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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

Summary

In this chapter, we explored three different approaches to displaying a user's home timeline. The first approach had the advantage of requiring no additional tables in our database; it was fully normalized. The downside was that reading all the data to display a user's home timeline was prohibitively expensive. The next approach, partial denormalization, kept references to the status updates in each user's home timeline and allowed us to avoid the worst performance characteristics of the normalized approach. Partial denormalization did not, however, allow us to get to the point where a home timeline could be displayed with only a single query to a single partition.

By storing a full copy of every status update in the home timeline of every follower of the update's author—a fully denormalized approach—we achieved the ideal read-time access pattern, namely selecting a slice...

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