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Cassandra 3.x High Availability

You're reading from   Cassandra 3.x High Availability Achieve scalability and high availability without compromising on performance

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Product type Paperback
Published in Aug 2016
Publisher
ISBN-13 9781786462107
Length 196 pages
Edition 2nd Edition
Languages
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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 (10) Chapters Close

Preface 1. Cassandras 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 Availability 8. Anti-Patterns 9. Failing Gracefully

Tying it all together


In attempting to develop a comprehensive approach to handling failure, we will start by assuming you prefer consistency when possible, but want your application to remain available even if the desired consistency level cannot be satisfied. You are also willing to experience slower client response rather than denying requests.

With these ideas in mind, we can tie the concepts you have learned throughout this chapter together in a policy that answers this demand. Take a look at the following example, which makes use of the previously discussed features:

// defined at class level 
private String localDC = "DC1"; 
private ConsistencyLevel defaultCL =  
 ConsistencyLevel.LOCAL_QUORUM; 
private Cluster cluster; 
 
LoadBalancingPolicy dcPolicy = 
 DCAwareRoundRobinPolicy.builder() 
  .withLocalDc(localDC) 
  .withUsedHostsPerRemoteDc(2) 
  .build(); 
 
// initialized once per application 
cluster = cluster.builder() 
   .addContactPoints("10.10.10.1", "10.10.10.2", "10.10.10...
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