HBase实战指南：大数据技术详解

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《HBase in Action》是一本专为大数据研究者和开发者精心撰写的实战指南，由Nick Dimiduk和Amandeep Khurana共同编写，旨在帮助读者深入了解HBase这一强大的分布式数据库系统。HBase是Apache Hadoop生态系统中的一个关键组件，它提供了高吞吐量、实时的数据存储和查询能力，特别适合于大规模、复杂的数据处理场景，如社交媒体分析、日志管理等。本书封面由Michael Stack撰写序言，他可能是一位在大数据领域有着深厚影响力的专家，对HBase的应用和价值给出了独到见解。作为Manning出版社的作品，它遵循了严格的版权规定，强调了所有内容未经出版商许可不得复制或传播的重要性。 Manning Publications是一家专注于技术书籍的公司，其 Shelter Island 地址和联系方式提供给了读者在线获取更多图书信息以及批量订购的途径。同时，出版社还提醒读者，许多产品名称可能被制造商或销售商注册为商标，并提醒在引用时保持尊重。本书的技术编辑是Mark Henry Ryan，他的工作可能包括审阅内容的准确性和一致性，确保技术细节的专业性。Manning强调版权保护，反映了他们对原创作品的尊重和维护，同时也保护了作者和出版商的权益。《HBase in Action》的内容涵盖了HBase的核心概念、安装与配置、数据模型、表设计、数据操作、查询优化、集群管理和故障恢复等方面，深入浅出地介绍了如何在实际项目中有效地利用HBase处理大规模数据。通过丰富的实例和案例，读者不仅能掌握理论知识，还能提升实际操作技能。对于那些正在探索大数据世界的工程师和分析师来说，这本书是一份不可或缺的参考资料，可以帮助他们在处理海量数据时更高效、更稳定地构建和管理分布式数据库系统。通过阅读这本书，读者可以了解到HBase如何适应不断变化的大数据环境，以及如何利用其特性应对不断增长的数据挑战。

preface

I got my start with HBase in the fall of 2008. It was a young project then, released only

in the preceding year. As early releases go, it was quite capable, although not without its

fair share of embarrassing warts. Not bad for an Apache subproject with fewer than 10

active committers to its name! That was the height of the No

SQL hype. The term NoSQL

hadn’t even been presented yet but would come into common parlance over the next

year. No one could articulate why the idea was important—only that it was important—

and everyone in the open source data community was obsessed with this concept. The

community was polarized, with people either bashing relational databases for their fool-

ish rigidity or mocking these new technologies for their lack of sophistication.

The people exploring this new idea were mostly in internet companies, and I came

to work for such a company—a startup interested in the analysis of social media con-

tent. Facebook still enforced its privacy policies then, and Twitter wasn’t big enough to

know what a Fail Whale was yet. Our interest at the time was mostly in blogs. I left a

company where I’d spent the better part of three years working on a hierarchical data-

base engine. We made extensive use of Berkeley

DB, so I was familiar with data tech-

nologies that didn’t have a SQL engine. I joined a small team tasked with building a

new data-management platform. We had an MS SQL database stuffed to the gills with

blog posts and comments. When our daily analysis jobs breached the 18-hour mark,

we knew the current system’s days were numbered.

After cataloging a basic set of requirements, we set out to find a new data technol-

ogy. We were a small team and spent months evaluating different options while main-

taining current systems. We experimented with different approaches and learned

PREFACE

xvi

firsthand the pains of manually partitioning data. We studied the CAP theorem and

eventual consistency—and the tradeoffs. Despite its warts, we decided on HBase, and

we convinced our manager that the potential benefits outweighed the risks he saw in

open source technology.

I’d played a bit with Hadoop at home but had never written a real MapReduce job.

I’d heard of

HBase but wasn’t particularly interested in it until I was in this new posi-

tion. With the clock ticking, there was nothing to do but jump in. We scrounged up a

couple of spare machines and a bit of rack, and then we were off and running. It was a

NET shop, and we had no operational help, so we learned to combine bash with rsync

and managed the cluster ourselves.

I joined the mailing lists and the

IRC channel and started asking questions. Around

this time, I met Amandeep. He was working on his master’s thesis, hacking up HBase

to run on systems other than Hadoop. Soon he finished school, joined Amazon, and

moved to Seattle. We were among the very few HBase-ers in this extremely Microsoft-

centric city. Fast-forward another two years…

The idea of

HBase in Action was first proposed to us in the fall of 2010. From my

perspective, the project was laughable. Why should we, two community members,

write a book about

HBase? Internally, it’s a complex beast. The Definitive Guide was still

a work in progress, but we both knew its author, a committer, and were well aware of

the challenge before him. From the outside, I thought it’s just a “simple key-value

store.” The

API has only five concepts, none of which is complex. We weren’t going to

write another internals book, and I wasn’t convinced there was enough going on from

the application developer’s perspective to justify an entire book.

We started brainstorming the project, and it quickly became clear that I was wrong.

Not only was there enough material for a user’s guide, but our position as community

members made us ideal candidates to write such a book. We set out to catalogue the

useful bits of knowledge we’d each accumulated over the couple of years we’d used

the technology. That effort—this book—is the distillation of our eight years of com-

bined

HBase experience. It’s targeted to those brand new to HBase, and it provides

guidance over the stumbling blocks we encountered during our own journeys. We’ve

collected and codified as much as we could of the tribal knowledge floating around

the community. Wherever possible, we prefer concrete direction to vague advice. Far

more than a simple

FAQ, we hope you’ll find this book to be a complete manual to

getting off the ground with HBase.

HBase is now stabilizing. Most of the warts we encountered when we began with the

project have been cleaned up, patched, or completely re-architected. HBase is

approaching its 1.0 release, and we’re proud to be part of this community as we

approach this milestone. We’re proud to present this manuscript to the community in

hopes that it will encourage and enable the next generation of HBase users. The sin-

gle strongest component of

HBase is its thriving community—we hope you’ll join us in

that community and help it continue to innovate in this new era of data systems.

NICK DIMIDUK

PREFACE

xvii

If you’re reading this, you’re presumably interested in knowing how I got involved

with HBase. Let me start by saying thank you for choosing this book as your means to

learn about HBase and how to build applications that use HBase as their underlying

storage system. I hope you’ll find the text useful and learn some neat tricks that will

help you build better applications and enable you to succeed.

I was pursuing graduate studies in computer science at

UC Santa Cruz, specializing

in distributed systems, when I started working at Cisco as a part-time researcher. The

team I was working with was trying to build a data-integration framework that could

integrate, index, and allow exploration of data residing in hundreds of heterogeneous

data stores, including but not limited to large

RDBMS systems. We started looking for

systems and solutions that would help us solve the problems at hand. We evaluated

many different systems, from object databases to graph databases, and we considered

building a custom distributed data-storage layer backed by Berkeley

DB. It was clear

that one of the key requirements was scalability, and we didn’t want to build a full-

fledged distributed system. If you’re in a situation where you think you need to build

out a custom distributed database or file system, think again—try to see if an existing

solution can solve part of your problem.

Following that principle, we decided that building out a new system wasn’t the best

approach and to use an existing technology instead. That was when I started playing

with the Hadoop ecosystem, getting my hands dirty with the different components in

the stack and going on to build a proof-of-concept for the data-integration system on

top of

HBase. It actually worked and scaled well! HBase was well-suited to the problem,

but these were young projects at the time—and one of the things that ensured our

success was the community.

HBase has one of the most welcoming and vibrant open

source communities; it was much smaller at the time, but the key principles were the

same then as now.

The data-integration project later became my master’s thesis. The project used

HBase at its core, and I became more involved with the community as I built it out. I

asked questions, and, with time, answered questions others asked, on both the mailing

lists and the

IRC channel. This is when I met Nick and got to know what he was work-

ing on. With each day that I worked on this project, my interest and love for the tech-

nology and the open source community grew, and I wanted to stay involved.

After finishing grad school, I joined Amazon in Seattle to work on back-end distrib-

uted systems projects. Much of my time was spent with the Elastic MapReduce team,

building the first versions of their hosted

HBase offering. Nick also lived in Seattle,

and we met often and talked about the projects we were working on. Toward the end

of 2010, the idea of writing HBase in Action for Manning came up. We initially scoffed

at the thought of writing a book on

HBase, and I remember saying to Nick, “It’s gets,

puts, and scans—there’s not a lot more to HBase from the client side. Do you want to

write a book about three API calls?”

But the more we thought about this, the more we realized that building applications

with

HBase was challenging and there wasn’t enough material to help people get off the

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