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Cassandra High Availability

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...

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...

What you will learn

Understand the core architecture of Cassandra that enables highly available applications Use replication and tunable consistency levels to balance consistency, availability, and performance Set up multiple data centers to enable failover, load balancing, and geographic distribution Add capacity to your cluster with zero downtime Take advantage of high availability features in the native driver Create data models that scale well and maximize availability Understand how to avoid common antipatterns Keep your system working well even during failure scenarios

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Andreas Baakind Feb 03, 2015

This book is very useful for those who have just started working with Cassandra and wants to avoid the common mistakes that many developers make. It is also a good starting point for those who have a relational database background since it covers the most common pitfalls these developers make. Cassandra may look like a relational database for the very first time, but it acts quite different under the hood. The author has a good way of describing many of the mistakes we make, and how easy it is to do so. He also brings forth the impact on performance from these mistakes.The book also contains simple examples and explanations of how to successfully model for high performance and availability. It uses some of the most known use cases for Cassandra today to illustrate: time series- and geospatial data.Overall I would recommend this book to developer who just started working with Cassandra, and those who are struggling with performance in an already existing cluster. If you do not have any experience with Cassandra beforehand, you will still benefit from reading this book since it will teach you how to do things right and prevent you from making bad decisions later on.

Amazon Verified review

Amazon Shopper Mar 02, 2015

This is the first Cassandra book I can recommend with no reservations. The author has serious hands-on time with Cassandra and it shows in both the level of detail and clarity in describing everything from the big picture down. Including anti-patterns will save new and some experienced Cassandra users a great deal of pain and frustration. A very good book to go along with your first experiences with Apache Cassandra.

Isidhu Dec 02, 2015

Perfect as an introduction to Cassandra. Helped streamline the process from dev to production.

Fabricio Suarte Apr 24, 2015

Very good book. I found information in that book that I had not found in the internet. The author is very experienced about Cassandra.

giacomo benelli Apr 20, 2015

This is a great book, it gets straight to the point and gives you lots of insights about real use cases. I suggest to approach this book after having read the available documentation, in particular the one available on Datastax web site. Don't get me wrong, a total beginner would still benefit from this book, but it's the kind of read where every sentence counts and fundamental concept are present but not repeated over and over. To get the full implications of many concepts, you probably need to have already heard or dealt with them.Also, even though the title is about high availability, a good amount of time is spent on other related concepts such as performance, application design, example of data center design...If you plan to ever use Cassandra seriously, get this book and you will have a solid foundation to get started.

Cassandra High Availability: Harness the power of Apache Cassandra to build scalable, fault-tolerant, and readily available applications

What do you get with Print?

Cassandra High Availability

Chapter 2. Data Distribution

Hash table fundamentals

Consistent hashing

The mechanics of consistent hashing

Note

Token assignment

Manually assigned tokens

Partitioners

Summary

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