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Aurora: a new model and architecture for data stream management

Aurora: a new model and architecture for data stream management. Daniel J. Abadi 1 , Don Carney 2 , Ugur Cetintemel 2 , Mitch Cherniack 1 , Christian Convey 2 , Sangdon Lee 2 , Michael Stonebraker 3 , Nesime Tatbul 2 , Stan Zdonik 2. 1 Department of Computer Science, Brandeis University

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Aurora: a new model and architecture for data stream management

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  1. Aurora: a new model and architecture for data stream management Daniel J. Abadi1, Don Carney2, Ugur Cetintemel2, Mitch Cherniack1, Christian Convey2, Sangdon Lee2, Michael Stonebraker3, Nesime Tatbul2, Stan Zdonik2 1 Department of Computer Science, Brandeis University 2 Department of Computer Science, Brown University 3 Department of EECS and Laboratory of Computer Science, M.I.T. Presenter: Saurin Kadakia

  2. ABOUT ME • MS CS STUDENT • GRADUATING IN DEC 08 • INTERESTED IN DATABASES AND WEB TECHNOLOGY

  3. WHAT ARE MONITORING APPLICATIONS?? • MONITORING APPLICATIONS ARE APPLICATIONS THAT MONITOR CONTINUOUS STREAMS OF DATA. EXAMPLES?? • MILITARY APPLICATIONS • FINANCIAL ANALYSIS APPLICATIONS • TRACKING APPLICATIONS

  4. TRADITIONAL DBMS ASSUMPTIONS • HUMAN ACTIVE, DBMS PASSIVE MODEL • ONLY CURRENT VALUE IMPORTANT • TRIGGERS/ASSERTIONS ARE SECONDARY • QUERIES MUST HAVE EXACT ANSWERS • NO REAL TIME SERVICE REQUIREMENTS

  5. REALITY FOR MONITORING APPLICATIONS • DBMS ACTIVE, HUMAN PASSIVE MODEL • HISTORY OF VALUES REQUIRED • TRIGGER ORIENTED APPLICATIONS • APPROXIMATE ANSWERS TO QUERIES • REAL TIME REQUIREMENTS

  6. Query spec QoS spec User application SYSTEM MODEL Historical Storage Aurora System External data source Continuous & ad hoc queries Operator boxes data flow Application administrator

  7. QUERY MODEL • Traditional • Structured Query Language • Declarative query on static data • Aurora • Data flow model for data stream • Application manager will construct queries using GUI • Stream Query Algebra • Queries are processed by SQuAl operators on the data stream • Some of the operators are filter, map, union, aggregate, join bsort, resample.

  8. QoS spec QoS spec QoS spec AURORA QUERY MODEL app data input b1 b2 b3 continuous query Connection point b4 b5 b6 view ad-hoc query app b7 b8 b9

  9. AURORA QoS GRAPH TYPES

  10. OPTIMIZATION Aggregate Join Map Filter pull data Hold Union Continuous query Filter Hold Ad hoc query Filter BSort Map Static storage Aggregate Join

  11. OPTIMIZATION • Dynamic continuous query optimization • Inserting projections • Combining boxes • Reordering boxes

  12. Q1 Q2 Qm Q1 Q2 Qn AURORA RUNTIME ARCHITECTURE inputs outputs Storage Manager Router σ μ Scheduler Buffer manager Box Processors Catalog Persistent Store Load Shedder QoS Monitor

  13. SUMMARY • Solution approach itself • Rethink about everything for the requirements • Query model • Data flow style query specification • Optimization • Dynamic runtime optimization • QoS specification based resource management

  14. QUESTIONS???

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