Perform lightning-fast Big Data processing using Apache Spark 2.x with help of this practical guide
Key Features:
- Contains quick solutions to solving even the most complex Big Data processing problems using Apache Spark
- Leverage the power of Apache Spark as a unified compute engine and perform streaming analytics, machine learning and graph processing with ease
- From installing and setting up Spark to fine-tuning its performance, this practical guide is all you need to become a master in using Apache Spark
Book Description:
While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data.
Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark.
Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting.
What You Will Learn:
- Install and configure Apache Spark with various cluster managers & on AWS
- Set up a development environment for Apache Spark including Databricks Cloud notebook
- Find out how to operate on data in Spark with schemas
- Get to grips with real-time streaming analytics using Spark Streaming & Structured Streaming
- Master supervised learning and unsupervised learning using MLlib
- Build a recommendation engine using MLlib
- Graph processing using GraphX and GraphFrames libraries
- Develop a set of common applications or project types, and solutions that solve complex big data problems
Who this book is for:
This book is for data engineers, data scientists, and Big Data professionals who want to leverage the power of Apache Spark 2.x for real-time Big Data processing. If you're looking for quick solutions to common problems while using Spark 2.x effectively, this book will also help you. The book assumes you have a basic knowledge of Scala as a programming language.
Rishi Yadav has 19 years of experience in designing and developing enterprise applications. He is an open source software expert and advises American companies on big data and public cloud trends. Rishi was honored as one of Silicon Valley's 40 under 40 in 2014. He earned his bachelor's degree from the prestigious Indian Institute of Technology, Delhi, in 1998. About 12 years ago, Rishi started InfoObjects, a company that helps data-driven businesses gain new insights into data. InfoObjects combines the power of open source and big data to solve business challenges for its clients and has a special focus on Apache Spark. The company has been on the Inc. 5000 list of the fastest growing companies for 6 years in a row. InfoObjects has also been named the best place to work in the Bay Area in 2014 and 2015. Rishi is an open source contributor and active blogger. This book is dedicated to my parents, Ganesh and Bhagwati Yadav; I would not be where I am without their unconditional support, trust, and providing me the freedom to choose a path of my own. Special thanks go to my life partner, Anjali, for providing immense support and putting up with my long, arduous hours (yet again).Our 9-year-old son, Vedant, and niece, Kashmira, were the unrelenting force behind keeping me and the book on track. Big thanks to InfoObjects' CTO and my business partner, Sudhir Jangir, for providing valuable feedback and also contributing with recipes on enterprise security, a topic he is passionate about; to our SVP, Bart Hickenlooper, for taking the charge in leading the company to the next level; to Tanmoy Chowdhury and Neeraj Gupta for their valuable advice; to Yogesh Chandani, Animesh Chauhan, and Katie Nelson for running operations skillfully so that I could focus on this book; and to our internal review team (especially Rakesh Chandran) for ironing out the kinks. I would also like to thank Marcel Izumi for, as always, providing creative visuals. I cannot miss thanking our dog, Sparky, for giving me company on my long nights out. Last but not least, special thanks to our valuable clients, partners, and employees, who have made InfoObjects the best place to work at and, needless to say, an immensely successful organization.
