logging in or signing up p11 cristian duda Miguel Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 91 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: October 25, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Predicate-Based Indexing of Enterprise Web Applications: Predicate-Based Indexing of Enterprise Web Applications Cristian Duda, David Graf, Donald Kossmann ETH ZurichEnterprise Search: Possible Approaches: Enterprise Search: Possible Approaches “Do It Yourself” (e.g., SAP, Oracle) + App vendors know the semantics of their application - Everybody impements their own search engine - Cross Application Search is difficult “Google for Web Applications” (generic ESE) + generic (for all applications) + enables cross-application search - need to teach the semantics of the app to the search engine - nobody knows how to do it Enterprise Search: Current Status: Enterprise Search: Current Status Enterprise Application Search: Enterprise Application Search Enteprise Application Search: Enteprise Application Search JSP file Database Property file title.english=PetStore XML Message <item part=“1”> <name>Snake</name> <quantity>1</quantity> <USPrice>60.30</USPrice> </item> Data User View SAP, ...Enterprise Search Engine (ESE): Enterprise Search Engine (ESE) Challenges: 1. Userview assembled in a non-trivial way (not WYSIWYG) 2. References to Web Pages are complex: URL function parameters context (workflow, security) This is not Google! 1. Google is WYSIWYG 2. Google references are simple URIs This is not Hidden Web! 1. The app developer collaborates and teaches the semantics of the app to the ESE 2. The ESE has full access to all data sourcesEnterprise Search Engine:: Enterprise Search Engine: Rules and Patterns a handful of patterns are enough to describe the mapping from raw view to user view declaratively (semi-automatic) Crawl the data sources (automatic) Normalize the data (automatic) Predicate-based indexing (automatic) Predicate-based query processing (automatic) Predicate-based Index: Predicate-based IndexDemo!: Demo! Indexing Query Processing Result Generation Use Case: Sun’s Java Pet Store Application The Application: The Application JSP Application developed by Sun Uses Dynamic JSP Pages + Database Sun uses it to showcase the capabilities of their J2EE platformIndexing (using our GUI): Indexing (using our GUI) JSP Files Rules from app. developer Index location Indexed filesQuery Processing (using our GUI): Query Processing (using our GUI) The queried Index Query Results (URL+additional info)Result presentation: Result presentation Dbl click on query result Web page (user view) is displayed in browser. 1 2 Query: java iguanaResult presentation: Result presentation java iguana Query: Only appears in the JSP file Only appears in the database Our ESE understood the combination between the two data sources ! The ESE combined the two data sources just as the application would have doneSomething funny: Something funny The application also has a search functionality, but…Something funny: Something funny No Results! The application’s search box is broken Details:: Details: http://www.dbis.ethz.ch/research/current_projects/appdata Contacts: You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
p11 cristian duda Miguel Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 91 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: October 25, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Predicate-Based Indexing of Enterprise Web Applications: Predicate-Based Indexing of Enterprise Web Applications Cristian Duda, David Graf, Donald Kossmann ETH ZurichEnterprise Search: Possible Approaches: Enterprise Search: Possible Approaches “Do It Yourself” (e.g., SAP, Oracle) + App vendors know the semantics of their application - Everybody impements their own search engine - Cross Application Search is difficult “Google for Web Applications” (generic ESE) + generic (for all applications) + enables cross-application search - need to teach the semantics of the app to the search engine - nobody knows how to do it Enterprise Search: Current Status: Enterprise Search: Current Status Enterprise Application Search: Enterprise Application Search Enteprise Application Search: Enteprise Application Search JSP file Database Property file title.english=PetStore XML Message <item part=“1”> <name>Snake</name> <quantity>1</quantity> <USPrice>60.30</USPrice> </item> Data User View SAP, ...Enterprise Search Engine (ESE): Enterprise Search Engine (ESE) Challenges: 1. Userview assembled in a non-trivial way (not WYSIWYG) 2. References to Web Pages are complex: URL function parameters context (workflow, security) This is not Google! 1. Google is WYSIWYG 2. Google references are simple URIs This is not Hidden Web! 1. The app developer collaborates and teaches the semantics of the app to the ESE 2. The ESE has full access to all data sourcesEnterprise Search Engine:: Enterprise Search Engine: Rules and Patterns a handful of patterns are enough to describe the mapping from raw view to user view declaratively (semi-automatic) Crawl the data sources (automatic) Normalize the data (automatic) Predicate-based indexing (automatic) Predicate-based query processing (automatic) Predicate-based Index: Predicate-based IndexDemo!: Demo! Indexing Query Processing Result Generation Use Case: Sun’s Java Pet Store Application The Application: The Application JSP Application developed by Sun Uses Dynamic JSP Pages + Database Sun uses it to showcase the capabilities of their J2EE platformIndexing (using our GUI): Indexing (using our GUI) JSP Files Rules from app. developer Index location Indexed filesQuery Processing (using our GUI): Query Processing (using our GUI) The queried Index Query Results (URL+additional info)Result presentation: Result presentation Dbl click on query result Web page (user view) is displayed in browser. 1 2 Query: java iguanaResult presentation: Result presentation java iguana Query: Only appears in the JSP file Only appears in the database Our ESE understood the combination between the two data sources ! The ESE combined the two data sources just as the application would have doneSomething funny: Something funny The application also has a search functionality, but…Something funny: Something funny No Results! The application’s search box is broken Details:: Details: http://www.dbis.ethz.ch/research/current_projects/appdata Contacts: