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Web Data Management PDF

451 Pages·2011·7 MB·English
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R M A “This book combines the unique strengths of the authors to create a beautiful coverage of the interplay iga an bit Web Data bmeatnwaegeenm tehnet .u Int dise rdlyeisntgin deede tpo tbheecoormy, ep trhaec taicuathl oarligtaortiivthem sso,u racned f osro tfhtwisa troep tico oflosr isnt uudseen ttso daanyd fporra Wcteitbio dnaetras ux olesc ebou u l alike.” S R – Susan B. Davidson, University of Pennsylvania e o n u e s lla se Management “Web data management is a broad field, and this text manages to cover it all while tying the material r t t together brilliantly, conveying it as a single field rather than just a collection of independent topics. It suc- ceeds in explaining both theory and practice – a difficult task that you do not often see accomplished in any W field of computer science. It is a unique book that fills a pressing need.” – Michael Benedikt, University of Oxford e The Internet and World Wide Web have revolutionized access to information. Users now store information across b multiple platforms from personal computers, to smartphones, to Web sites such as YouTube and Picasa. As a consequence, data management concepts, methods, and techniques are increasingly focused on distribution con- D cerns. That information largely resides in the network, as do the tools that process this information. a This book explains the foundations of XML, the Web standard for data management, with a focus on data distribution. t It covers the many facets of distributed data management on the Web, such as description logics, that are already a emerging in today’s data integration applications and herald tomorrow’s semantic Web. It also introduces the ma- chinery used to manipulate the unprecedented amount of data collected on the Web. Several “Putting into Practice” M chapters describe detailed practical applications of the technologies and techniques. Striking a balance between the conceptual and the practical, the book will serve as an introduction to the new global a information systems for Web professionals as well as for master’s level courses. n Serge Abiteboul is a researcher at INRIA Saclay and ENS Cachan and cofounder of the start-up Xyleme. His previous books include the textbook Foundations of Databases. a g Ioana Manolescu is a researcher at INRIA Saclay, and the scientific leader of the LEO team, joint between INRIA and University Paris XI. e M Philippe Rigaux is a Professor of Computer Science at the Conservatoire National des Arts et Métiers. He has co-authored six books, including Spatial Databases. e Marie-Christine Rousset is a Professor of Computer Science at the University of Grenoble. n Pierre Senellart is an Associate Professor in the DBWeb team at Télécom ParisTech, the leading French engineering t school specializing in information technology. Serge Abiteboul, Ioana Manolescu, Philippe Rigaux, Marie-Christine Rousset, Pierre Senellart Cover image: © kalachakra / Photocase Cover design by David Levy Web Data Management TheInternet and World WideWeb have revolutionized access to infor- mation. Users now store information across multiple platforms from personalcomputers,tosmartphones,toWebsitessuchasYouTubeand Picasa. As a consequence, data management concepts, methods, and techniquesareincreasinglyfocusedondistributionconcerns.Thatinfor- mation largely resides in the network, as do the tools that process this information. This book explains the foundations of XML, the Web standard for data management, with afocus on data distribution. Itcovers the many facets of distributed data management on the Web, such as description logics, thatarealreadyemergingintoday’sdataintegrationapplications and herald tomorrow’s semantic Web. It also introduces the machinery used to manipulate the unprecedented amount of data collected on the Web.Several“PuttingintoPractice”chaptersdescribedetailedpractical applicationsofthetechnologiesandtechniques. Strikingabalancebetweentheconceptualandthepractical,thebook will serve as an introduction to the new global information systems for Webprofessionalsaswellasformaster’slevelcourses. Serge Abiteboul is a researcher at INRIA Saclay and ENS Cachan and cofounder of the start-up Xyleme. His previous books include the textbookFoundationsofDatabases. Ioana Manolescu is a researcher at INRIA Saclay, and the scientific leaderoftheLEOteam,jointbetweenINRIAandUniversityParisXI. PhilippeRigauxisaProfessorofComputerScienceattheConservatoire National des Arts et Métiers. He has coauthored six books, including SpatialDatabases(2001). Marie-Christine Rousset is a Professor of Computer Science at the UniversityofGrenoble. Pierre Senellart is an Associate Professor in the DBWeb team at Télé- com ParisTech, the leading French engineering school specializing in informationtechnology. Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE i — #1 Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE ii — #2 WEB DATA MANAGEMENT Serge Abiteboul ˆ INRIASaclay–Ile-de-France Ioana Manolescu ˆ INRIASaclay–Ile-de-France Philippe Rigaux CNAM, France Marie-Christine Rousset Universityof Grenoble,France Pierre Senellart TélécomParisTech,France Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE iii — #3 CAMBRIDGE UNIVERSITY PRESS Cambridge,NewYork,Melbourne,Madrid,CapeTown, Singapore,SãoPaulo,Delhi,Tokyo,MexicoCity CambridgeUniversityPress 32AvenueoftheAmericas,NewYork,NY10013-2473,USA www.cambridge.org Informationonthistitle:www.cambridge.org/9781107012431 ©SergeAbiteboul,IoanaManolescu,PhilippeRigaux, Marie-ChristineRousset,andPierreSenellart2012 Thispublicationisincopyright.Subjecttostatutoryexception andtotheprovisionsofrelevantcollectivelicensingagreements, noreproductionofanypartmaytakeplacewithoutthewritten permissionofCambridgeUniversityPress. Firstpublished2012 PrintedintheUnitedStatesofAmerica AcatalogrecordforthispublicationisavailablefromtheBritishLibrary. LibraryofCongressCataloginginPublicationData Webdatamanagement/SergeAbiteboul...[etal.]. p. cm. Includesbibliographicalreferencesandindex. ISBN978-1-107-01243-1(hardback) 1. Webdatabases. 2. Databasemanagement. 3. Electroniccommerce. I. Abiteboul,S.(Serge) QA76.9.W43.W41542011 005.7402854678–dc23 2011037996 ISBN978-1-107-01243-1Hardback Additionalresourcesforthispublicationathttp://webdam.inria.fr/Jorge/ Cambridge University Press has no responsibility for the persistence or accuracy of URLsforexternalorthird-partyInternetWebsitesreferredtointhispublicationand does not guarantee that any content on such Web sites is, or will remain, accurate orappropriate. Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE iv — #4 Contents Introduction pageix Part 1 Modeling Web Data 1 Data Model 3 1.1 SemistructuredData 3 1.2 XML 5 1.3 WebDataManagementwithXML 16 1.4 TheXMLWorld 18 1.5 FurtherReading 28 1.6 Exercises 29 2 XPath and XQuery 32 2.1 Introduction 32 2.2 Basics 32 2.3 XPath 42 2.4 FLWORExpressionsinXQuery 54 2.5 XPathFoundations 62 2.6 FurtherReading 67 2.7 Exercises 69 3 Typing 72 3.1 MotivatingTyping 72 3.2 Automata 75 3.3 SchemaLanguagesforXML 80 3.4 TypingGraphData 89 3.5 FurtherReading 91 3.6 Exercises 92 v Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE v — #5 vi Contents 4 XML Query Evaluation 95 4.1 FragmentingXMLDocumentsonDisk 97 4.2 XMLNodeIdentifiers 99 4.3 XMLQueryEvaluationTechniques 103 4.4 FurtherReading 112 4.5 Exercises 113 5 Putting into Practice: Managing an XML Database with EXIST 116 5.1 Prerequisites 116 5.2 InstallingEXIST 117 5.3 GettingStartedwithEXIST 118 5.4 RunningXPathandXQueryQuerieswiththeSandbox 120 5.5 ProgrammingwithEXIST 123 5.6 Projects 127 6 Putting into Practice: Tree Pattern Evaluation Using SAX 131 6.1 Tree-PatternDialects 131 6.2 CTPEvaluation 134 6.3 ExtensionstoRicherTreePatterns 138 Part 2 Web Data Semantics and Integration 7 Ontologies, RDF, and OWL 143 7.1 Introduction 143 7.2 OntologiesbyExample 145 7.3 RDF,RDFS,andOWL 148 7.4 Ontologiesand(Description)Logics 159 7.5 FurtherReading 169 7.6 Exercises 170 8 Querying Data Through Ontologies 171 8.1 Introduction 171 8.2 QueryingRDFData:NotationandSemantics 172 8.3 QueryingThroughRDFSOntologies 176 8.4 AnsweringQueriesThroughDL-LITEOntologies 179 8.5 FurtherReading 194 8.6 Exercises 195 9 Data Integration 196 9.1 Introduction 196 9.2 ContainmentofConjunctiveQueries 199 9.3 Global-as-ViewMediation 200 9.4 Local-as-ViewMediation 204 9.5 Ontology-BasedMediators 215 9.6 Peer-to-PeerDataManagementSystems 222 9.7 FurtherReading 229 9.8 Exercises 229 Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE vi — #6 Contents vii 10 Putting into Practice: Wrappers and Data Extraction with XSLT 231 10.1 ExtractingDatafromWebPages 232 10.2 RestructuringData 234 11 Putting into Practice: Ontologies in Practice (by Fabian M. Suchanek) 236 11.1 ExploringandInstallingYago 236 11.2 QueryingYago 237 11.3 WebAccesstoOntologies 238 12 Putting into Practice: Mashups with YAHOO! PIPES and XProc 240 12.1 YAHOO!PIPES:AGraphicalMashupEditor 240 12.2 XProc:AnXMLPipelineLanguage 241 Part 3 Building Web Scale Applications 13 Web Search 247 13.1 TheWorldWideWeb 248 13.2 ParsingtheWeb 250 13.3 WebInformationRetrieval 257 13.4 WebGraphMining 272 13.5 HotTopicsinWebSearch 280 13.6 FurtherReading 281 13.7 Exercises 283 14 An Introduction to Distributed Systems 287 14.1 BasicsofDistributedSystems 288 14.2 FailureManagement 295 14.3 RequiredPropertiesofaDistributedSystem 299 14.4 ParticularitiesofP2PNetworks 303 14.5 CaseStudy:ADistributedFileSystemforVeryLargeFiles 305 14.6 FurtherReading 308 15 Distributed Access Structures 310 15.1 Hash-BasedStructures 311 15.2 DistributedIndexing:SearchTrees 325 15.3 FurtherReading 336 15.4 Exercises 337 16 Distributed Computing with MAPREDUCE and PIG 339 16.1 MAPREDUCE 341 16.2 PIG 348 16.3 FurtherReading 359 16.4 Exercises 361 Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE vii — #7 viii Contents 17 Putting into Practice: Full-Text Indexing with LUCENE (by Nicolas Travers) 364 17.1 Preliminary:ALUCENESandbox 364 17.2 IndexingPlainTextwithLUCENE–AFullExample 364 17.3 PutItintoPractice! 371 17.4 LUCENE–TuningtheScoring(Project) 372 18 Putting into Practice: Recommendation Methodologies (by Alban Galland) 374 18.1 IntroductiontoRecommendationSystems 374 18.2 Prerequisites 375 18.3 DataAnalysis 377 18.4 GeneratingSomeRecommendations 380 18.5 Projects 385 19 Putting into Practice: Large-Scale Data Management with HADOOP 387 19.1 InstallingandRunningHADOOP 388 19.2 RunningMAPREDUCEJobs 391 19.3 PIGLATINScripts 395 19.4 RunninginClusterMode(Optional) 395 19.5 Exercises 397 20 Putting into Practice: COUCHDB, a JSON Semistructured Database 400 20.1 IntroductiontotheCOUCHDBDocumentDatabase 401 20.2 PuttingCOUCHDBintoPractice! 417 20.3 FurtherReading 419 Bibliography 421 Index 431 Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE viii — #8 Introduction The Internet and the Web have revolutionized access to information. Individuals are depending more and more on the Web to find or publish information, down- load music and movies, and interact with friends in social networking Web sites. Following a paralleltrend, companiesgomore andmore towardWebsolutions in theirdailyactivitybyusing Webservices(e.g., agenda)aswellasbymovingsome applications into the cloud (e.g., with Amazon Web services). The growth of this immense information source is witnessed by the number of newly connected peo- ple,bytheinteractionsamongthemfacilitatedbythesocialnetworkingplatforms, and above all by the huge amount of data covering all aspects of human activity. WiththeWeb,informationhasmovedfromdataisolatedinveryprotectedislands (typically relational databases) to information freely available to any machine or anyindividualconnectedtotheInternet. Perhaps the best illustration comes from a typical modern Web user. She has informationstoredonPCs,apersonallaptop,andaprofessionalcomputer,butalso possiblyonsomeserveratwork,onhersmartphone,inane-book,andsoon.Also, she maintains information in personal Web sites or social network Web sites. She maystore picturesinPicasa, moviesinYouTube, bookmarks inFirefoxSync, and the like. So, even an individual is now facing the management of a complex dis- tributedcollectionofdata.Onadifferentscale,publicorprivateorganizationsalso havetodealwithinformationproducedandstoredindifferentplaces,orcollected ontheWeb,eitherasasideeffectoftheiractivity(e.g.,worldwidee-commerceor auctionsites)orbecausetheydirectlyattempttounderstand,organizeandanalyze datacollectedontheWeb(e.g.,searchengines,digitallibraries,orWebintelligence companies). Asaconsequence,amajortrendintheevolutionofdatamanagementconcepts, methods, and techniques is their increasing focus on distribution concerns: Since information now mostly resides in the network, so do the tools that process this information to make sense of it. Consider for instance the management of inter- nalreportsinacompany.Typically,manycollectionsofreportsmaybemaintained in different local branches. To offer a unique company-wide query access to the ix Abiteboul: “Prelims” — 2011/10/28 — 14:16 — PAGE ix — #9

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