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Learning Spark Lightning Fast Big Data Analysis 1st Edition by Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia ISBN 1449358624 9781449358624

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Learning Spark Lightning Fast Big Data Analysis 1st Edition Holden Karau Digital Instant Download

Author(s): Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia
ISBN(s): 9781449358624, 1449358624
Edition: 1
File Details: PDF, 7.82 MB
Year: 2015
Language: english
SKU: EB-4986324 Category: Tags: , , ,

Learning Spark Lightning Fast Big Data Analysis 1st Edition by Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia – Ebook PDF Instant Download/Delivery: 1449358624, 9781449358624
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Product details:

ISBN 10: 1449358624 
ISBN 13: 9781449358624
Author: Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, 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. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates.

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

Learning Spark Lightning Fast Big Data Analysis 1st Table of contents:

Part 1: Introduction to Spark

  1. Chapter 1: Introduction to Big Data and Apache Spark

  2. Chapter 2: Getting Started with Spark

  3. Chapter 3: Spark’s Core Concepts and Architecture

Part 2: Spark’s Core Libraries
4. Chapter 4: Working with RDDs (Resilient Distributed Datasets)
5. Chapter 5: Introduction to DataFrames and Datasets
6. Chapter 6: Spark SQL and Structured Streaming

Part 3: Advanced Spark Techniques
7. Chapter 7: Machine Learning with Spark MLlib
8. Chapter 8: Spark GraphX for Graph Processing
9. Chapter 9: Tuning Spark Performance and Optimizing Jobs

Part 4: Using Spark in Practice
10. Chapter 10: Building a Spark Application
11. Chapter 11: Running Spark on a Cluster
12. Chapter 12: Integrating Spark with Other Tools and Frameworks

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Tags: Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia, Spark Lightning, Data Analysis