构建高性能Cassandra应用：实战指南与最新CQL深度解析

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《实践Cassandra》(Addison, 2013)是一本面向开发者的实战指南，专为构建提供卓越速度、可扩展性、可靠性和性能的Cassandra系统和应用而设计。该书紧密跟踪最新版本的Cassandra，包括Cassandra Query Language (CQL)的更新，这极大地降低了Cassandra开发者的学习难度，使其更加易于上手。作者Russell Bradberry和Eric Lubow是Cassandra领域的先驱开发者以及Datastax的明星贡献者，他们以丰富的实践经验为基础，带领读者从头到尾构建一个真正适用于生产环境的应用程序。本书涵盖的内容广泛，包括但不限于数据存储（结构化、半结构化和非结构化数据）、查询策略、部署管理、维护、监控以及故障排查等关键环节。书中详细阐述了如何有效地设计和实现Cassandra架构，以便处理海量数据，并通过实例展示如何优化查询性能，提高系统的并发处理能力。同时，对于Cassandra集群的搭建、配置调整、故障转移和性能调优都有深入的讲解，确保读者能够理解和应对实际工作中的挑战。《实践Cassandra》不仅是一本技术手册，也是一本实战手册，它帮助开发者理解Cassandra的核心原理和最佳实践，以便在大规模分布式环境中实现高效的数据处理。无论是初次接触Cassandra的新手还是经验丰富的开发者，都能从中受益匪浅，提升对NoSQL数据库特别是Cassandra的理解和运用能力。此外，书中还提到了版权信息，指出制造商和销售商使用的许多产品名称可能为注册商标，并强调了出版商对可能存在的商标声明的尊重。同时，作者和出版社对书中信息的准确性和完整性不承担任何明确或隐含的保修责任，也不对因使用本书内容或程序所引发的附带或间接损害承担责任。《实践Cassandra》是一本实用的工具书，是Cassandra开发者、数据工程师和架构师不可或缺的参考资料，帮助他们在大数据时代利用Cassandra实现高效且可靠的解决方案。

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Foreword by Paul Dix

Cassandra is quickly becoming one of the backbone components for anyone working

with large datasets and real-time analytics. Its ability to scale horizontally to handle

hundreds of thousands (or millions) of writes per second makes it a great choice for

high-volume systems that must also be highly available. That’s why I’m very pleased that

this book is the first in the series to cover a key infrastructural component for the

Addison-Wesley Data & Analytics Series: the data storage layer.

In 2011, I was making my second foray into working with Cassandra to create a high-

volume, scalable time series data store. At the time, Cassandra 0.8 had been released, and

the path to 1.0 was fairly clear, but the available literature was lagging sorely behind. This

book is exactly what I could have used at the time. It provides a great introduction to

setting up and modeling your data in Cassandra. It has coverage of the most recent features,

including CQL, sets, maps, and lists. However, it doesn’t stop with the introductory stuff.

There’s great material on how to run a cluster in production, how to tune performance,

and on general operational concerns.

I can’t think of more qualified users of Cassandra to bring this material to you. Eric

and Russell are Datastax Cassandra MVPs and have been working extensively with

Cassandra and running it in production for years. Thankfully, they’ve done a great job of

distilling their experience into this book so you won’t have to search for insight into how

to develop against and run the most current release of Cassandra.

—Paul Dix, Series Editor

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Preface

Apache Cassandra is a massively scalable, open-source, NoSQL database. Cassandra is

best suited to applications that need to store large amounts of structured, semistructured,

and unstructured data. Cassandra offers asynchronous masterless replication to nodes in

many data centers. This gives it the capability to have no single point of failure while still

offering low latency operations.

When we first embarked on the journey of writing a book, we had one goal in mind:

We wanted to keep the book easily digestible by someone just getting started with

Cassandra, but also make it a useful reference guide for day-to-day maintenance, tuning,

and troubleshooting. We know the pain of scouring the Internet only to find outdated

and contrived examples of how to get started with a new technology. We hope that

Practical Cassandra will be the go-to guide for developers—both new and at an interme-

diate level—to get up and running with as little friction as possible.

This book describes, in detail, how to go from nothing to a fully functional Cassandra

cluster. It shows how to bring up a cluster of Cassandra servers, choose the appropriate

configuration options for the cluster, model your data, and monitor and troubleshoot any

issues. Toward the end of the book, we provide sample code, in-depth detail as to how

Cassandra works under the covers, and real-world case studies from prominent users.

What’s in This Book?

This book is intended to guide a developer in getting started with Cassandra, from instal-

lation to common maintenance tasks to writing an application. If you are just starting

with Cassandra, this book will be most helpful when read from start to finish. If you are

familiar with Cassandra, you can skip around the chapters to easily find what you need.

Chapter 1, Introduction to Cassandra: This chapter gives an introduction to

Cassandra and the philosophies and history of the project. It provides an overview

of terminology, what Cassandra is best suited for, and, most important what we

hope to accomplish with this book.

Chapter 2, Installation: Chapter 2 is the start-to-finish guide to getting Cassandra

up and running. Whether the installation is on a single node or a large cluster, this

chapter guides you through the process. In addition to cluster setup, the most

important configuration options are outlined.

Chapter 3, Data Modeling: Data modeling is one of the most important aspects of

using Cassandra. Chapter 3 discusses the primary differences between Cassandra

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xviii

Preface

and traditional RDBMSs, as well as going in depth into different design patterns,

philosophies, and special features that make Cassandra the data store of tomorrow.

Chapter 4, CQL: CQL is Cassandra’s answer to SQL. While not a full implementa-

tion of SQL, CQL helps to bridge the gap when transitioning from an RDBMS.

This chapter explores in depth the features of CQL and provides several real-world

examples of how to use it.

Chapter 5, Deployment and Provisioning: After you’ve gotten an overview of instal-

lation and querying, this chapter guides you through real-world deployment and

resource provisioning. Whether you plan on deploying to the cloud or on bare-

metal hardware, this chapter is for you. In addition to outlining provisioning in

various types of configurations, it discusses the impact of the different configuration

options and what is best for different types of workloads.

Chapter 6, Performance Tuning: Now that you have a live production cluster

deployed, this chapter guides you through tweaking the Cassandra dials to get the

most out of your hardware, operating system, and the Java Virtual Machine ( JVM).

Chapter 7, Maintenance: Just as with everything in life, the key to having a perfor-

mant and, more important, working Cassandra cluster is to maintain it properly.

Chapter 7 describes all the different tools that take the headache out of maintaining

the components of your system.

Chapter 8, Monitoring: Any systems administrator will tell you that a healthy sys-

tem is a monitored system. Chapter 8 outlines the different types of monitoring

options, tools, and what to look out for when administering a Cassandra cluster.

Chapter 9, Drivers and Sample Code: Now that you have a firm grasp on how to

manage and maintain your Cassandra cluster, it is time to get your feet wet. In

Chapter 9, we discuss the different drivers and driver features offered in various

languages. We then go for the deep dive by presenting a working example applica-

tion in not only one, but four of the most commonly used languages: Java, C#,

Ruby, and Python.

Chapter 10, Troubleshooting: Now that you have written your sample application,

what happens when something doesn’t quite work right? Chapter 10 outlines the

tools and techniques that can be used to get your application back on the fast track.

Chapter 11, Architecture: Ever wonder what goes on under the Cassandra “hood”?

In this chapter, we discuss how Cassandra works, how it keeps your data safe and

accurate, and how it achieves such blazingly fast performance.

Chapter 12, Case Studies: So who uses Cassandra, and how? Chapter 12 presents

three case studies from forward-thinking companies that use Cassandra in unique

ways. You will get the perspective straight from the mouths of the developers at

Ooyala, Hailo, and eBay.

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