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Big Data Analytics

You're reading from Big Data Analytics Real time analytics using Apache Spark and Hadoop

Product type Paperback

Published in Sep 2016

Publisher Packt

ISBN-13 9781785884696

Length 326 pages

Edition 1st Edition

Tools

Hadoop

Concepts

Big Data

Author (1):

Venkat Ankam

View More author details

Table of Contents (12) Chapters

Preface

1. Big Data Analytics at a 10,000-Foot View

2. Getting Started with Apache Hadoop and Apache Spark FREE CHAPTER

3. Deep Dive into Apache Spark

4. Big Data Analytics with Spark SQL, DataFrames, and Datasets

5. Real-Time Analytics with Spark Streaming and Structured Streaming

6. Notebooks and Dataflows with Spark and Hadoop

7. Machine Learning with Spark and Hadoop

8. Building Recommendation Systems with Spark and Mahout

9. Graph Analytics with GraphX

10. Interactive Analytics with SparkR

Index

Introducing SQL, Datasources, DataFrame, and Dataset APIs

Let's understand four components in Spark SQL—SQL, the Data Sources API, the DataFrame API, and the Dataset API.

Spark SQL can write and read data to and from Hive tables using the SQL language. SQL can be used within Java, Scala, Python, R languages, over JDBC/ODBC, or using the command-line option. When SQL is used in programming languages, the results will be converted as DataFrames.

Advantages of SQL are:

Can work with Hive tables easily
Can connect BI tools to a distributed SQL engine using Thrift Server and submit SQL or Hive QL queries using JDBC or ODBC interfaces

The Data Sources API provides a single interface for reading and writing data using Spark SQL. In addition to the in-built sources that come prepackaged with the Apache Spark distribution, the Data Sources API provides integration for external developers to add custom data sources. All external data sources and other packages can be viewed at http:/...

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Authors (1)

Venkat Ankam

Venkat Ankam

Venkat Ankam has over 18 years of IT experience and over 5 years in big data technologies, working with customers to design and develop scalable big data applications. Having worked with multiple clients globally, he has tremendous experience in big data analytics using Hadoop and Spark. He is a Cloudera Certified Hadoop Developer and Administrator and also a Databricks Certified Spark Developer. He is the founder and presenter of a few Hadoop and Spark meetup groups globally and loves to share knowledge with the community. Venkat has delivered hundreds of trainings, presentations, and white papers in the big data sphere. While this is his first attempt at writing a book, many more books are in the pipeline.

See other products by Venkat Ankam

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