Mastering Apache Spark + code

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Название: Mastering Apache Spark

Автор:Mike Frampton

Издательство: PACKT

Год: 2015

Страниц: 318

Язык: English

Формат: epub+code

Размер: 8,5 Mb

Gain expertise in processing and storing data by using advanced techniques with Apache Spark

If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected.

About This Book

Explore the integration of Apache Spark with third party applications such as H20, Databricks and Titan

Evaluate how Cassandra and Hbase can be used for storage

An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities

Who This Book Is For

If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected.

Table of Contents

1: Apache Spark

2: Apache Spark MLlib

3: Apache Spark Streaming

4: Apache Spark SQL

5: Apache Spark GraphX

6: Graph-based Storage

7: Extending Spark with H2O

8: Spark Databricks

9: Databricks Visualization

What You Will Learn

Extend the tools available for processing and storage

Examine clustering and classification using MLlib

Discover Spark stream processing via Flume, HDFS

Create a schema in Spark SQL, and learn how a Spark schema can be populated with data

Study Spark based graph processing using Spark GraphX

Combine Spark with H20 and deep learning and learn why it is useful

Evaluate how graph storage works with Apache Spark, Titan, HBase and Cassandra

Use Apache Spark in the cloud with Databricks and AWS

In Detail

Apache Spark is an in-memory cluster based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and SQL. It operates at unprecedented speeds, is easy to use and offers a rich set of data transformations.

This book aims to take your limited knowledge of Spark to the next level by teaching you how to expand Spark functionality. The book commences with an overview of the Spark eco-system. You will learn how to use MLlib to create a fully working neural net for handwriting recognition. You will then discover how stream processing can be tuned for optimal performance and to ensure parallel processing. The book extends to show how to incorporate H20 for machine learning, Titan for graph based storage, Databricks for cloud-based Spark. Intermediate Scala based code examples are provided for Apache Spark module processing in a CentOS Linux and Databricks cloud environment.

Authors

Mike Frampton

Mike Frampton is an IT contractor, blogger, and IT author with a keen interest in new technology and big data. He has worked in the IT industry since 1990 in a range of roles (tester, developer, support, and author). He has also worked in many other sectors (energy, banking, telecoms, and insurance). He now lives by the beach in Pa raparaumu, New Zealand, with his wife and teenage son. Being married to a Thai national, he divides his time between Paraparaumu and their house in Roi Et, Thailand, between writing and IT consulting.

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