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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

In this chapter, you learned how to set up a multinode cluster by changing various configuration options. We also took a practical look at how consistency levels work and how Cassandra provides a balance between consistency and availability. We tried out various consistency levels including QUORUM and ANY for writes. We then took a quick look at the architectural aspects of Cassandra.

We looked at the write path, and how data was written to both memory and disk. Data was persisted to commitlog on disk to avoid data loss in case of restarts. Data is flushed to immutable SSTables when the memtables are filled up. The read path utilizes several data structures, both in memory and on disk, to optimize reads. We could enable row and key caching to avoid disk seeks. In case a partition was not found in cache, we would have to hit bloom filters and partition indexes to figure out the location of a partition within...

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