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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

User-defined aggregate functions

Earlier, we created a status_update_views table to keep track of the views on status updates. We also keep track of the origin of these status-update views. They could have originated from a web site, mobile app, or other apps using our API. But to keep track of the count of each type of view, we had to create a separate table with counter columns partitioned by year and clustered by date.

We can also do the same without actually creating a separate table. This can be done using Cassandra's user-defined aggregate functions. You can create custom aggregate functions, which can be applied to data persisting within Cassandra and returned as part of the query result. The coordinator performs aggregation.

Before we proceed with the aggregation, let's populate the status_update_views table with raw data:

    INSERT INTO "status_update_views" ("status_update_username...
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