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InfoQ Homepage Guides Big Data Processing with Apache Spark

Big Data Processing with Apache Spark

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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.

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Buy the print version for $19.99

Table of Contents:

  • Part 1: Overview        
  • Part 2: Spark SQL                
  • Part 3: Spark Streaming       
  • Part 4: Spark Machine Learning           
  • Part 5: spark.ml Data Pipelines        
  • Part 6: Graph Data Analytics with Spark GraphX     
  • Part 7: Emerging Trends in Data Science 
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