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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

Aggregating Time-Series Data

In the preceding chapters, you learned how to use Cassandra as a primary data store for the MyStatus application, with a focus on modeling the data that drives the main user experience on the site. In this chapter, we'll shift focus to another popular use of Cassandra: aggregating data that we observe over time. In particular, we'll build a small analytics component into our schema, which will allow us to keep track of how many times a given status update was viewed on a given day.

In order to do this, we'll introduce a new type of column, the counter column, which is a special numeric column type that can be discretely incremented or decremented. Counter columns have a lot in common with collection columns, which we explored in the previous chapter: you can make discrete changes to them without reading their current value, and they're good for scenarios in which...

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