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
About the Authors
About the Reviewers
Customer Feedback
Part 1 - Overview
Part 2 - Technical Building blocks of Data Lake
Part 3 - Bringing It All Together

Kafka connect

Extensibility is one of the important design principle followed rigorously by Kafka. The Kafka Connect tool makes Kafka extensible. The tool enables Kafka to connect with external systems and helps bring data into it, and also out from it to other systems. It has a common framework, using which custom connectors can be written. More details on Kafka connect can be found in Kafka documentation in

The following figure shows how Kafka Connect works.

Figure 13: Kafka connect working

The Kafka connectors are categorized into two:

  • Source Connectors: Connectors which bring data into Kafka topics.
  • Sink Connectors: Connectors which take data away from topics into other external systems

There are a huge list of connectors available, catering to various external systems, using which Kafka can hook onto them. These existing connectors are again categorized broadly into two:

  • Certified connectors: Connectors which are written using the Kafka...