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Learning Real-time Analytics with Storm and Cassandra

You're reading from   Learning Real-time Analytics with Storm and Cassandra Solve real-time analytics problems effectively using Storm and Cassandra

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781784395490
Length 220 pages
Edition 1st Edition
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Author (1):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
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Toc

Table of Contents (14) Chapters Close

Preface 1. Let's Understand Storm FREE CHAPTER 2. Getting Started with Your First Topology 3. Understanding Storm Internals by Examples 4. Storm in a Clustered Mode 5. Storm High Availability and Failover 6. Adding NoSQL Persistence to Storm 7. Cassandra Partitioning, High Availability, and Consistency 8. Cassandra Management and Maintenance 9. Storm Management and Maintenance 10. Advance Concepts in Storm 11. Distributed Cache and CEP with Storm A. Quiz Answers Index

Components of a Storm topology


A Storm topology consists of two basic components: a spout and one or more bolts. These building blocks are tied together using streams; it is over these streams that endless arrays of tuples flow.

Let's discuss the topology with a simple analogy, as depicted in the diagram and explained thereafter:

In our example topology, we have a big processing unit for roasted chips where the input, raw potato, is consumed by the spout, and there are various bolts such as a peeler bolt, slicer bolt, and roasting bolt that perform the tasks as their name suggests. There are various assembly lines or workers that move the chips from the peeler unit to the shredder and beyond; in our case, we have streams to link and wire in the spout and bolts with each other. Now the basic unit of exchange between the peeler and shredder is a peeled potato, and between the shredder units and roasting units is a sliced potato. This is analogous to a tuple, the datum of information exchange...

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