About This Book
- Become an expert at graph processing using GraphX
- Use Apache Spark as your single big data compute platform and master its libraries
- Learn with recipes that can be run on a single machine as well as on a production cluster of thousands of machines
Who This Book Is For
If you are a data engineer, application developer, or data scientist who would like to leverage the power of Apache Spark to get better insights from big data, this is the book for you.
What You Will Learn
- Install and configure Apache Spark with various cluster managers
- Set up development environments
- Perform interactive queries using Spark SQL
- Get to grips with real-time streaming analytics using Spark Streaming
- Master supervised learning and unsupervised learning using MLlib
- Build a recommendation engine using MLlib
- Develop a set of common applications or project types and solutions that solve complex big data problems
The success of Hadoop as a big data platform had users asking for more. Apache Spark emerged as one standard, rather than a combination of tools, which solves all these challenges in one shot. By introducing in-memory persistent storage, Apache Spark eliminated the need to store intermediate data in filesystems, thereby increasing the processing speed up to 100 times. It provides a single-computer platform that takes care of various computer needs such as machine learning and real-time streaming.
This book will focus on how one can analyze large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will cover setting development environments. You will then cover various recipes to perform interactive queries using Spark SQL and then real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will then focus on machine learning including supervised learning, unsupervised learning, and recommendation engine algorithms. Once you master graph processing using GraphX you will cover various recipes for cluster optimization and troubleshooting will also be discussed.