Apache Spark in 24 Hours, Sams Teach Yourself : 9780672338519

Apache Spark in 24 Hours, Sams Teach Yourself

Published by
Pearson Higher Ed USA
Available on demand
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Apache Spark is rapidly becoming the preferred computing engine for Big Data systems. It's fast, fast, scalable, fault-tolerant, and exceptionally flexible and extensible. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to successfully build practical Spark solutions. Each short, easy lesson builds on all that's come before: you'll learn all of Spark's essentials, and extend it to meet your unique challenges. Apache Spark in 24 Hours, Sams Teach Yourself covers all this, and much more:

  • What Apache Spark does, and how it fits into the Big Data landscape
  • How to deploy Spark local or in the cloud, and use the Spark Cluster Architecture
  • How to program Spark applications with Scala, functional Python, and the Spark API
  • How to use RDDs for caching, persistence, and output
  • How to use Spark with both SQL and NoSQL
  • How to work with advanced Spark programming techniques and common processing patterns
  • How to extend spark with streaming, machine learning, R, and Sparkling Water
  • How to manage Spark, extend it, and improve its performance
  • Where Spark is headed, and how to prepare for the future

Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Spark to solve a wide spectrum of Big Data problems.

Table of contents
Hour 1. Introducing Apache Spark
Hour 2. Spark and the Big Data Landscape
Hour 3. Deploying Spark
Hour 4. Spark Cluster Architecture
Hour 5. Spark Programming Basics
Hour 6. Scala Programming Primer
Hour 7. Functional Python Programming
Hour 8. MapReduce Revisited
Hour 9. The Spark API (Transformations and Actions)
Hour 10. RDDs: Caching, Persistence and Output
Hour 11. Advanced Spark Programming
Hour 12. Using SQL with Spark
Hour 13. Common Processing Patterns in Spark
Hour 14. Spark Streaming
Hour 15. Spark and R
Hour 16. Machine Learning in Spark
Hour 17. Sparkling Water (H20 and Spark)
Hour 18. Managing Spark
Hour 19. Extending Spark
Hour 20. Improving Spark Performance
Hour 21. Spark in the Cloud
Hour 22. Spark and NoSQL using Apache Cassandra
Hour 23. Spark and Message Queues
Hour 24. The Future for Spark