Book Image

Learning Apache Spark 2

Book Image

Learning Apache Spark 2

Overview of this book

Apache Spark has seen an unprecedented growth in terms of its adoption over the last few years, mainly because of its speed, diversity and real-time data processing capabilities. It has quickly become the preferred choice of tool for many Big Data professionals looking to find quick insights from large chunks of data. This book introduces you to the Apache Spark framework, and familiarizes you with all the latest features and capabilities introduced in Spark 2. Starting with a detailed introduction to Spark’s architecture and the installation procedure, this book covers everything you need to know about the Spark framework in the most practical manner. You will learn how to perform the basic ETL activities using Spark, and work with different components of Spark such as Spark SQL, as well as the Dataset and DataFrame APIs for manipulating your data. Then, you will perform machine learning using Spark MLlib, as well as perform streaming analytics and graph processing using the Spark Streaming and GraphX modules respectively. The book also gives special emphasis on deploying your Spark models, and how they can be operated in a clustered mode. During the course of the book, you will come across implementations of different real-world use-cases and examples, giving you the hands-on knowledge you need to use Apache Spark in the best possible manner.
Table of Contents (18 chapters)
Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface

Structured Data sources and Databases


Spark works with a variety of structured data sources including, but not limited to, the following:

  1. Parquet Files: Apache Parquet is a columnar storage format. More details about the structure of Parquet and how spark makes use of it is available in the Spark SQL chapter.
  2. Hive tables.
  3. JDBC: Spark allows the use of JDBC to connect to a wide variety of databases. Of course the data access via JDBC is relatively slow compared to native database utilities.

We'll cover most of the structured sources in Chapter 4, Spark SQL later in this book.

Working with NoSQL Databases

A NoSQL (originally referring to non SQL, non relational or not only SQL) database provides a mechanism for storage (https://en.wikipedia.org/wiki/Computer_data_storage) and retrieval (https://en.wikipedia.org/wiki/Data_retrieval) of data which is modeled in means other than the tabular relations used in Relational databases (https://en.wikipedia.org/wiki/Relational_database). NoSQL is a relatively...