On Tue, Sep 21, 2021 at 12:03 AM Dilip Kumar <dilipbalaut@gmail.com> wrote:
>
> On Mon, Sep 20, 2021 at 5:37 PM Amit Kapila <amit.kapila16@gmail.com> wrote:
> > > >
> > >
> > > Adding a patch that strives to do the logic that I described above.
> > > For updates, the row filter is applied on both old_tuple
> > > and new_tuple. This patch assumes that the row filter only uses
> > > columns that are part of the REPLICA IDENTITY. (the current patch-set
> > > only
> > > restricts this for row-filters that are delete only)
> > > The old_tuple only has columns that are part of the old_tuple and have
> > > been changed, which is a problem while applying the row-filter. Since
> > > unchanged REPLICA IDENTITY columns
> > > are not present in the old_tuple, this patch creates a temporary
> > > old_tuple by getting such column values from the new_tuple and then
> > > applies the filter on this hand-created temp old_tuple. The way the
> > > old_tuple is created can be better optimised in future versions.
>
> I understand why this is done, but I have 2 concerns here 1) We are
> having extra deform and copying the field from new to old in case it
> is unchanged replica identity. 2) The same unchanged attribute values
> get qualified in the old tuple as well as in the new tuple. What
> exactly needs to be done is that the only updated field should be
> validated as part of the old as well as the new tuple, the unchanged
> field does not make sense to have redundant validation. For that we
> will have to change the filter for the old tuple to just validate the
> attributes which are actually modified and remaining unchanged and new
> values will anyway get validated in the new tuple.
>
But what if the filter expression depends on multiple columns, say (a+b) > 100
where a is unchanged while b is changed. Then we will still need both
columns for applying
the filter even though one is unchanged. Also, I am not aware of any
mechanism by which
we can apply a filter expression on individual attributes. The current
mechanism does it
on a tuple. Do let me know if you have any ideas there?
Even if it were done, there would still be the overhead of deforming the tuple.
I will run some performance tests like Amit suggested and see what the
overhead is and
try to minimise it.
regards,
Ajin Cherian
Fujitsu Australia
