1 / 27

Aurora

A new model and architecture for data stream management. Aurora. The Topic. Aurora The prototype DBMS / SPE / DSMS UI The query language The project The authors. The Authors. M.I.T. , Department of EECS and Laboratory of Computer Science Michael Stonebraker

dalit
Download Presentation

Aurora

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A new model and architecture for data stream management Aurora

  2. The Topic • Aurora • The prototype • DBMS / SPE / DSMS • UI • The query language • The project • The authors

  3. The Authors • M.I.T. , Department of EECS and Laboratory of Computer Science • Michael Stonebraker • Brandeis University, Department of Computer Science • Daniel J. Abadi • Mitch Cherniack • Brown University , Department of Computer Science • Don Carney • Uğur Çetintemel • Christian Convey • Sangdon Lee • Nesime Tatbul • Stat Zdonik

  4. Talk Overview • Stream Processing Engines • SQuAl • Runtime • Related work

  5. Aurora Stream Processing Engines

  6. Stream Processing Engines • HADP vs DAHP • Events & Triggers • Continuous Queries • Real-time processing • Transient data • Lossy information

  7. Application Domains • Online Auctions • Network Traffic Management • Habitat Monitoring • Military Logistics • Immersive Environments • Road Traffic Monitoring • System Monitoring

  8. Aurora SQuAl (Stream Query Algebra)

  9. SQuAl Overview • Connection Points • Models • Continuous Query • View • Ad-hoc Query • Operators • Order-agnostic • Order-sensitive

  10. SQuAl Operators • Order-agnostic • Filter • Map • Union • Order-sensitive • BSort • Aggregate • Join • Resample

  11. Filter (Unordered)

  12. Map (Unordered)

  13. Union (Unordered)

  14. BSort (Ordered)

  15. Aggregate (Ordered)

  16. Join (Ordered)

  17. Resample (Ordered) • Based on RRDTool’s philosophy? • Paper: • Simple interpolation • Use The Force, Read The Source: • Average • Count • Sum • Max • Min • LastVal

  18. SQuAl: Example

  19. Aurora Runtime

  20. Query Optimization • Dynamic Continuous Query Optimization • Inserting projections • Combining boxes • Reordering boxes • Ad-hoc query optimization

  21. Real-time Scheduling • Timestamped Tuples • Train scheduling • Interbox nonlinearities • Intrabox nonlinearities • Superboxes • Introspection • Static • Run-time

  22. Handling overload • QoS specifications • Response times • Tuple drops • Values produced • Load Shedding • Not Implemented at the time

  23. Aurora Related work

  24. Related work • STREAM • Stanford University, 2000-2006 • Telegraph • UC Berkley, 2000-2007? • SASE • UC Berkley / Mass Amherst, 2006-2008? • Cayuga • Cornell University, 2005-2007? • PIPES • University of Marburg, 2003-2007? • NiagaraCQ • University of Wiscon-Madison, 1999-2002

  25. Aurora’s Evolution

  26. Complex Event Processing Today • Oracle • Oracle CEP • Microsoft • MS SQL Server StreamInsight • Open Source • OpenPDC • StreamBase • Aurora’s Grandchild • IBM • SPADE • Active Middleware Technology

More Related