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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

Beyond two columns


We've now seen a table with two columns in its primary key: a partition key and a clustering column. As it turns out, neither of these roles is limited to a single column. A table can define one or more partition key columns and zero or more clustering columns.

Multiple clustering columns

Clustering columns are not limited to one field as specified before. Let's take a look at how multiple clustering columns work and facilitate data ordering. To illustrate this, we will recreate our status updates table so that it is clustered by the date and time when the user updated their status:

CREATE TABLE "user_status_updates_by_datetime" ( 
  "username" text, 
  "status_date" date, 
  "status_time" time, 
  "body" text, 
  PRIMARY KEY ("username", "status_date", "status_time") 
);

We have created a new table user_status_updates_by_datetime as shown next:

  • Partition key: username, which is a text field.
  • Clustering columns: status_date and status_time. Rows for a particular username are...
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