By Holden Karau,Andy Konwinski,Patrick Wendell,Matei Zaharia
Data in all domain names is getting larger. how will you paintings with it successfully? Recently up to date for Spark 1.3, this e-book introduces Apache Spark, the open resource cluster computing process that makes facts analytics quickly to write down and speedy to run. With Spark, you could take on enormous datasets quick via uncomplicated APIs in Python, Java, and Scala. This version contains new details on Spark SQL, Spark Streaming, setup, and Maven coordinates.
Written via the builders of Spark, this ebook can have information scientists and engineers up and working very quickly. You’ll the right way to exhibit parallel jobs with quite a few traces of code, and canopy purposes from easy batch jobs to circulation processing and desktop learning.
- Quickly dive into Spark functions similar to disbursed datasets, in-memory caching, and the interactive shell
- Leverage Spark’s robust integrated libraries, together with Spark SQL, Spark Streaming, and MLlib
- Use one programming paradigm rather than mix and matching instruments like Hive, Hadoop, Mahout, and Storm
- Learn the way to set up interactive, batch, and streaming applications
- Connect to information assets together with HDFS, Hive, JSON, and S3
- Master complex themes like facts partitioning and shared variables
Read or Download Learning Spark: Lightning-Fast Big Data Analysis PDF
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Extra resources for Learning Spark: Lightning-Fast Big Data Analysis
Learning Spark: Lightning-Fast Big Data Analysis by Holden Karau,Andy Konwinski,Patrick Wendell,Matei Zaharia