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Cassandra High Availability

You're reading from   Cassandra High Availability Harness the power of Apache Cassandra to build scalable, fault-tolerant, and readily available applications

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Product type Paperback
Published in Dec 2014
Publisher Packt
ISBN-13 9781783989126
Length 186 pages
Edition 1st Edition
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Author (1):
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Robbie Strickland Robbie Strickland
Author Profile Icon Robbie Strickland
Robbie Strickland
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Toc

Table of Contents (11) Chapters Close

Preface 1. Cassandra's Approach to High Availability FREE CHAPTER 2. Data Distribution 3. Replication 4. Data Centers 5. Scaling Out 6. High Availability Features in the Native Java Client 7. Modeling for High Availability 8. Antipatterns 9. Failing Gracefully Index

Consistent hashing

To solve the problem of locating a key in a distributed hash table, we use a technique called consistent hashing. Introduced as a term in 1997, consistent hashing was originally used as a means of routing requests among large numbers of web servers. It's easy to see how the Web can benefit from a hash mechanism that allows any node in the network to efficiently determine the location of an object, in spite of the constant shifting of nodes in and out of the network. This is the fundamental objective of consistent hashing.

The mechanics of consistent hashing

With consistent hashing, the buckets are arranged in a ring with a predefined range; the exact range depends on the partitioner being used. Keys are then hashed to produce a value that lies somewhere along the ring. Nodes are assigned a range, which is computed as follows:

Range start

Range end

Token value

Next token value - 1

Note

The following examples assume that the default Murmur3Partitioner is used. For...

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