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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

Summary

Having spent the bulk of this book exploring Cassandra using CQL, we've now peeked under the hood to see how the robust data structures offered by CQL are in fact abstractions upon a much more rudimentary column family data structure. If nothing else, this is an opportunity to appreciate modern technology; as recently as Cassandra 1.1, the CQL data structures we take for granted were unheard of. Before Cassandra 0.7, CQL did not exist at all; the Thrift interface we explored in this chapter was state-of-the-art.

Our deep dive into Cassandra's internal data structures also helps us understand the underlying reasons behind facts that in previous chapters we'd taken as first principles. You learned in Chapter 3, Organizing Related Data that partition keys group related data, but now we know that in fact all the data under a partition key, or RowKey, coexists in a single wide row. Similarly, we...

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