I store time-series simulation results in PostgreSQL. The db schema is like this.
table SimulationInfo (
simulation_id integer primary key,
simulation_property1,
simulation_property2,
....
)
table SimulationResult ( // The size of one row would be around 100 bytes
simulation_id integer,
res_date Date,
res_value1,
res_value2,
...
res_value9,
primary key (simulation_id, res_date)
)
I usually query data based on simulation_id and res_date.
I partitioned the SimulationResult table into 200 sub-tables based on the range value of simulation_id. A fully filled sub table has 10 ~ 15 millions rows. Currently about 70 sub-tables are fully filled, and the database size is more than 100 gb. The total 200 sub tables would be filled soon, and when it happens, I need to add more sub tables.
But I read this answers, which says more than a few dozen partitions does not make sense. So my questions are like below.
more than a few dozen partitions not make sense? why? I checked the execution plan on my 200 sub-tables, and it scan only the relevant sub-table. So i guessed more partitions with smaller each sub-table must be better.
if number of partitions should be limited, like 50, then is it no problem to have billions rows in one table? How big one table can be without big problem given the schema like mine?