Reading Learning Spark: Lightning-Fast Big Data Analysis [Paperback]

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Data in all domains is getting bigger. How can you work with it efficiently? This book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala.

Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.

Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell
Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib
Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm
Learn how to deploy interactive, batch, and streaming applications
Connect to data sources including HDFS, Hive, JSON, and S3
Master advanced topics like data partitioning and shared variables



Author : Holden Karau - Andy Konwinski - Patrick Wendell - Matei Zaharia
Publisher: O'Reilly Media; 1 edition (February 27, 2015)
Length : 274 pages
File Size:
License Model : Purchase
Language: English
Release Date: February 27, 2015
Date Update : March 03, 2015

What's content in Learning Spark: Lightning-Fast Big Data Analysis :

1: Introduction to Data Analysis with Spark
2: Downloading Spark and Getting Started
3: Programming with RDDs
4: Working with Key/Value Pairs
5: Loading and Saving Your Data
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11: Machine Learning with MLlib

Reading Learning Spark: Lightning-Fast Big Data Analysis

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Reading Learning Spark: Lightning-Fast Big Data Analysis

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Reading Learning Spark: Lightning-Fast Big Data Analysis


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