On Sat, 10 Sept 2022 at 22:50, James Pang (chaolpan) <chaolpan@cisco.com> wrote:
> We plan to convert one large partition table to multiple non-partitioned tables, for example , one 256 HASH
partitiontable to 256 small tables. Then application will query small tables directly to get quick sql response time.
Doesthat help reduce backend process memory for "metadata", I can expect to reduce partition related cache of backend
process,but the table/index count is same.
Not really. The metadata (aka relcache) we're talking about is per
relation and it is loaded into the backend when a relation is first
accessed in a backend. Both tables and partitions are relations. A
partition may use slightly more memory in the relcache for storing the
partition constraint. However, that's probably quite insignificant
compared to the other data stored in relcache. The key here is likely
how many relations are being accessed from a given backend. HASH
partitioning does tend to lend itself to many partitions being
accessed in a short space of time. That's quite different from say,
having a RANGE partitioned table on time-series data with one
partition per month. Your workload might only access 1 partition per
month, in that case.
You've not really explained your use case, so it's hard to know if
HASH partitioning is best suited for your schema or not.
David
