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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

Data Sources API

The Data Sources API provides a single interface for loading and storing data using Spark SQL. In addition to the built-in sources, this API provides an easy way for developers to add support for custom data sources. All available external packages are listed at http://spark-packages.org/. Let's learn how to use built-in sources and external sources in this section.

Read and write functions

The Data Sources API provides generic read and write functions that can used for any kind of data source. Generic read and write functions provide two functionalities as given in the following:

Parses text records, JSON records, and other formats and deserializes data stored in binary
Converts Java objects to rows of Avro, JSON, Parquet, and HBase records

The default data source is set to parquet with the spark.sql.sources.default configuration property. This can be changed as needed.

Built-in sources

Built-in sources are pre-packaged with Spark by default. Examples of built-in sources are Text...

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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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