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Learning Apache Cassandra

You're reading from   Learning Apache Cassandra Managing fault-tolerant, scalable data with high performance

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Product type Paperback
Published in Apr 2017
Publisher
ISBN-13 9781787127296
Length 360 pages
Edition 2nd Edition
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Author (1):
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Sandeep Yarabarla Sandeep Yarabarla
Author Profile Icon Sandeep Yarabarla
Sandeep Yarabarla
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Table of Contents (15) Chapters Close

Preface 1. Getting Up and Running with Cassandra FREE CHAPTER 2. The First Table 3. Organizing Related Data 4. Beyond Key-Value Lookup 5. Establishing Relationships 6. Denormalizing Data for Maximum Performance 7. Expanding Your Data Model 8. Collections, Tuples, and User-Defined Types 9. Aggregating Time-Series Data 10. How Cassandra Distributes Data 11. Cassandra Multi-Node Cluster 12. Application Development Using the Java Driver 13. Peeking under the Hood 14. Authentication and Authorization

Denormalizing Data for Maximum Performance

In the previous chapter, we created a structure that allows a user to follow other users. The goal of the follow system was to allow users to see all of their followed users' status updates in one place, which we'll call the home timeline. In this chapter, we will build a table to store users' home timelines.

The follow structures in Chapter 5, Establishing Relationships, introduced the concept of denormalization, the practice of storing the same piece of data in more than one place in order to optimize read performance. The denormalization we used for follows was fairly mild; however, each follow relationship is stored in exactly two places. For home timelines, we will create a much more aggressively denormalized data structure: a given piece of data will be stored in an arbitrary number of places.

While this highly denormalized structure will be the end...

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