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. In this talk I'll describe "q-optimal histograms," which are histograms proposed by Guido Moerkotte that provide a quality guarantee such that any cardinality estimate derived from the histogram obeys a parameterized error bound. In addition to describing theory related to construction and use of q-optimal histograms, I'll also describe my own experience of implementing q-optimal histograms within the latest release of SAP HANA, along with some of the engineering decisions and algorithmic improvements that factored into the implementation. |
Location
DC - William G. Davis Computer Research Centre
Room 1331
200 University Avenue West
Waterloo, ON N2L 3G1
Canada
200 University Avenue West
Waterloo, ON N2L 3G1
Canada
