HBase实战解析：Nick Dimiduk与Amandeep Khurana合著 - CSDN文库

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"HBase 实战 - HBase in Action" 《HBase 实战》是一本深入探讨分布式列式数据库HBase的专业书籍，由Nick Dimiduk和Amandeep Khurana合著，并由Mark Henry Ryan担任技术编辑。本书是Manning出版社出版的一部作品，旨在帮助读者理解和应用HBase解决大数据存储和处理的问题。 HBase是建立在Apache Hadoop之上的开源NoSQL数据库，设计用于处理大规模数据集。这本书主要面向那些对HBase感兴趣的开发者、架构师以及数据科学家，无论他们是有经验的HBase用户还是初学者。通过本书，读者将了解到HBase的核心概念、设计原理以及实际操作中的最佳实践。书中的内容可能包括但不限于以下几个方面： 1. **HBase概述**：介绍HBase的基本架构，包括Region服务器、HMaster、ZooKeeper等组件的作用，以及HBase如何在分布式环境中运行。 2. **数据模型**：深入解析HBase的数据模型，包括行、列族、列限定符和时间戳的概念，以及它们如何协同工作来提供高效的数据存储和检索。 3. **数据存储与索引**：讨论HBase的数据文件格式（HFile）、BlockCache和MemStore，以及如何构建和优化索引来提升查询性能。 4. **读写操作**：介绍Put、Get、Scan等基本操作，以及如何使用过滤器进行复杂查询。同时，还会讨论数据的版本控制和生命周期管理。 5. **集群管理**：涵盖HBase集群的部署、监控和调优，包括Region划分和自动分割，以及如何处理故障恢复。 6. **应用程序开发**：提供Java API和HBase Shell的使用示例，帮助开发者更好地集成HBase到他们的应用中。 7. **高级主题**：探讨HBase与其他Hadoop组件（如HDFS、MapReduce、Hive）的集成，以及与Spark、Storm等实时处理框架的配合。 8. **案例研究**：通过实际应用场景，展示如何利用HBase解决大数据问题，如日志分析、实时监控和互联网广告投放等。 9. **未来展望**：介绍HBase的最新发展和未来趋势，以及如何跟上社区的更新和技术演进。通过阅读《HBase 实战》，读者不仅可以掌握HBase的基本用法，还能了解到如何在实际项目中设计和优化HBase解决方案，从而在大数据领域建立起坚实的基础。这本书对于任何想要深入理解HBase并利用其处理海量数据的个人或团队来说，都是一份宝贵的参考资料。

xv

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

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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

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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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