

4. Resilient Distributed Datasets

   • Hien Luu

   Pages 51-86

5. Spark SQL (Foundations)

   • Hien Luu

   Pages 87-145

6. Spark SQL (Advanced)

   • Hien Luu

   Pages 147-217

7. Spark Streaming

   • Hien Luu

   Pages 219-286

8. Spark Streaming (Advanced)

   • Hien Luu

   Pages 287-326

9. Machine Learning with Spark

   • Hien Luu

   Pages 327-383

10. Back Matter

    Pages 385-393

    PDF

Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it.


Along the way, you’ll discover resilient distributed datasets (RDDs); use Spark SQL for structured data; and learn stream processing and build real-time applications with Spark Structured Streaming. Furthermore, you’ll learn the fundamentals of Spark ML for machine learning and much more. 



After you read this book, you will have the fundamentals to become proficient in using Apache Spark and know when and how to apply it to your big data applications.  




What You Will Learn  

• Understand Spark unified data processing platform
• Howto run Spark in Spark Shell or Databricks 
  
• Use and manipulate RDDs 
  
• Deal with structured data using Spark SQL through its operations and advanced functions
• Build real-time applications using Spark Structured Streaming
  
• Develop intelligent applications with the Spark Machine Learning library
  

Who This Book Is For


Programmers and developers active in big data, Hadoop, and Java but who are new to the Apache Spark platform.  

• Big Data
• Apache Spark
• Spark
• No SQL
• HDFS
• MapReduce
• Scala
• Spark Data Frames
• Hadoop

• SAN JOSE, USA

  Hien Luu

Hien Luu has extensive experience in designing and building big data applications and scalable web-based applications. He is particularly passionate about the intersection between big data and machine learning. Hien enjoys working with open source software and has contributed to Apache Pig and Azkaban. Teaching is also one of his passions, and he serves as an instructor at the UCSC Silicon Valley Extension school teaching Apache Spark. He has given presentations at various conferences such a QCon SF, QCon London, Seattle Data Day, Hadoop Summit, and JavaOne.

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