Re: [HACKERS] Block level parallel vacuum

On Thu, Oct 24, 2019 at 4:33 PM Dilip Kumar <dilipbalaut(at)gmail(dot)com> wrote:
>
> On Thu, Oct 24, 2019 at 4:21 PM Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> >
> > On Thu, Oct 24, 2019 at 11:51 AM Dilip Kumar <dilipbalaut(at)gmail(dot)com> wrote:
> > >
> > > On Fri, Oct 18, 2019 at 12:18 PM Dilip Kumar <dilipbalaut(at)gmail(dot)com> wrote:
> > > >
> > > > On Fri, Oct 18, 2019 at 11:25 AM Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> > > > >
> > > > > I am thinking if we can write the patch for both the approaches (a.
> > > > > compute shared costs and try to delay based on that, b. try to divide
> > > > > the I/O cost among workers as described in the email above[1]) and do
> > > > > some tests to see the behavior of throttling, that might help us in
> > > > > deciding what is the best strategy to solve this problem, if any.
> > > > > What do you think?
> > > >
> > > > I agree with this idea. I can come up with a POC patch for approach
> > > > (b). Meanwhile, if someone is interested to quickly hack with the
> > > > approach (a) then we can do some testing and compare. Sawada-san,
> > > > by any chance will you be interested to write POC with approach (a)?
> > > > Otherwise, I will try to write it after finishing the first one
> > > > (approach b).
> > > >
> > > I have come up with the POC for approach (a).

> > Can we compute the overall throttling (sleep time) in the operation
> > separately for heap and index, then divide the index's sleep_time with
> > a number of workers and add it to heap's sleep time? Then, it will be
> > a bit easier to compare the data between parallel and non-parallel
> > case.
I have come up with a patch to compute the total delay during the
vacuum. So the idea of computing the total cost delay is

Total cost delay = Total dealy of heap scan + Total dealy of
index/worker; Patch is attached for the same.

I have prepared this patch on the latest patch of the parallel
vacuum[1]. I have also rebased the patch for the approach [b] for
dividing the vacuum cost limit and done some testing for computing the
I/O throttling. Attached patches 0001-POC-compute-total-cost-delay
and 0002-POC-divide-vacuum-cost-limit can be applied on top of
v31-0005-Add-paralell-P-option-to-vacuumdb-command.patch. I haven't
rebased on top of v31-0006, because v31-0006 is implementing the I/O
throttling with one approach and 0002-POC-divide-vacuum-cost-limit is
doing the same with another approach. But,
0001-POC-compute-total-cost-delay can be applied on top of v31-0006 as
well (just 1-2 lines conflict).

Testing: I have performed 2 tests, one with the same size indexes and
second with the different size indexes and measured total I/O delay
with the attached patch.

Setup:
VacuumCostDelay=10ms
VacuumCostLimit=2000

Test1 (Same size index):
create table test(a int, b varchar, c varchar);
create index idx1 on test(a);
create index idx2 on test(b);
create index idx3 on test(c);
insert into test select i, repeat('a',30)||i, repeat('a',20)||i from
generate_series(1,500000) as i;
delete from test where a < 200000;

Vacuum (Head) Parallel Vacuum
Vacuum Cost Divide Patch
Total Delay 1784 (ms) 1398(ms)
1938(ms)

Test2 (Variable size dead tuple in index)
create table test(a int, b varchar, c varchar);
create index idx1 on test(a);
create index idx2 on test(b) where a > 100000;
create index idx3 on test(c) where a > 150000;

insert into test select i, repeat('a',30)||i, repeat('a',20)||i from
generate_series(1,500000) as i;
delete from test where a < 200000;

Vacuum (Head) Parallel Vacuum
Vacuum Cost Divide Patch
Total Delay 1438 (ms) 1029(ms)
1529(ms)

Conclusion:
1. The tests prove that the total I/O delay is significantly less with
the parallel vacuum.
2. With the vacuum cost divide the problem is solved but the delay bit
more compared to the non-parallel version. The reason could be the
problem discussed at[2], but it needs further investigation.

Next, I will test with the v31-0006 (shared vacuum cost) patch. I
will also try to test different types of indexes.

[1] https://www.postgresql.org/message-id/CAD21AoBMo9dr_QmhT%3DdKh7fmiq7tpx%2ByLHR8nw9i5NZ-SgtaVg%40mail.gmail.com
[2] https://www.postgresql.org/message-id/CAA4eK1%2BPeiFLdTuwrE6CvbNdx80E-O%3DZxCuWB2maREKFD-RaCA%40mail.gmail.com

--
Regards,
Dilip Kumar
EnterpriseDB: http://www.enterprisedb.com