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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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Concepts
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Author (1):
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 Yarabarla Yarabarla
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Yarabarla
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Table of Contents (14) Chapters Close

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

The limits of the WHERE keyword


At this point, we've seen that you can look up rows by partition key alone, or by a combination of a partition key and a clustering column. We can easily imagine other ways to use WHERE, but it's not as flexible as we might hope.

Restricting by clustering column

In Chapter 3, Organizing Related Data, you learned that any row in a table is uniquely identified by the combined values of its primary key columns. However, in the case of user_status_updates, the role of the username column is superfluous for the purposes of uniqueness; since id is a UUID, we know that it alone will uniquely identify the row on its own.

So, can we skip the username partition key and just look up rows by the id clustering column? Let's give it a shot:

SELECT * FROM "user_status_updates"
WHERE id = 3f9b5f00-e8f7-11e3-9211-5f98e903bf02;

This query is a syntactically valid CQL, and the WHERE clause identifies an existing row in the table - specifically, the status update whose body reads...

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