Tài liệu Solr 1.4 Enterprise Search Server- P1 pptx

Solr 1.4 Enterprise
Search Server
Enhance your search with faceted navigation, result
highlighting, fuzzy queries, ranked scoring, and more
David Smiley
Eric Pugh

BIRMINGHAM - MUMBAI
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Solr 1.4 Enterprise Search Server
Copyright © 2009 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval
system, or transmitted in any form or by any means, without the prior written
permission of the publisher, except in the case of brief quotations embedded in
critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy
of the information presented. However, the information contained in this book is
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Publishing, and its dealers and distributors will be held liable for any damages
caused or alleged to be caused directly or indirectly by this book.
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companies and products mentioned in this book by the appropriate use of capitals.
However, Packt Publishing cannot guarantee the accuracy of this information.
First published: August 2009
Production Reference: 1120809
Published by Packt Publishing Ltd.
32 Lincoln Road
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Birmingham, B27 6PA, UK.
ISBN 978-1-847195-88-3

www.packtpub.com
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Credits
Authors
David Smiley
Eric Pugh
Reviewers
James Brady
Jerome Eteve
Acquisition Editor
Rashmi Phadnis
Development Editor
Darshana Shinde
Technical Editor
Pallavi Kachare
Copy Editor
Leonard D'Silva
Indexer
Monica Ajmera
Production Editorial Manager
Abhijeet Deobhakta
Editorial Team Leader
Akshara Aware
Project Team Leader
Priya Mukherji
Project Coordinator

Leena Purkait
Proofreader
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Production Coordinator
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Cover Work
Shantanu Zagade
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About the Authors
Born to code,
David Smiley
is a senior software developer and loves
programming. He has 10 years of experience in the defense industry at MITRE,
using Java and various web technologies. David is a strong believer in the
opensource development model and has made small contributions to various
projects over the years.
David began using Lucene way back in 2000 during its infancy and was immediately
excited by it and its future potential. He later went on to use the Lucene based
"Compass" library to construct a very basic search server, similar in spirit to Solr.
Since then, David has used Solr in a major search project and was able to contribute
modications back to the Solr community. Although preferring open source
solutions, David has also been trained on the commercial Endeca search platform
and is currently using that product as well as Solr for different projects.
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Most, if not all, authors seem to dedicate their book to someone. As
simply a reader of books, I have thought of this seeming prerequisite
as customary tradition. That was my feeling before I embarked on
writing about Solr, a project that has sapped my previously "free"

time on nights and weekends for a year. I chose this sacrice and
would not change it, but my wife, family, and friends did not choose
it. I am married to my lovely wife Sylvie who has sacriced easily
as much as I have to complete this book. She has suffered through
this time with an absentee husband while bearing our rst child—
Camille. She was born about a week before the completion of my
rst draft and has been the apple of my eye ever since. I ofcially
dedicate this book to my wife Sylvie and my daughter Camille,
whom I both lovingly adore. I also pledge to read book
dedications with newfound rsthand experience at what
the dedication represents.

I would also like to thank others who helped bring this book to
fruition. Namely, if it were not for Doug Cutting creating Lucene
with an open source license, there would be no Solr. Furthermore,
CNet's decision to open source what was an in-house project, Solr
itself in 2006, deserves praise. Many corporations do not understand
that open source isn't just "free code" you get for free that others
wrote; it is an opportunity to let your code ourish on the outside
instead of it withering inside. Finally, I thank the team at Packt who
were particularly patient with me as a rst-time author writing at a
pace that left a lot to be desired.

Last but not least, this book would not have been completed in a
reasonable time were it not for the assistance of my contributing
author, Eric Pugh. His perspectives and experiences have
complemented mine so well that I am absolutely certain the
quality of this book is much better than what I could have
done alone.

Thank you all.
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Fascinated by the 'craft' of software development,
Eric Pugh
has been heavily
involved in the open source world as a developer, committer, and user for the
past ve years. He is an emeritus member of the Apache Software Foundation
and lately has been mulling over how we move from the read/write Web to the
read/write/share Web.
In biotech, nancial services, and defense IT, he has helped European and
American companies develop coherent strategies for embracing open source
software. As a speaker, he has advocated the advantages of Agile practices in
software development.
Eric became involved with Solr when he submitted the patch SOLR-284 for Parsing
Rich Document types such as PDF and MS Ofce formats that became the single
most popular patch as measured by votes! The patch was subsequently cleaned
up and enhanced by three other individuals, demonstrating the power of the
open source model to build great code collaboratively. SOLR-284 was eventually
refactored into Solr Cell as part of Solr version 1.4.
He blogs at
/>.
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Throughout my life I have been helped by so many people, but all
too rarely do I get to explicitly thank them. This book is arguable
one of the high points of my career, and as I wrote it, I thought about
all the people who have provided encouragement, mentoring, and
the occasional push to succeed. First off, I would like to thank Erik
Hatcher, author, entrepreneur, and great family man for introducing

me to the world of open source software. My rst hesitant patch
to Ant was made under his tutelage, and later my interest in Solr
was fanned by his advocacy. Thanks to Harry Sleeper for taking
a chance on a rst time conference speaker; he moved me from
thinking of myself as a developer improving myself to thinking of
myself as a consultant improving the world (of software!). His team
at MITRE are some of the most passionate developers I have met,
and it was through them I met my co-author David. I owe a huge
debt of gratitude to David Smiley. He has encouraged me, coached
me, and put up with my lack of respect for book deadlines, making
this book project a very positive experience! I look forward to the
next one. With my new son Morgan at home, I could only have done
this project with a generous support of time from my company,
OpenSource Connections. I am incredibly proud of what o19s
is accomplishing!

Lastly, to the all the folks in the Solr/Lucene community who took
the time to review early drafts and provide feedback: Solr is at the
tipping point of becoming the "it" search engine because of your
passion and commitment

I am who I am because of my wife, Kate. Schweetie, real life for me
began when we met. Thank you.
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About the Reviewers
James Brady
is an entrepreneur and software developer living in San Francisco,
CA. Originally from England, James discovered his passion for computer science and
programming while at Cambridge University. Upon graduation, James worked as a

software engineer at IBM's Hursley Park laboratory—a role which taught him many
things, most importantly, his desire to work in a small company.
In January 2008, James founded WebMynd Corp., which received angel funding
from the Y Combinator fund, and he relocated to San Francisco. WebMynd is one
of the largest installations of Solr, indexing up to two million HTML documents
per day, and making heavy use of Solr's multicore features to enable a partially
active index.
Jerome Eteve
holds a BSC in physics, maths and computing and an MSC in IT
and bioinformatics from the University of Lille (France). After starting his career in
the eld of bioinformatics, where he worked as a biological data management and
analysis consultant, he's now a senior web developer with interests ranging from
database level issues to user experience online. He's passionate about open source
technologies, search engines, and web application architecture. At present, he is
working since 2006 for Careerjet Ltd, a worldwide job search engine.
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Table of Contents
Preface 1
Chapter 1: Quick Starting Solr 7
An introduction to Solr 7
Lucene, the underlying engine 8
Solr, the Server-ization of Lucene 8
Comparison to database technology 9
Getting started 10
The last official release or fresh code from source control 11
Testing and building Solr 12
Solr's installation directory structure 13
Solr's home directory 15
How Solr finds its home 15

Deploying and running Solr 17
A quick tour of Solr! 18
Loading sample data 20
A simple query 22
Some statistics 24
The schema and configuration files 25
Solr resources outside this book 26
Summary 27
Chapter 2: Schema and Text Analysis 29
MusicBrainz.org 30
One combined index or multiple indices 31
Problems with using a single combined index 33
Schema design 34
Step 1: Determine which searches are going to be powered by Solr 35
Step 2: Determine the entities returned from each search 35
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Table of Contents
[
ii
]
Step 3: Denormalize related data 36
Denormalizing—"one-to-one" associated data 36
Denormalizing—"one-to-many" associated data 36
Step 4: (Optional) Omit the inclusion of fields
only used in search results 38
The schema.xml file 39
Field types 40
Field options 40
Field definitions 42

Sorting 44
Dynamic fields 45
Using copyField 46
Remaining schema.xml settings 47
Text analysis 47
Configuration 48
Experimenting with text analysis 50
Tokenization 52
WorkDelimiterFilterFactory 53
Stemming 54
Synonyms 55
Index-time versus Query-time, and to expand or not 57
Stop words 57
Phonetic sounds-like analysis 58
Partial/Substring indexing 60
N-gramming costs 61
Miscellaneous analyzers 62
Summary 63
Chapter 3: Indexing Data 65
Communicating with Solr 65
Direct HTTP or a convenient client API 65
Data streamed remotely or from Solr's filesystem 66
Data formats 66
Using curl to interact with Solr 66
Remote streaming 68
Sending XML to Solr 69
Deleting documents 70
Commit, optimize, and rollback 70
Sending CSV to Solr 72
Configuration options 73

Direct database and XML import 74
Getting started with DIH 75
The DIH development console 76
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Table of Contents
[
iii
]
DIH documents, entities 78
DIH fields and transformers 79
Importing with DIH 80
Indexing documents with Solr Cell 81
Extracting binary content 81
Configuring
Solr 83
Extracting karaoke lyrics 83
Indexing richer documents 85
Summary 88
Chapter 4: Basic Searching 89
Your first search, a walk-through 89
Solr's generic XML structured data representation 92
Solr's XML response format 93
Parsing the URL 94
Query parameters 95
Parameters affecting the query 95
Result paging 96
Output related parameters 96
Diagnostic query parameters 98
Query syntax 99

Matching all the documents 99
Mandatory, prohibited, and optional clauses 99
Boolean operators 100
Sub-expressions (aka sub-queries) 101
Limitations of prohibited clauses in sub-expressions 102
Field qualifier 102
Phrase queries and term proximity 103
Wildcard queries 103
Fuzzy queries 105
Range queries 105
Date math 106
Score boosting 107
Existence (and non-existence) queries 107
Escaping special characters 108
Filtering 108
Sorting 109
Request handlers 110
Scoring 112
Query-time and index-time boosting 113
Troubleshooting scoring 113
Summary 115
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Table of Contents
[
iv
]
Chapter 5: Enhanced Searching 117
Function queries 117
An example: Scores influenced by a lookupcount 118

Field references 120
Function reference 120
Mathematical primitives 121
Miscellaneous math 121
ord and rord 122
An example with scale() and lookupcount 123
Using logarithms 123
Using inverse reciprocals 124
Using reciprocals and rord with dates 126
Function query tips 128
Dismax Solr request handler 128
Lucene's DisjunctionMaxQuery 130
Configuring queried fields and boosts 131
Limited query syntax 131
Boosting: Automatic phrase boosting 132
Configuring automatic phrase boosting 133
Phrase slop configuration 134
Boosting: Boost queries 134
Boosting: Boost functions 137
Min-should-match 138
Basic rules 139
Multiple rules 139
What to choose 140
A default search 140
Faceting 141
A quick example: Faceting release types 142
MusicBrainz schema changes 144
Field requirements 146
Types of faceting 146
Faceting text 147

Alphabetic range bucketing (A-C, D-F, and so on) 148
Faceting dates 149
Date facet parameters 151
Faceting on arbitrary queries 152
Excluding filters 153
The solution: Local Params 155
Facet prefixing (term suggest) 156
Summary 158
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Table of Contents
[
v
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Chapter 6: Search Components 159
About components 159
The highlighting component 161
A highlighting example 161
Highlighting configuration 163
Query elevation 166
Configuration 167
Spell checking 169
Schema configuration 169
Configuration in solrconfig.xml 171
Configuring spellcheckers (dictionaries) 173
Processing of the q parameter 175
Processing of the spellcheck.q parameter 176
Building the dictionary from its source 176
Issuing spellcheck requests 177
Example usage for a mispelled query 178

An alternative approach 180
The more-like-this search component 182
Configuration parameters 183
Parameters specific to the MLT search component 183
Parameters specific to the MLT request handler 184
Common MLT parameters 185
MLT results example 186
Stats component 189
Configuring the stats component 189
Statistics on track durations 190
Field collapsing 191
Configuring field collapsing 192
Other components 193
Terms component 194
termVector component 194
LocalSolr component 194
Summary 195
Chapter 7: Deployment 197
Implementation methodology 197
Questions to ask 198
Installing into a Servlet container 199
Differences between Servlet containers 199
Defining solr.home property 199
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Table of Contents
[
vi
]
Logging 201

HTTP server request access logs 201
Solr application logging 203
Configuring logging output 203
Logging to Log4j 204
Jetty startup integration 205
Managing log levels at runtime 205
A SearchHandler per search interface 207
Solr cores 208
Configuring solr.xml 208
Managing cores 209
Why use multicore 210
JMX 212
Starting Solr with JMX 212
Take a walk on the wild side! Use JRuby to extract JMX information 215
Securing Solr 217
Limiting server access 217
Controlling JMX access 220
Securing index data 220
Controlling document access 221
Other things to look at 221
Summary 222
Chapter 8: Integrating Solr 223
Structure of included examples 223
Inventory of examples 224
SolrJ: Simple Java interface 224
Using Heritrix to download artist pages 226
Indexing HTML in Solr 227
SolrJ client API 230
Indexing POJOs 234
When should I use Embedded Solr 235

In-Process streaming 236
Rich clients 237
Upgrading from legacy Lucene 237
Using JavaScript to integrate Solr 238
Wait, what about security? 239
Building a Solr powered artists autocomplete widget with
jQuery and JSONP 240
SolrJS: JavaScript interface to Solr 245
Accessing Solr from PHP applications 247
solr-php-client 248
Drupal options 250
Apache Solr Search integration module 251
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Table of Contents
[
vii
]
Hosted Solr by Acquia 252
Ruby on Rails integrations 253
acts_as_solr 254
Setting up MyFaves project 255
Populating MyFaves relational database from Solr 256
Build Solr indexes from relational database 258
Complete MyFaves web site 260
Blacklight OPAC 263
Indexing MusicBrainz data 263
Customizing display 267
solr-ruby versus rsolr 269
Summary 270

Chapter 9: Scaling Solr 271
Tuning complex systems 271
Using Amazon EC2 to practice tuning 273
Firing up Solr on Amazon EC2 274
Optimizing a single Solr server (Scale High) 276
JVM configuration 277
HTTP caching 277
Solr caching 280
Tuning caches 281
Schema design considerations 282
Indexing strategies 283
Disable unique document checking 285
Commit/optimize factors 285
Enhancing faceting performance 286
Using term vectors 286
Improving phrase search performance 287
The solution: Shingling 287
Moving to multiple Solr servers (Scale Wide) 289
Script versus Java replication 289
Starting multiple Solr servers 290
Configuring replication 291
Distributing searches across slaves 291
Indexing into the master server 292
Configuring slaves 292
Distributing search queries across slaves 293
Sharding indexes 295
Assigning documents to shards 296
Searching across shards 297
Combining replication and sharding (Scale Deep) 298
Summary 300

Index 301
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Preface
Text search has been around for perhaps longer than we all can remember. Just
about all systems, from client installed software to web sites to the web itself, have
search. Yet there is a big difference between the best search experiences and the
mediocre, unmemorable ones. If you want the application you're building to stand
out above the rest, then it's got to have great search features. If you leave this to the
capabilities of a database, then it's near impossible that you're going to get a great
search experience, because it's not going to have features that users come to expect in
a great search. With Solr, the leading open source search server, you'll tap into a host
of features from highlighting search results to spell-checking to faceting.
As you read Solr Enterprise Search Server you'll be guided through all of the aspects
of Solr, from the initial download to eventual deployment and performance
optimization. Nearly all the options of Solr are listed and described here, thus making
this book a resource to turn to as you implement your Solr based solution. The book
contains code examples in several programming languages that explore various
integration options, such as implementing query auto-complete in a web browser
and integrating a web crawler. You'll nd these working examples in the online
supplement to the book along with a large, real-world, openly available data set from
MusicBrainz.org
. Furthermore, you will also nd instructions on accessing a Solr
image readily deployed from within Amazon's Elastic Compute Cloud.
Solr Enterprise Search Server targets the Solr 1.4 version. However, as this book went
to print prior to Solr 1.4's release, two features were not incorporated into the book:
search result clustering and trie-range numeric elds.
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Preface
[
2
]
What this book covers
Chapter 1, Quick Starting Solr introduces Solr to the reader as a middle ground
between database technology and document/web crawlers. The reader is guided
through the Solr distribution including running the sample conguration with
sample data.
Chapter 2, The Schema and Text Analysis is all about Solr's schema. The schema
design is an important rst order of business along with the related text
analysis conguration.
Chapter 3, Indexing Data details several methods to import data; most of them can
be used to bring the MusicBrainz data set into the index. A popular Solr extension
called the DataImportHandler is demonstrated too.
Chapter 4, Basic Searching is a thorough reference to Solr's query syntax from the
basics to range queries. Factors inuencing Solr's scoring algorithm are explained
here, as well as diagnostic output essential to understanding how the query worked
and how a score is computed.
Chapter 5, Enhanced Searching moves on to more querying topics. Various score
boosting methods are explained from those based on record-level data to those that
match particular elds or those that contain certain words. Next, faceting is a major
subject area of this chapter. Finally, the term auto-complete is demonstrated, which
is implemented by the faceting mechanism.
Chapter 6, Search Components covers a variety of searching extras in the form of
Solr "components", namely, spell-check suggestions, highlighting search results,
computing statistics of numeric elds, editorial alterations to specic user queries,
and nding other records "more like this".
Chapter 7, Deployment transits from running Solr from a developer-centric perspective

to deploying and running Solr as a deployed production enterprise service that is
secure, has robust logging, and can be managed by System Administrators.
Chapter 8, Integrating Solr surveys a plethora of integration options for Solr, from
supported client libraries in Java, JavaScript, and Ruby, to being able to consume Solr
results in XML, JSON, and even PHP syntaxes. We'll look at some best practices and
approaches for integrating Solr into your web application.
Chapter 9, Scaling Solr looks at how to scale Solr up and out to avoid meltdown and
meet performance expectations. This information varies from small changes of
conguration les to architectural options.
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Preface
[
3
]
Who this book is for
This book is for developers who would like to use Solr to implement a search
capability for their applications. You need only to have basic programming skills to
use Solr; extending or modifying Solr itself requires Java programming. Knowledge
of Lucene, the foundation of Solr, is certainly a bonus.
Conventions
In this book, you will nd 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: "These are essentially defaults for searches
that are processed by Solr request handlers dened in
solrconfig.xml
."
A block of code is set as follows:
<uniqueKey>id</uniqueKey>

<!-- <defaultSearchField>text</defaultSearchField>
<solrQueryParser defaultOperator="AND"/> -->
<copyField source="r_name" dest="r_name_sort" />
When we wish to draw your attention to a particular part of a code block, the
relevant lines or items are set in bold:
<arr name="id">
<str>mccm.pdf</str>
</arr>
Any command-line input or output is written as follows:
>> curl http://localhost:8983/solr/karaoke/update/ -H "Content-Type:
text/xml" --data-binary '<commit waitFlush="false"/>'
New terms and important words are shown in bold. Words that you see on the
screen, in menus or dialog boxes for example, appear in the text like this: "Take for
example the Top Voters section ".
Warnings or important notes appear in a box like this.
Tips and tricks appear like this.
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Preface
[
4
]
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