Thread: Propose a new hook for mutating the query bounds
Hi hackers,
I am currently working on improving the cardinality estimation component in PostgreSQL with machine learning. I came up with a solution that mutates the bounds for different columns. For example, assume that we have a query
```
select * from test where X<10 and Y<20;
```
Our approach tries to learn the relation between X and Y. For example, if we have a linear relation, Y=X+10. Then Y<20 is essentially equivalent to X<10. Therefore we can mutate the Y<20 to Y<INT_MAX so that the selectivity will be 1, and we will have a more accurate estimation.
It seems to me that we can achieve something similar by mutating the pg_statistics, however, mutating the bounds is something more straightforward to me and less expensive.
I am wondering if it is possible to have such an extension? Or if there is a better solution to this? I have already implemented this stuff in a private repository, and if this is something you like, I can further propose the patch to the list.
Best regards,
Xiaozhe
On 11/17/21 2:24 PM, Xiaozhe Yao wrote: > Hi hackers, > > I am currently working on improving the cardinality estimation component > in PostgreSQL with machine learning. I came up with a solution that > mutates the bounds for different columns. For example, assume that we > have a query > > ``` > select * from test where X<10 and Y<20; > ``` > > Our approach tries to learn the relation between X and Y. For example, > if we have a linear relation, Y=X+10. Then Y<20 is essentially > equivalent to X<10. Therefore we can mutate the Y<20 to Y<INT_MAX so > that the selectivity will be 1, and we will have a more accurate estimation. > OK. FWIW the extended statistics patch originally included a patch for multi-dimensional histograms, and that would have worked for this example just fine, I guess. But yeah, there are various other dependencies for which a histogram would not help. And ML might discover that and help ... > It seems to me that we can achieve something similar by mutating the > pg_statistics, however, mutating the bounds is something more > straightforward to me and less expensive. > I don't understand how you could achieve this by mutating pg_statistic, without also breaking estimation for queries that only have Y<20. > I am wondering if it is possible to have such an extension? Or if there > is a better solution to this? I have already implemented this stuff in a > private repository, and if this is something you like, I can further > propose the patch to the list. > Maybe, but it's really hard to comment on this without seeing any PoC patches. We don't know where you you'd like the hook called, what info would it have access to, how would it tweak the selectivities etc. If you think this would work, write a PoC patch and we'll see. regards -- Tomas Vondra EnterpriseDB: http://www.enterprisedb.com The Enterprise PostgreSQL Company
Hi Tomas and Hackers,
Thanks for your reply and feedback!
> I don't understand how you could achieve this by mutating pg_statistic,
without also breaking estimation for queries that only have Y<20.
without also breaking estimation for queries that only have Y<20.
I agree, if we mutate pg_statistics, we will break lots of stuff and the process becomes complicated. That's also why I think mutating the bounds makes more sense and is easier to achieve.
> Maybe, but it's really hard to comment on this without seeing any PoC
patches. We don't know where you you'd like the hook called, what info
would it have access to, how would it tweak the selectivities etc.
patches. We don't know where you you'd like the hook called, what info
would it have access to, how would it tweak the selectivities etc.
I have attached a PoC patch to this mail. Essentially in this patch, I only try to pass the pointer of the constval in ```scalarineqsql``` function. It is enough from the Postgres side. With that, I can handle other things in an independent extension.
I hope this makes sense.
Best regards,
Xiaozhe
On Wed, Nov 17, 2021 at 2:49 PM Tomas Vondra <tomas.vondra@enterprisedb.com> wrote:
On 11/17/21 2:24 PM, Xiaozhe Yao wrote:
> Hi hackers,
>
> I am currently working on improving the cardinality estimation component
> in PostgreSQL with machine learning. I came up with a solution that
> mutates the bounds for different columns. For example, assume that we
> have a query
>
> ```
> select * from test where X<10 and Y<20;
> ```
>
> Our approach tries to learn the relation between X and Y. For example,
> if we have a linear relation, Y=X+10. Then Y<20 is essentially
> equivalent to X<10. Therefore we can mutate the Y<20 to Y<INT_MAX so
> that the selectivity will be 1, and we will have a more accurate estimation.
>
OK. FWIW the extended statistics patch originally included a patch for
multi-dimensional histograms, and that would have worked for this
example just fine, I guess. But yeah, there are various other
dependencies for which a histogram would not help. And ML might discover
that and help ...
> It seems to me that we can achieve something similar by mutating the
> pg_statistics, however, mutating the bounds is something more
> straightforward to me and less expensive.
>
I don't understand how you could achieve this by mutating pg_statistic,
without also breaking estimation for queries that only have Y<20.
> I am wondering if it is possible to have such an extension? Or if there
> is a better solution to this? I have already implemented this stuff in a
> private repository, and if this is something you like, I can further
> propose the patch to the list.
>
Maybe, but it's really hard to comment on this without seeing any PoC
patches. We don't know where you you'd like the hook called, what info
would it have access to, how would it tweak the selectivities etc.
If you think this would work, write a PoC patch and we'll see.
regards
--
Tomas Vondra
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company
Attachment
Xiaozhe Yao <askxzyao@gmail.com> writes: + if (mutate_bounds_hook) { + mutate_bounds_hook(root, &constval, isgt, iseq); + } It seems unlikely that this could do anything actually useful, and impossible that it could do anything useful without enormous waste of cycles along the way. Basically, each time one calls scalarineqsel, the hook would have to re-analyze the entire query to see if it should do anything. Most of the time the answer would be "no", after a lot of cycles wasted. It would also have to keep some state (where?) to coordinate mutation of different Consts in a WHERE clause. And why only a hook in scalarineqsel? Is that really the only context that you'd need to adjust the results in? Another important deficiency in this API spec is that the hook has no idea *which* constant it's being called on, so I don't see how it could really deliver correct answers at all. I can buy that ML techniques might provide a way to improve selectivity estimates overall, but I think inserting them would be better done with a much higher-level hook, maybe about at the level of clauselist_selectivity. regards, tom lane
Hi Tom,
Thanks for your feedback. I completely agree with you that a higher-level hook is better suited for this case. I have adjusted the PoC patch to this email.
Now it is located in the clauselist_selectivity_ext function, where we first check if the hook is defined. If so, we let the hook estimate the selectivity and return the result. With this one, I can also develop extensions to better estimate the selectivity.
I hope it makes more sense. Also please forgive me if I am understanding Postgres somehow wrong, as I am quite new to this community :)
Best regards,
Xiaozhe
Attachment
On 11/17/21 16:39, Xiaozhe Yao wrote: > Hi Tom, > > Thanks for your feedback. I completely agree with you that a > higher-level hook is better suited for this case. I have adjusted the > PoC patch to this email. > > Now it is located in the clauselist_selectivity_ext function, where we > first check if the hook is defined. If so, we let the hook estimate the > selectivity and return the result. With this one, I can also develop > extensions to better estimate the selectivity. > I think clauselist_selectivity is the right level, because this is pretty similar to what extended statistics are doing. I'm not sure if the hook should be called in clauselist_selectivity_ext or in the plain clauselist_selectivity. But it should be in clauselist_selectivity_or too, probably. The way the hook is used seems pretty inconvenient, though. I mean, if you do this if (clauselist_selectivity_hook) return clauselist_selectivity_hook(...); then what will happen when the ML model has no information applicable to a query? This is called for all relations, all conditions, etc. and you've short-circuited all the regular code, so the hook will have to copy all of that. Seems pretty silly and fragile. IMO the right approach is what statext_clauselist_selectivity is doing, i.e. estimate clauses, mark them as estimated in a bitmap, and let the rest of the existing code take care of the remaining clauses. So more something like if (clauselist_selectivity_hook) s1 *= clauselist_selectivity_hook(..., &estimatedclauses); regards -- Tomas Vondra EnterpriseDB: http://www.enterprisedb.com The Enterprise PostgreSQL Company
Hi,
Thanks for the previous feedbacks!
> The way the hook is used seems pretty inconvenient, though.
I see the problem, and I agree.
I looked into how other hooks work, and I am wondering if it looks ok if we: pass a pointer to the hook, and let the hook check if there is any information applicable. If there is none, the hook just returns False and we let the rest of the code handle. If it is true, we get the selectivity from the hook and return it. So something like
```
if (clauselist_selectivity_hook &&
(*clauselist_selectivity_hook) (root, clauses, varRelid, jointype, sjinfo, use_extended_stats, &s1))
{
return s1;
}
(*clauselist_selectivity_hook) (root, clauses, varRelid, jointype, sjinfo, use_extended_stats, &s1))
{
return s1;
}
```
What I am trying to mock is the get_index_stats_hook (https://github.com/taminomara/psql-hooks/blob/master/Detailed.md#get_index_stats_hook).
Am I understanding your idea correctly and does this look somehow better?
Best regards,
Xiaozhe
On Wed, Nov 17, 2021 at 7:47 PM Tomas Vondra <tomas.vondra@enterprisedb.com> wrote:
On 11/17/21 16:39, Xiaozhe Yao wrote:
> Hi Tom,
>
> Thanks for your feedback. I completely agree with you that a
> higher-level hook is better suited for this case. I have adjusted the
> PoC patch to this email.
>
> Now it is located in the clauselist_selectivity_ext function, where we
> first check if the hook is defined. If so, we let the hook estimate the
> selectivity and return the result. With this one, I can also develop
> extensions to better estimate the selectivity.
>
I think clauselist_selectivity is the right level, because this is
pretty similar to what extended statistics are doing. I'm not sure if
the hook should be called in clauselist_selectivity_ext or in the plain
clauselist_selectivity. But it should be in clauselist_selectivity_or
too, probably.
The way the hook is used seems pretty inconvenient, though. I mean, if
you do this
if (clauselist_selectivity_hook)
return clauselist_selectivity_hook(...);
then what will happen when the ML model has no information applicable to
a query? This is called for all relations, all conditions, etc. and
you've short-circuited all the regular code, so the hook will have to
copy all of that. Seems pretty silly and fragile.
IMO the right approach is what statext_clauselist_selectivity is doing,
i.e. estimate clauses, mark them as estimated in a bitmap, and let the
rest of the existing code take care of the remaining clauses. So more
something like
if (clauselist_selectivity_hook)
s1 *= clauselist_selectivity_hook(..., &estimatedclauses);
regards
--
Tomas Vondra
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company
Attachment
On 11/18/21 10:59, Xiaozhe Yao wrote: > Hi, > > Thanks for the previous feedbacks! > > > The way the hook is used seems pretty inconvenient, though. > > I see the problem, and I agree. > > I looked into how other hooks work, and I am wondering if it looks ok if > we: pass a pointer to the hook, and let the hook check if there is any > information applicable. If there is none, the hook just returns False > and we let the rest of the code handle. If it is true, we get the > selectivity from the hook and return it. So something like > > ``` > if (clauselist_selectivity_hook && > (*clauselist_selectivity_hook) (root, clauses, varRelid, jointype, > sjinfo, use_extended_stats, &s1)) > { > return s1; > } > ``` > No, that doesn't really solve the issue, because it's all or nothing approach. What if you ML can help estimating just a subset of clauses? IMHO the hooks should allow estimating the clauses the ML model was built on, and then do the usual estimation for the remaining ones. Otherwise you still have to copy large parts of the code. > What I am trying to mock is the get_index_stats_hook > (https://github.com/taminomara/psql-hooks/blob/master/Detailed.md#get_index_stats_hook > <https://github.com/taminomara/psql-hooks/blob/master/Detailed.md#get_index_stats_hook>). > But that hook only deals with a single index at a time - either it finds stats for it or not. But this new hook deals with a list of clauses, it should allow processing just a subset of them, I think. regards -- Tomas Vondra EnterpriseDB: http://www.enterprisedb.com The Enterprise PostgreSQL Company