RE: row filtering for logical replication

On Monday, December 20, 2021 11:24 AM tanghy.fnst@fujitsu.com <tanghy.fnst@fujitsu.com>
> 
> On Wednesday, December 8, 2021 2:29 PM Amit Kapila
> <amit.kapila16@gmail.com> wrote:
> >
> > On Mon, Dec 6, 2021 at 6:04 PM Euler Taveira <euler@eulerto.com> wrote:
> > >
> > > On Mon, Dec 6, 2021, at 3:35 AM, Dilip Kumar wrote:
> > >
> > > On Mon, Dec 6, 2021 at 6:49 AM Euler Taveira <euler@eulerto.com> wrote:
> > > >
> > > > On Fri, Dec 3, 2021, at 8:12 PM, Euler Taveira wrote:
> > > >
> > > > PS> I will update the commit message in the next version. I barely changed
> the
> > > > documentation to reflect the current behavior. I probably missed some
> > changes
> > > > but I will fix in the next version.
> > > >
> > > > I realized that I forgot to mention a few things about the UPDATE behavior.
> > > > Regardless of 0003, we need to define which tuple will be used to evaluate
> the
> > > > row filter for UPDATEs. We already discussed it circa [1]. This current version
> > > > chooses *new* tuple. Is it the best choice?
> > >
> > > But with 0003, we are using both the tuple for evaluating the row
> > > filter, so instead of fixing 0001, why we don't just merge 0003 with
> > > 0001?  I mean eventually, 0003 is doing what is the agreed behavior,
> > > i.e. if just OLD is matching the filter then convert the UPDATE to
> > > DELETE OTOH if only new is matching the filter then convert the UPDATE
> > > to INSERT.  Do you think that even we merge 0001 and 0003 then also
> > > there is an open issue regarding which row to select for the filter?
> > >
> > > Maybe I was not clear. IIUC we are still discussing 0003 and I would like to
> > > propose a different default based on the conclusion I came up. If we merged
> > > 0003, that's fine; this change will be useless. If we don't or it is optional,
> > > it still has its merit.
> > >
> > > Do we want to pay the overhead to evaluating both tuple for UPDATEs? I'm still
> > > processing if it is worth it. If you think that in general the row filter
> > > contains the primary key and it is rare to change it, it will waste cycles
> > > evaluating the same expression twice. It seems this behavior could be
> > > controlled by a parameter.
> > >
> >
> > I think the first thing we should do in this regard is to evaluate the
> > performance for both cases (when we apply a filter to both tuples vs.
> > to one of the tuples). In case the performance difference is
> > unacceptable, I think it would be better to still compare both tuples
> > as default to avoid data inconsistency issues and have an option to
> > allow comparing one of the tuples.
> >
> 
> I did some performance tests to see if 0003 patch has much overhead.
> With which I compared applying first two patches and applying first three patches
> in four cases:
> 1) only old rows match the filter.
> 2) only new rows match the filter.
> 3) both old rows and new rows match the filter.
> 4) neither old rows nor new rows match the filter.
> 
> 0003 patch checks both old rows and new rows, and without 0003 patch, it only
> checks either old or new rows. We want to know whether it would take more time
> if we check the old rows.
> 
> I ran the tests in asynchronous mode and compared the SQL execution time. I also
> tried some complex filters, to see if the difference could be more obvious.
> 
> The result and the script are attached.
> I didn’t see big difference between the result of applying 0003 patch and the
> one not in all cases. So I think 0003 patch doesn’t have much overhead.
> 

In previous test, I ran 3 times and took the average value, which may be affected by
performance fluctuations.

So, to make the results more accurate, I tested them more times (10 times) and
took the average value. The result is attached.

In general, I can see the time difference is within 3.5%, which is in an reasonable
performance range, I think.

Regards,
Tang