Book Image

Data Lake for Enterprises

By : Vivek Mishra, Tomcy John, Pankaj Misra
Book Image

Data Lake for Enterprises

By: Vivek Mishra, Tomcy John, Pankaj Misra

Overview of this book

The term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together. This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient. By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.
Table of Contents (23 chapters)
Title Page
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Part 1 - Overview
Part 2 - Technical Building blocks of Data Lake
Part 3 - Bringing It All Together

Context Routing


As explained earlier, event has two main parts namely Header and Payload. Header (Key/Value pair) values can be used and accordingly routing defined. Two components where the routing selection can be decided are:

  • Channel: A channel can be selected according to the header values. Custom component namely Channel Selector can be written which can have code written to select the channel desired for achieving your use case.
  • Sink: As before, header values can be used to make decisions to select the right sink. Also, within the sink different operations can be performed by writing custom sink which can do whatever your use case require. There are some default header values which can also be used to do sophisticated stuff for your use case selected.

Basically you can introduce any number of headers and using which your components can do the right stuff. Doing this, the flume components behaves dynamically in all aspects.