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As an eSI Visiting Researcher

As an eSI Visiting Researcher. Beth Plale Computer Science Dept. Indiana University. Background. Involved in GGF since early ‘GF’ days Relational Grid Information System research group (RGIS-RG) chair (inception-Jan 2003) Systems researcher distributed systems, and

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As an eSI Visiting Researcher

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  1. As an eSI Visiting Researcher Beth Plale Computer Science Dept. Indiana University

  2. Background • Involved in GGF since early ‘GF’ days • Relational Grid Information System research group (RGIS-RG) chair (inception-Jan 2003) • Systems researcher • distributed systems, and • experimental evaluation • Main research thread is data streams

  3. Attraction of eSI • UK respected in grid community for expertise in databases • My research crosses systems and databases • Opportunity to work with OGSA-DAI PIs, OGSA-DAI development team, and GGF DAIS WG leaders • Took opportunity to develop scheme for handling stream queries within DAIS framework

  4. Stream systems span range of functionality • Data manipulation • systems • processing large • amounts of data • Stream monitoring • systems • identifying unusual • behavior size and number of stream chunks analyzed overlap • Stream routing • systems • event delivery timeliness demands on response

  5. Stream systems: events arrive and queries long standing (not vice versa) queries added through user interface long-standing queries Results multicast to owners of satisfied queries stock quote stream Each arriving event matched against set of queries

  6. DAIS model applied to traditional database queries pushed into external data source OGSA- DAI Data Service transport mechanism (could be pub/sub system) request Data Source (e.g., RDBMS) Rowset Data Service Instance Rowset Data Service Instance Rowset Data Service Instance response

  7. DAIS model applied to data stream source Queries pushed into external data resource OGSA- DAI Data Service Long running queries distributed, virtual data source streamed response Rowset Data Service

  8. http://lead.ou.edu

  9. LEAD Data Cloud

  10. dQUOB queries dQUOB queries dQUOB queries dQUOB SQL compiler Data stream architecture: DAIS and dQUOB WRF model WRF model WRF weather forecasting model subquery scripts query request Rich query operator support in external resources Data Service Result stream stream Rowset Data Service stream

  11. Positive Outcomes • Relationships (!) • Increased understanding on both sides • Scheme for how to handle stream queries in DAIS framework • LEAD project leverages OGSA-DAI

  12. Ongoing and Future Collaboration • Instrumentation of OGSA-DAI • RGRbench • Leverage OGSA-DAI in LEAD • Provide feedback on our experiences • Use • development • Future visits (both directions) • International funding barrier?

  13. Beth Plale plale@cs.indiana.edu http://www.cs.indiana.edu/~plale

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