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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
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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
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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

Chapter 2. Data Distribution

Cassandra's peer-to-peer architecture and scalability characteristics are directly tied to its data placement scheme. Cassandra employs a distributed hash table data structure that allows data to be stored and retrieved by a key quickly and efficiently. Consistent hashing is the core of this strategy as it enables all nodes to understand where data exists in the cluster without complicated coordination mechanisms.

In this chapter, we'll cover the following topics:

  • The fundamentals of distributed hash tables
  • Cassandra's consistent hashing mechanism
  • Token assignment, both manual and using virtual nodes (vnodes)
  • The implications of Cassandra's partitioner implementations
  • Formation of hotspots in the cluster

By the time you finish this chapter, you should have a deep understanding of these concepts. Let's begin with some basics about hash tables in general, and then we can delve deeper into Cassandra's distributed hash table implementation...

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