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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
Languages
Concepts
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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

Cassandra Multi-Node Cluster

So far, we have been running a single Cassandra node to store all our data. This isn't how it is ideally supposed to run. This defeats the purpose of Cassandra being a distributed database. As you saw in the previous chapter, every Cassandra node stores a subset of data, which is based on the token range assigned to that node. Multiple nodes will have overlapping token ranges in case the replication factor is higher than 1. In our case, the entire token range resides on the single node that we have been running. To demonstrate the distributed nature of Cassandra and take an in-depth look at whatever concepts we learnt in the previous chapter, we will set up a 3-node cluster and perform various operations.

Setting up a multinode cluster is slightly different from setting up the single-node cluster that we have been using so far. For a single-node cluster, leaving all the configuration...

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