Thanks for the insights..
Thanks,
Arun
On Wed, 3 Jan, 2024, 23:26 Jeremy Schneider, <schneider@xxxxxxxxxxxxxx> wrote:
On 1/2/24 11:23 PM, arun chirappurath wrote:
> Do we have any open source tools which can be used to create sample data
> at scale from our postgres databases?
> Which considers data distribution and randomness
I would suggest to use the most common tools whenever possible, because
then if you want to discuss results with other people (for example on
these mailing lists) then you're working with data sets that are widely
and well understood.
The most common tool for PostgreSQL is pgbench, which does a TPCB-like
schema that you can scale to any size, always the same [small] number of
tables/columns and same uniform data distribution, and there are
relationships between tables so you can create FKs if needed.
My second favorite tool is sysbench. Any number of tables, easily scale
to any size, standardized schema with small number of colums and no
relationships/FKs. Data distribution is uniformly random however on the
query side it supports a bunch of different distribution models, not
just uniform random, as well as queries processing ranges of rows.
The other tool that I'm intrigued by these days is benchbase from CMU.
It can do TPCC and a bunch of other schemas/workloads, you can scale the
data sizes. If you're just looking at data generation and you're going
to make your own workloads, well benchbase has a lot of different
schemas available out of the box.
You can always hand-roll your schema and data with scripts & SQL, but
the more complex and bespoke your performance test schema is, the more
work & explaining it takes to get lots of people to engage in a
discussion since they need to take time to understand how the test is
engineered. For very narrowly targeted reproductions this is usually the
right approach with a very simple schema and workload, but not commonly
for general performance testing.
-Jeremy
--
http://about.me/jeremy_schneider
