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Learning Spark SQL

You're reading from   Learning Spark SQL Architect streaming analytics and machine learning solutions

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781785888359
Length 452 pages
Edition 1st Edition
Languages
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Author (1):
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Aurobindo Sarkar Aurobindo Sarkar
Author Profile Icon Aurobindo Sarkar
Aurobindo Sarkar
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Spark SQL FREE CHAPTER 2. Using Spark SQL for Processing Structured and Semistructured Data 3. Using Spark SQL for Data Exploration 4. Using Spark SQL for Data Munging 5. Using Spark SQL in Streaming Applications 6. Using Spark SQL in Machine Learning Applications 7. Using Spark SQL in Graph Applications 8. Using Spark SQL with SparkR 9. Developing Applications with Spark SQL 10. Using Spark SQL in Deep Learning Applications 11. Tuning Spark SQL Components for Performance 12. Spark SQL in Large-Scale Application Architectures

Introducing SparkR


R is a language and environment for statistical computing and visualization. It is one of the most popular tools used by statisticians and data scientists. R is open source and provides a dynamic interactive environment with a rich set of packages and powerful visualization features. It is an interpreted language that includes extensive support for numerical computing, with data types for vectors, matrices, arrays, and libraries for performing numerical operations.

R provides support for structured data processing using DataFrames. R DataFrames make data manipulation simpler and more convenient. However, R's dynamic design limits the extent of possible optimizations. Additionally, interactive data analysis capabilities and overall scalability are also limited, as the R runtime is single threaded and can only process Datasets that fit in a single machine's memory.

Note

For more details on R, refer to the R project website at https://www.r-project.org/about.html.

SparkR addresses...

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