On Mon, Apr 1, 2019 at 11:30 AM Jinho Jung <jinhojun@usc.edu> wrote:
> Surprisingly, we found that even on a larger TPC-C database (scale factor of 50, roughly 4GB of size), parallel scan
isstill slower than the non-parallel execution plan in the old version.
That's not a large database, and it's certainly not a large TPC-C
database. If you attempt to stay under the spec's maximum
tpmC/throughput per warehouse, which is 12.86 tpmC per warehouse, then
you'll need several thousand warehouses on modern hardware. We're
talking several hundred gigabytes. Otherwise, as far as the spec is
concerned you're testing an unrealistic workload. There will be
individual customers that make many more purchases than is humanly
possible. You're modelling an app involving hypothetical warehouse
employees that must enter data into their terminals at a rate that is
not humanly possible.
More importantly, this kind of analysis seems much too simplistic to
be useful. *Any* change to the optimizer or optimizer settings is
certain to regress some queries. We expect users that are very
sensitive to small regressions to take an active interest in
performance tuning their database. It would certainly be very useful
if somebody came up with a less complicated way of assessing these
questions, but that seems to be elusive.
--
Peter Geoghegan
