Cassandra is a fantastic data store and certainly well suited as the foundation of a highly available system. In fact, it was built just for such a purpose: to handle Facebook’s messaging service. But it hasn’t always been so easy to use, with its early Thrift interface and unfamiliar data model causing many potential users to pause—and in many cases for a good reason.
Fortunately, Cassandra has matured substantially over the last few years. I used to advise people only to use Cassandra if nothing else would do the job because the learning curve was quite steep. Version 3.x continues this trend, with the introduction of features such as materialized views and SASI indexes. These additions reduce developer workload and significantly increase the overall utility of the system.
The flip side is that each new feature further obscures the underlying data structure, making complex operations seem straightforward. The familiarity of a SQL-like interface can lure an unsuspecting new user into dangerous traps. The moral of this story is that it’s still not a relational database, and you still need to know what it’s doing under the hood.
And imparting that knowledge is the core objective of this book. Each chapter attempts to demystify the inner workings of Cassandra so that you’re no longer working blindly against a black box data store. You will learn to configure, design, and build your system based on a fundamentally solid foundation.
The good news is that Cassandra makes the task of building massively scalable and incredibly reliable systems relatively straightforward, presuming you understand how to partner with it to achieve these goals.
Since you are reading this book, I presume you are either already using Cassandra or planning to do so, and that you’re interested in building a highly available system on top of it. If so, I am confident that you will meet with success if you follow the principles and guidelines offered in the chapters that follow.
Chapter 1, Cassandra’s Approach to High Availability, is an introduction to concepts related to system availability and the problems that have been encountered historically when trying to make data stores highly available. The chapter outlines Cassandra’s solutions to these problems.
Chapter 2, Data Distribution, outlines the core mechanisms that underlie Cassandra’s distributed hash table model, including consistent hashing and partitioner implementations.
Chapter 3, Replication, offers an in-depth look at the data replication architecture used in Cassandra, with a focus on the relationship between consistency levels and replication factor.
Chapter 4, Data Centers, provides you with a thorough understanding of Cassandra’s robust data center replication capabilities, including deployment on EC2 and building separate clusters for analysis using Hadoop or Spark.
Chapter 5, Scaling Out, is a discussion of the tools, processes, and general guidance needed to properly increase the size of your cluster.
Chapter 6, High Availability Features in the Native Java Client, covers the new native Java driver and its availability-related features. We’ll discuss node discovery, cluster-aware load balancing, automatic failover, and other important concepts.
Chapter 7, Modeling for Availability, discusses the important concepts readers need to understand when modeling highly available data in Cassandra. CQL, keys, wide rows, and denormalization are among the topics that will be covered.
Chapter 8, Anti-Patterns, complements the data modeling chapter by presenting a set of common anti-patterns that proliferate among inexperienced Cassandra developers. Some patterns include queues, joins, high delete volumes, and high-cardinality secondary indexes, among others.
Chapter 9, Failing Gracefully, helps you understand how to deal with the various failure cases, as failure in a large distributed system is inevitable. We’ll examine a number of possible failure scenarios, how to detect them, and how to resolve them.
This book assumes you have access to a running Cassandra installation that is at least as new as release 3.0. Some features discussed will apply only to 3.8 or newer, and we will point these out when that applies. Users of versions older than 3.0 can still gain a lot from the content, but there will be some portions that do not directly translate to those versions.
For Chapter 6, High Availability Features in the Native Java Client coverage of the Java driver, you will need the Java Development Kit 1.8 and a suitable text editor to write Java code. All command line examples assume a Linux environment, through translation to a Windows environment should be straightforward for those users.
This book is for developers and system administrators who are interested in building an advanced understanding of Cassandra’s internals for the purpose of deploying high-availability services, using it as a backing data store. This is not an introduction to Cassandra, so those who are completely new would be well served to find a suitable tutorial before diving into this book.
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."
A block of code is set as follows:
CREATE KEYSPACE AddressBook
WITH REPLICATION = {
‘class’ : ‘SimpleStrategy’,
‘replication_factor’ : 3
};Any command-line input or output is written as follows:
# nodetool status
New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "click on the Connect button."
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