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  • Book Overview & Buying Cassandra High Availability
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Cassandra High Availability

Cassandra High Availability

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

Cassandra High Availability

4.6 (14)
By: Robbie 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
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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
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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
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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

Summary

In this chapter, we discussed some common data modeling patterns to avoid. However, it would be impossible to cover every bad choice a user might make, so it's important to focus on understanding the fundamentals of sound design. This will give you a foundation that will allow you to make correct data modeling decisions on whatever problem you may encounter.

As we have also seen in this chapter, sometimes Cassandra isn't the right tool for the problem at hand. Hopefully, you can now recognize when this is the case, and choose the right tool for the right job.

It is now time to wrap up this book by taking a look at ways in which things can go wrong when running Cassandra. While it is a highly fault-tolerant system, you will rest easy if you know what to do when the unexpected happens.

CONTINUE READING
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Tech Concepts
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Programming languages
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