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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

Handling conflicting data

As we explored earlier, Cassandra's masterless replication can lead to situations in which multiple versions of the same record exist on different nodes. Since there is no master node containing the canonical copy of a record, Cassandra must use other means to determine which version of the data is correct.

This situation comes into play when reading data at any consistency level other than ONE. When our application requests a row from Cassandra, we will receive a response with that row's data; each column will contain one value. However, if we're reading at a consistency level such as QUORUM or ALL, Cassandra internally will fetch the copies of the data from multiple nodes; it's possible that the different copies will contain conflicting data. It's up to Cassandra to figure out exactly what to return to us.

The problem is most acute when different clients are writing...

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