Wednesday, March 26, 2014 2:30 PM EDT
| Speaker: |
Dan Farrar, SAP Waterloo |
| Abstract: |
I will revisit the seminal 1994 paper [1] by Goetz Graefe that describes the parallel Volcano query evaluation model. I will talk about the power of the Volcano model, its relevance to the hardware landscape today (SSDs, in-memory stores, massively multi-core systems), and the engineering challenges of getting it implemented correctly. |
Wednesday, March 19, 2014 2:30 PM EDT
Friday, March 14, 2014 11:00 AM EDT
| Abstract: |
Various High Availability DataBase systems (HADB) are used to provide high availability. Pairing an active database system with a standby system is one commonly used HADB techniques. The active system serves read/write workloads. One or more standby systems replicate the active and serve read-only workloads. |
Wednesday, March 12, 2014 2:30 PM EDT
| Abstract: |
I'll give an overview of some recent systems, e.g., Spanner, MDCC, Granola, and Megastore, that implement transactions over replicated partitioned databases, and will try to place them in context. |
Wednesday, March 5, 2014 2:30 PM EST
Wednesday, February 26, 2014 2:30 PM EST
| Abstract: |
New trends in storage industry suggest that in the near future a majority of the hard disk drive-based storage subsystems will be replaced by solid state drives (SSDs). Database management systems can substantially benefit from the superior I/O performance of SSDs. Although the impact of using SSDs in query processing has been studied in the past, exploiting the I/O parallelism of SSDs in query processing and optimization has not received enough attention. |
Wednesday, February 12, 2014 2:30 PM EST
| Abstract: |
I will present a practice talk for our LSDS-IR 2014 workshop paper on document size distribution in the context of search engines, then give a few related ideas that could be explored by interested grad students. |
Wednesday, February 5, 2014 2:30 PM EST
| Speaker: |
David DeHaan, SAP Waterloo |
| Abstract: |
In most DBMSs, histograms are an important data source used during cardinality estimation. Bad cardinality estimates originating from poor histograms can have drastic effects on the optimizer's ability to cost and therefore select a reasonable execution plan for a query. |
