Book Image

Hadoop Blueprints

By : Anurag Shrivastava, Tanmay Deshpande
Book Image

Hadoop Blueprints

By: Anurag Shrivastava, Tanmay Deshpande

Overview of this book

If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.
Table of Contents (14 chapters)
Hadoop Blueprints
About the Authors
About the Reviewers

Apache Flume

Data Lakes can be filled with data coming from multiple sources at different speeds. The tools in the ingestion tier, such as Apache Flume, can handle the massive volume of incoming data and store it on HDFS.

Apache Flume is a distributed and scalable tool that can reliably collect the data from different sources and move it to a centralized data store on HDFS. Massive volumes of data can be generated in the form of weblogs or sensor data and stored on HDFS for analysis and distribution. Though the typical use cases of Apache Flume involve collection and storage of log data, it can be used to ingest any kind of data in HDFS.

Understanding the Design of Flume

Flume is an agent-based system. It contains three components:

  • Source: The source receives the events from an external system or from the sink of another Flume agent.

  • Channel: This offers the means to let events flow from a source to a sink. A channel is a transient store that holds the event coming from a source until it is...