• Title Big Data Processing with Apache Spark
• Author(s) Srini Penchikala
• Publisher: InfoQ (2018)
• Paperback: N/A
• eBook PDF (104 pages)
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
• Share This:  

Book Description

Apache Spark is an open-source big-data processing framework built around speed, ease of use, and sophisticated analytics.

Spark has several advantages compared to other big-data and MapReduce technologies like Hadoop and Storm. It provides a comprehensive, unified framework with which to manage big-data processing requirements for datasets that are diverse in nature (text data, graph data, etc.) and that come from a variety of sources (batch versus real-time streaming data).

Spark enables applications in HDFS clusters to run up to a hundred times faster in memory and ten times faster even when running on disk.

In this mini-book, the reader will learn about the Apache Spark framework and will develop Spark programs for use cases in big-data analysis. The book covers all the libraries that are part of Spark ecosystem, which includes Spark Core, Spark SQL, Spark Streaming, Spark MLlib, and Spark GraphX.

• Srini Penchikala currently works as Software Architect at a financial services organization in Austin, Texas. He has over 20 years of experience in software architecture, design and development.

• Amazon

• Big Data
• Data Science
• Parallel, Concurrent, and Distributed Computing and Programming
• Data Analysis and Data Mining
• Non-relational/NoSQL Databases

• Big Data Processing with Apache Spark (Srini Penchikala)

• Mastering Apache Spark 2.0 (Jacek Laskowski)
• Hadoop Explained (Aravind Shenoy)
• Big Data on Real-World Applications (Sebastian Ventura Soto)
• O'Reilly® Programming Pig (Alan F Gates)
• O'Reilly® Graph Databases (Ian Robinson, et al)