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Learning Apache Cassandra - Second Edition

You're reading from  Learning Apache Cassandra - Second Edition

Product type Book
Published in Apr 2017
Publisher
ISBN-13 9781787127296
Pages 360 pages
Edition 2nd Edition
Languages
Concepts

Table of Contents (14) Chapters

1. Getting Up and Running with Cassandra 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 limitations of collections


As we saw, collection columns are a useful and versatile feature of CQL. In fact, we might suppose that collections would be a good way to model data we've modeled in other ways in previous chapters. For instance, why not model a user's status updates as a list of text values in the users table?

As it turns out, collection columns do have some limitations that circumscribe the cases in which they're the best solution. We'll explore the major limitations now.

Reading discrete values from collections

The most powerful feature of CQL collections is the ability to write discrete values to a collection. It's possible to append a single value to a list, update a single key-value pair in a map, remove a specific value from a set, and so on.

At read time, however, there is no special support for reading discrete values. For instance, we might want to be able to do something like the following to read a specific element from a list column:

SELECT "shared_by"[2] 
FROM "user_status_updates...
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