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Learning Apache Cassandra

You're reading from   Learning Apache Cassandra Build an efficient, scalable, fault-tolerant, and highly-available data layer into your application using Cassandra

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Product type Paperback
Published in Feb 2015
Publisher
ISBN-13 9781783989201
Length 246 pages
Edition 1st Edition
Languages
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Author (1):
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Matthew Brown Matthew Brown
Author Profile Icon Matthew Brown
Matthew Brown
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Toc

Table of Contents (14) Chapters Close

Preface 1. Getting Up and Running with Cassandra 2. The First Table FREE CHAPTER 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 A. Peeking Under the Hood B. Authentication and Authorization Index

Recording analytics observations

At this point, we've explored structuring both discrete and aggregate analytics data, and looked at accessing that data. However, to have interesting data aggregates to access, we first need to record our observations.

Updating a counter column

The daily_status_update_views table introduces a new type of column: the counter column. Counter columns store integer values, just like int and bigint columns; however, unlike a normal data column, counter columns are always incremented or decremented, rather than having a value set directly.

We've currently got two tables to store usage data: status_update_views to store raw view observations, and daily_status_update_views to store views by day. We'd like to record that one of alice's status updates was viewed on the web on October 5, 2014 at 3:12 P.M. EDT:

INSERT INTO "status_update_views" (
  "status_update_username", "status_update_id",
  "observed_at",...
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