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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

Fully denormalizing the home timeline

The partially denormalized structure we built using the home_status_update_ids table certainly improves read-time performance, but we're still not at the sweet spot of querying exactly one partition to display the home timeline. In order to do this, we'll need to take the denormalization one step further.

Instead of storing references to status updates in the home timeline, we'll store actual copies of the status updates. Each user's timeline will contain its own copy of the status updates of all the users they follow. We create the following table:

CREATE TABLE "home_status_updates" ( 
"timeline_username" text,
"status_update_id" timeuuid,
"status_update_username" text,
"body" text,
PRIMARY KEY ("timeline_username", "status_update_id")
) WITH CLUSTERING ORDER BY ("status_update_id...
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