From: | Shaun Thomas <shaun(dot)thomas(at)2ndquadrant(dot)com> |
---|---|
To: | Rick Otten <rottenwindfish(at)gmail(dot)com> |
Cc: | "pgsql-performa(dot)" <pgsql-performance(at)postgresql(dot)org> |
Subject: | Re: partitioning materialized views |
Date: | 2017-07-06 15:25:23 |
Message-ID: | CAG1YDPeH+FBFv9_w1ktPn3JyJNA1F8L_6qaMcRZZQsbBjXtxww@mail.gmail.com |
Views: | Raw Message | Whole Thread | Download mbox | Resend email |
Thread: | |
Lists: | pgsql-performance |
> I'm curious if I'm overlooking other possible architectures or tools that might make this simpler to manage.
One of the issues with materialized views is that they are based on
views... For a concurrent update, it essentially performs a looped
merge, which can be pretty ugly. That's the price you pay to be
non-blocking. For this particular setup, I'd actually recommend using
something like pglogical to just maintain a live copy of the remote
table or wait for Postgres 10's logical replication. If you _can't_ do
that due to cloud restrictions, you'd actually be better off doing an
atomic swap.
CREATE MATERIALIZED VIEW y AS ...;
BEGIN;
ALTER MATERIALIZED VIEW x RENAME TO x_old;
ALTER MATERIALIZED VIEW y RENAME TO x;
DROP MATERIALIZED VIEW x_old;
COMMIT;
You could still follow your partitioned plan if you don't want to
update all of the data at once. Let's face it, 3-4 hours is still a
ton of data transfer and calculation.
--
Shaun M Thomas - 2ndQuadrant
PostgreSQL Training, Services and Support
shaun(dot)thomas(at)2ndquadrant(dot)com | www.2ndQuadrant.com
From | Date | Subject | |
---|---|---|---|
Next Message | Rick Otten | 2017-07-06 16:05:33 | Re: partitioning materialized views |
Previous Message | Rick Otten | 2017-07-06 15:03:54 | partitioning materialized views |