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Learning Apache Cassandra

You're reading from   Learning Apache Cassandra Build an efficient, scalable, fault-tolerant, and highly-available data layer into your application using Cassandra

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Product type Paperback
Published in Feb 2015
Publisher
ISBN-13 9781783989201
Length 246 pages
Edition 1st Edition
Languages
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Author (1):
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Matthew Brown Matthew Brown
Author Profile Icon Matthew Brown
Matthew Brown
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Toc

Table of Contents (14) 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 A. Peeking Under the Hood B. Authentication and Authorization Index

Distributed deletion


When we want to delete data from storage, we might assume that Cassandra simply removes the data from disk and forgets that it ever existed. In a non-distributed environment, this approach to deletion would be entirely sufficient, but deletion is a bit more complex in a distributed database like Cassandra. To find out why, let's return to, and modify, our previous scenario with Heather and Charles making concurrent modifications to HappyCorp's user record.

In our modified scenario, Heather will still be updating the location column to contain New York, but Charles will be attempting to delete the contents of that column altogether. As with the original scenario, they'll be making their respective changes at roughly the same time, and our application will issue the UPDATE and DELETE queries at the ONE consistency level. Consider the following sequence of events:

  1. Heather issues a request to update the location value to New York; this is acknowledged by Replica 1.

  2. Charles...

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