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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

Lightweight transactions and their cost


Lightweight transactions allow us to maintain data integrity in the face of concurrent updates, but they don't do it for free. Because of Cassandra's distributed architecture, it actually goes to great lengths to guarantee that the data is in a certain state before modifying it, as all the machines that store that piece of data need to be in agreement.

Note

Accordingly, there's a performance penalty in using lightweight transactions. As a result, you shouldn't use them in situations where you don't need to.

 

When lightweight transactions aren't necessary

As we discussed earlier, concurrent insertions aren't a concern for any table that uses UUIDs that are generated by the application or by Cassandra at row-creation time. Simply using UUIDs guarantees that we'll never have a row key collision.

Another scenario in which we can skip conditional inserts is when we have a globally unique natural key. For instance, if you're building a Rich Site Summary (RSS...

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