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Cassandra High Availability

Cassandra High Availability

By : Strickland
4.6 (14)
Buy this Book
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Cassandra High Availability

Cassandra High Availability

4.6 (14)
By: Strickland
Buy this Book

Overview of this book

If you are a developer or DevOps engineer who understands the basics of Cassandra and are ready to take your knowledge to the next level, then this book is for you. An understanding of the essentials of Cassandra is needed.
Table of Contents (11 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Cassandra's Approach to High Availability
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1. Cassandra's Approach to High Availability
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ACID
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The monolithic architecture
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The master-slave architecture
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Cassandra's solution
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Cassandra's architecture
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Summary
2
2. Data Distribution
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2. Data Distribution
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Hash table fundamentals
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Consistent hashing
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Token assignment
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Partitioners
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Summary
3
3. Replication
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3. Replication
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The replication factor
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Snitches
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Consistency conflicts
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Balancing the replication factor with consistency
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Summary
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4. Data Centers
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4. Data Centers
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Use cases for multiple data centers
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Data center setup
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Replication across data centers
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Summary
5
5. Scaling Out
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5. Scaling Out
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Choosing the right hardware configuration
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Scaling out versus scaling up
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Growing your cluster
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How to scale out
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How to scale up
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Removing nodes
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Other data migration scenarios
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Snitch changes
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Summary
6
6. High Availability Features in the Native Java Client
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6. High Availability Features in the Native Java Client
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Thrift versus the native protocol
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Setting up the environment
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Connecting to the cluster
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Executing statements
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Handling asynchronous requests
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Load balancing
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Failing over to a remote data center
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Tying it all together
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Summary
7
7. Modeling for High Availability
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7. Modeling for High Availability
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How Cassandra stores data
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Understanding compaction
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CQL under the hood
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Understanding queries
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How collections are stored
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Working with time-series data
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Designing for immutability
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Working with geospatial data
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Summary
8
8. Antipatterns
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8. Antipatterns
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Multikey queries
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Secondary indices
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Distributed joins
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Deleting data
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Unbounded row growth
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Summary
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9. Failing Gracefully
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9. Failing Gracefully
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Knowledge is power
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Logging
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Monitoring node metrics
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When a node goes down
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Backing up data
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Summary
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Index
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Index

How collections are stored

The introduction of collections to CQL addresses some of the concerns that frequently arose regarding Cassandra's primitive data model. They add richer capabilities that give developers more flexibility when modeling certain types of data.

Cassandra supports three collection types: sets, lists, and maps. In this section, we will examine each of these and take a look at how they're stored under the hood. But first, it's important to understand some basic rules regarding collections:

  • The size of each item in a collection must not be more than 64 KB

  • A maximum of 64,000 items may be stored in a single collection

  • Querying a collection always returns the entire collection

  • Collections are best used for relatively small, bounded datasets

With those rules in mind, we can examine each type of collection in detail, starting with sets.

Sets

A set in CQL is very similar to a set in your favorite programming language. It is a unique collection of items. This means that it does not allow...

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