Book Image

Real-time Analytics with Storm and Cassandra

By : Shilpi Saxena
Book Image

Real-time Analytics with Storm and Cassandra

By: Shilpi Saxena

Overview of this book

Table of Contents (19 chapters)
Real-time Analytics with Storm and Cassandra
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Building high availability of components


Now we are at an opportune juncture to look for high availability of various components in the cluster. We will do this as a series of exercises wherein we assume that each component is installed in the clustered mode and more than one instance of it exists in the ecosystem.

The high availability of RabbitMQ can be checked only after you have a mirrored queue in place. Let's assume:

  • We have two nodes in the RabbitMQ cluster: node1 and node2

  • MyExchange is the name of the exchange that is created for the purpose of this exercise

  • MyQueue is a mirrored queue that is created for this exercise

Next, we will just run the fixedEmitter code we created in the Creating a RabbitMQ feeder component section. Now perform the Litmus test:

  • Let's assume the queue MyQueue has 100 messages

  • Now bring down node2 (this means, one node on the cluster is down)

  • All the 100 messages will be retained and will be visible on the console; node1 fills in when there is an absence of node2...