Back in 2007, Twitter users experienced the fail whale, occasionally captioned with "Too many tweets...". On August 3, 2013, Twitter posted a new record of high tweets rate of 143,199 per second, and we rarely see the fail whale. Many things changed since 2007. People and things connected to the Internet have increased exponentially. Cloud computing and hardware on demand has become cheap and easily available. Distributed computing and the NoSQL paradigm has taken off with a plethora of freely available, robust, proven, and open source projects to store large data sets and then process and visualize the data. Big data has become a cliché. With massive amounts of data that get generated at a very high speed via people or machines, our capability to store and analyze the data has increased. Cassandra is one of the most successful data stores that scales linearly, is easy to deploy and manage, and is blazing fast.
This book is about Cassandra and its ecosystem. The aim of this book is to take you through the basics of Apache Cassandra to understand what goes on under the hood. The book has three broad goals: the first is to help you to make the right design decisions and understand the patterns and anti-patterns, the second is to enable you to manage infrastructure and rainy days, and the third is to introduce you to some of the tools that work with Cassandra to monitor and manage Cassandra and to analyze the big data that you have inside it.
The book does not take a purist approach, rather a practical one. You will come to know proprietary tools, GitHub projects, shell scripts, third-party monitoring tools, and enough references to go beyond this book and dive deeper if you want.
Chapter 1, Quick Start, is about getting excited and gaining instant gratification. If you have no prior experience with Cassandra, you leave this chapter with enough information to get yourself started on the next big project.
Chapter 2, Cassandra Architecture, covers design decisions and Cassandra's internal plumbing. If you have never worked with a distributed system, this chapter has a lot of useful distributed design concepts. This chapter will be helpful for the rest of the book when we look at patterns and infrastructure management. It will also help you to understand the discussion of the Cassandra mailing list and JIRA. It is a theoretical chapter; you may skip it and come back later.
Chapter 3, Design Patterns, discusses various design decisions and their pros and cons. You will learn about Cassandra limitations and capabilities. If you are planning to write a program that uses Cassandra, this is the chapter for you. Do not miss Chapter 9, Introduction to CQL 3 and Cassandra 1.2 for CQL.
Chapter 4, Deploying a Cluster, is a full chapter about how to deploy a cluster correctly. Once you have gone through the chapter, you will realize it is not really hard to deploy a cluster. It is probably one of the simplest distributed systems.
Chapter 5, Performance Tuning, explains how to get the most out of the hardware the cluster is deployed on. Usually you will not need to rotate lots of knobs and the default is just fine.
Chapter 6, Managing a Cluster, is about the daily DevOps drills. For example, scaling up a cluster, shrinking it down, replacing a dead node, and balancing the data load across the cluster.
Chapter 7, Monitoring, talks about the various tools that you can use to monitor Cassandra. If you already have a monitoring system, you would probably want to plug Cassandra health monitoring to it, or you may choose to use dedicated Cassandra monitoring tools.
Chapter 8, Integration, Shows how to integrate Cassandra with other tools. Cassandra is about large data sets, fast writes, and reads terabytes of data. What is the use of data if you can't analyze it? Cassandra can be smoothly integrated with various Hadoop projects, and integrating with tools such as Spark and Twitter Storm is just as easy. This chapter gives you an introduction to get you started with setting up Cassandra and Hadoop setup.
Chapter 9, Introduction to CQL 3 and Cassandra 1.2, fills the version gap. At the time of writing this book, Cassandra's latest version was 1.1.11. The complete book uses that version and the Thrift API to connect to Cassandra. Cassandra 1.2 was released later and Cassandra 2.0 is also expected to be released anytime now. CQL 3 is the preferred way to query Cassandra, and Cassandra 1.2 has some interesting upgrades.
If you have any development experience, this book should be easy to follow. A beginner level knowledge of Unix commands, Python, and some Java is good to speed up the understanding, but they are not absolute requirements.
In terms of software and hardware, a machine with 1 GB RAM and a dual core processor is the minimum requirement. For all practical purposes, any modern machine (your laptop from 2007 or newer) is good. You should have the following software installed: Python, Java development kit 6 (JDK), Cassandra 1.1.x, and Hadoop 1.1.x. The examples in this book are done in Ubuntu 11.10/13.04 and CentOS 5.5. So, if you have a Linux/Unix/OS X machine, that would be hugely beneficial. You may need to look for a Windows equivalent if it is your environment.
This book is for anyone who is curious about Cassandra. A beginner can start from Chapter 1, Quick Start, and learn all the way up to advanced topics. If you have an intermediate level of experience, that is, you have worked on a toy project or better with Cassandra, you may skip to Chapter 2, Cassandra Architecture.
A DevOps engineer is probably the best job title who needs to read the book end to end. If you wear multiple hats during the day (very common in startups)—writing code, managing infrastructure, working on analytics, and evangelizing your product— you may find this book extremely useful.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text are shown as follows: "Fire up your shell and type in $CASSANDRA_HOME/bin/cassandra -f."
A block of code is set as follows:
[default@unknown] USE crud; Authenticated to keyspace: crud [default@crud] CREATE COLUMN FAMILY test_cf ... WITH ... DEFAULT_VALIDATION_CLASS = UTF8Type AND ... KEY_VALIDATION_CLASS = LongType AND ... COMPARATOR = UTF8Type;
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
[default@unknown] USE crud; Authenticated to keyspace: crud [default@crud] CREATE COLUMN FAMILY test_cf ... WITH ... DEFAULT_VALIDATION_CLASS = UTF8Type AND ... KEY_VALIDATION_CLASS = LongType AND ... COMPARATOR = UTF8Type;
New terms and important words are shown in bold.
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