Re: Qual evaluation cost estimates for GIN indexes

I looked into the complaint here of poor estimation for GIN indexscans:
http://archives.postgresql.org/pgsql-performance/2012-02/msg00028.php
At first glance it sounds like a mistake in selectivity estimation,
but it isn't: the rowcount estimates are pretty nearly dead on.
The problem is in the planner's estimate of the cost of executing the
@@ operator. We have pg_proc.procost set to 1 for ts_match_vq, but
actually it's a good deal more expensive than that. Some
experimentation suggests that @@ might be about 500 times as expensive
as a simple integer comparison. I don't propose pushing its procost
up that much, but surely at least 10 would be appropriate, maybe even
100.

However ... if you just alter pg_proc.procost in Marc's example, the
planner *still* picks a seqscan, even though its estimate of the seqscan
cost surely does go up. The reason is that its estimate of the GIN
indexscan cost goes up just as much, since we charge one qual eval cost
per returned tuple in gincostestimate. It is easy to tell from the
actual runtimes that that is not what's happening in a GIN indexscan;
we are not re-executing the @@ operator for every tuple. But the
planner's cost model doesn't know that.

There are a couple of issues that would have to be addressed to make
this better:

1. If we shouldn't charge procost per row, what should we charge?
It's probably reasonable to assume that the primitive GIN-index-entry
comparison operations have cost equal to one cpu_operator_cost
regardless of what's assigned to the user-visible operators, but I'm
not convinced that that's sufficient to model complicated operators.
It might be okay to charge that much per index entry visited rather
than driving it off the number of heap tuples returned. The code in
gincostestimate goes to considerable lengths to estimate the number of
index pages fetched, and it seems like it might be able to derive the
number of index entries visited too, but it's not trying to account for
any CPU costs at the moment.

2. What about lossy operators, or lossy bitmap scans? If either of
those things happen, we *will* re-execute the @@ operator at visited
tuples, so discounting its high cost would be a mistake. But the
planner has no information about either effect, since we moved all
support for lossiness to runtime.

I think it was point #2 that led us to not consider these issues before.
But now that we've seen actual cases where the planner makes a poor
decision because it's not modeling this effect, I think we ought to try
to do something about it.

I haven't got time to do anything about this for 9.2, and I bet you
don't either, but it ought to be on the TODO list to try to improve
this.

BTW, an entirely different line of thought is "why on earth is @@ so
frickin expensive, when it's comparing already-processed tsvectors
with only a few entries to an already-processed tsquery with only one
entry??". This test case suggests to me that there's something
unnecessarily slow in there, and a bit of micro-optimization effort
might be well repaid.

regards, tom lane

I wrote:
> BTW, an entirely different line of thought is "why on earth is @@ so
> frickin expensive, when it's comparing already-processed tsvectors
> with only a few entries to an already-processed tsquery with only one
> entry??". This test case suggests to me that there's something
> unnecessarily slow in there, and a bit of micro-optimization effort
> might be well repaid.

Oh, scratch that: a bit of oprofiling shows that while the tsvectors
aren't all that long, they are long enough to get compressed, and most
of the runtime is going into pglz_decompress not @@ itself. So this
goes back to the known issue that the planner ought to try to account
for detoasting costs.

regards, tom lane

On Thu, Feb 16, 2012 at 6:30 PM, Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> wrote:
> I wrote:
>> BTW, an entirely different line of thought is "why on earth is @@ so
>> frickin expensive, when it's comparing already-processed tsvectors
>> with only a few entries to an already-processed tsquery with only one
>> entry??".  This test case suggests to me that there's something
>> unnecessarily slow in there, and a bit of micro-optimization effort
>> might be well repaid.
>
> Oh, scratch that: a bit of oprofiling shows that while the tsvectors
> aren't all that long, they are long enough to get compressed, and most
> of the runtime is going into pglz_decompress not @@ itself.  So this
> goes back to the known issue that the planner ought to try to account
> for detoasting costs.

This issue of detoasting costs comes up a lot, specifically in
reference to @@. I wonder if we shouldn't try to apply some quick and
dirty hack in time for 9.2, like maybe random_page_cost for every row
or every attribute we think will require detoasting. That's obviously
going to be an underestimate in many if not most cases, but it would
probably still be an improvement over assuming that detoasting is
free.

--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company

Robert Haas <robertmhaas(at)gmail(dot)com> writes:
> This issue of detoasting costs comes up a lot, specifically in
> reference to @@. I wonder if we shouldn't try to apply some quick and
> dirty hack in time for 9.2, like maybe random_page_cost for every row
> or every attribute we think will require detoasting. That's obviously
> going to be an underestimate in many if not most cases, but it would
> probably still be an improvement over assuming that detoasting is
> free.

Well, you can't theorize without data, to misquote Sherlock. We'd need
to have some stats on which to base "we think this will require
detoasting". I guess we could teach ANALYZE to compute and store
fractions "percent of entries in this column that are compressed"
and "percent that are stored out-of-line", and then hope that those
percentages apply to the subset of entries that a given query will
visit, and thereby derive a number of operations to multiply by whatever
we think the cost-per-detoast-operation is.

It's probably all do-able, but it seems way too late to be thinking
about this for 9.2. We've already got a ton of new stuff that needs
to be polished and tuned...

regards, tom lane

Hi.

First, thanks for looking at this. Except from GIN indexes and
full-text-search being really good in our applications, this also
points to those excact places where it can be improved.

On 2012-02-17 00:15, Tom Lane wrote:
> I looked into the complaint here of poor estimation for GIN indexscans:
> http://archives.postgresql.org/pgsql-performance/2012-02/msg00028.php

I think this is the excact same issue:
http://archives.postgresql.org/pgsql-hackers/2011-11/msg01754.php

> At first glance it sounds like a mistake in selectivity estimation,
> but it isn't: the rowcount estimates are pretty nearly dead on.
> The problem is in the planner's estimate of the cost of executing the
> @@ operator. We have pg_proc.procost set to 1 for ts_match_vq, but
> actually it's a good deal more expensive than that. Some
> experimentation suggests that @@ might be about 500 times as expensive
> as a simple integer comparison. I don't propose pushing its procost
> up that much, but surely at least 10 would be appropriate, maybe even
> 100.
>
> However ... if you just alter pg_proc.procost in Marc's example, the
> planner *still* picks a seqscan, even though its estimate of the seqscan
> cost surely does go up. The reason is that its estimate of the GIN
> indexscan cost goes up just as much, since we charge one qual eval cost
> per returned tuple in gincostestimate. It is easy to tell from the
> actual runtimes that that is not what's happening in a GIN indexscan;
> we are not re-executing the @@ operator for every tuple. But the
> planner's cost model doesn't know that.

There is something about lossy vs. non-lossy, if the index-result
is lossy, then it would "need" to execute the @@ operator
on each tuple and de-toast the toasted stuff and go all the way.

If it isn't then at least count() on a gin-index should be able to
utillize an index-only scan now?

I've had a significant amout of struggle over the years in this
corner and the patch that went in for gincostestimate brought
a huge set of problems to the ground, but not all.

Other related threads:
http://archives.postgresql.org/pgsql-performance/2010-05/msg00031.php
(ts_match_vq cost in discussion)
http://archives.postgresql.org/pgsql-performance/2010-05/msg00266.php

I dont think I have ever seen the actual run-time of any @@ query
to be faster going through the seq-scan than going through the index. Not
even if it is pulling near all the tuples out.

(test-case that tries to go in that corner).
http://archives.postgresql.org/pgsql-performance/2009-10/msg00393.php

And I think is it due to a coulple of "real-world" things:
1) The tsvector-column is typically toasted.
2) The selected columns are typically in the main table.
3) The gin-index search + pulling main table is in
fact a measuable cheaper operation than pulling main+toast
uncompressing toast and applying ts_match_vq even in the most
favourable case for the seqscan.

Another real-world thing is that since the tsvector column is in toast
and isn't read when performing a bitmap-heap-scan, in addition
to the decompress-cost is it almost never hot in memory either,
causing its actuall runtime to be even worse.

Same problems hit a index-scan on another key where filtering
on a @@ operator, but I think I got around most of them by bumping
both cost of @@ and limit in the query to 10K instead of the 200 actually
wanted.

I do think I have been digging sufficiently in this corner and can
fairly easy test and craft test-examples that will demonstrate
the challenges. (a few is attached in above links).

Thanks for digging in this corner. Let me know if i can help, allthough
my actual coding skills are spare (at best).

--
Jesper

> I looked into the complaint here of poor estimation for GIN
indexscans:
> http://archives.postgresql.org/pgsql-performance/2012-02/msg00028.php
> At first glance it sounds like a mistake in selectivity estimation,
> but it isn't: the rowcount estimates are pretty nearly dead on.
> The problem is in the planner's estimate of the cost of executing the
> @@ operator. We have pg_proc.procost set to 1 for ts_match_vq, but
> actually it's a good deal more expensive than that. Some
> experimentation suggests that @@ might be about 500 times as expensive
> as a simple integer comparison. I don't propose pushing its procost
> up that much, but surely at least 10 would be appropriate, maybe even
> 100.
>
> However ... if you just alter pg_proc.procost in Marc's example, the
> planner *still* picks a seqscan, even though its estimate of the
> seqscan
> cost surely does go up. The reason is that its estimate of the GIN
> indexscan cost goes up just as much, since we charge one qual eval
cost
> per returned tuple in gincostestimate. It is easy to tell from the
> actual runtimes that that is not what's happening in a GIN indexscan;
> we are not re-executing the @@ operator for every tuple. But the
> planner's cost model doesn't know that.

Hello,

many thanks for your feedback.

I've repeated my test with a table using plain storage, which halved the
query time.
This confirms that detoasting is the major issue for cost estimation,
but even with plain storage the table scan remains about 30% slower
compared to the index scan.

I've also looked for complex tsqueries where the planner would make a
better choice when the statistics are available
but found none. In some cases I got an identical plan, in other an
inversion of the plans (with NOT operator(s)).

In all cases where the plans differed, the planner chose the worse one,
with severe time differences.
So a naive 'empirical' question:

In case of an inverted index in non lossy situation, shouldn't the
planner also "invert" its cost assumptions?

best regards,

Marc Mamin

toast impact:

query: select id from <table> where v @@ 'fooblablabla'::tsquery

toasted table, analyzed: 813 ms (table scan)
http://explain.depesz.com/s/EoP

plain storage, analyzed: 404 ms (table scan)
http://explain.depesz.com/s/iGX

without analyze: 280 ms (index scan)
http://explain.depesz.com/s/5aGL

other queries

v @@ '(lexeme1 | lexeme4 ) &! (lexeme2 | lexeme3)'::tsquery
http://explain.depesz.com/s/BC7 (index scan im both cases)

plan switch !
v @@ '! fooblablabla'::tsquery

plain storage, analyzed: 2280 ms (index scan !)
http://explain.depesz.com/s/gCt

without analyze: 760 ms (table scan !)
http://explain.depesz.com/s/5aGL

>
> There are a couple of issues that would have to be addressed to make
> this better:
>
> 1. If we shouldn't charge procost per row, what should we charge?
> It's probably reasonable to assume that the primitive GIN-index-entry
> comparison operations have cost equal to one cpu_operator_cost
> regardless of what's assigned to the user-visible operators, but I'm
> not convinced that that's sufficient to model complicated operators.
> It might be okay to charge that much per index entry visited rather
> than driving it off the number of heap tuples returned. The code in
> gincostestimate goes to considerable lengths to estimate the number of
> index pages fetched, and it seems like it might be able to derive the
> number of index entries visited too, but it's not trying to account
for
> any CPU costs at the moment.
>
> 2. What about lossy operators, or lossy bitmap scans? If either of
> those things happen, we *will* re-execute the @@ operator at visited
> tuples, so discounting its high cost would be a mistake. But the
> planner has no information about either effect, since we moved all
> support for lossiness to runtime.
>
> I think it was point #2 that led us to not consider these issues
> before.
> But now that we've seen actual cases where the planner makes a poor
> decision because it's not modeling this effect, I think we ought to
try
> to do something about it.
>
> I haven't got time to do anything about this for 9.2, and I bet you
> don't either, but it ought to be on the TODO list to try to improve
> this.
>
> BTW, an entirely different line of thought is "why on earth is @@ so
> frickin expensive, when it's comparing already-processed tsvectors
> with only a few entries to an already-processed tsquery with only one
> entry??". This test case suggests to me that there's something
> unnecessarily slow in there, and a bit of micro-optimization effort
> might be well repaid.
>
> regards, tom lane

On Mon, Feb 20, 2012 at 10:18:31AM +0100, Marc Mamin wrote:
> > I looked into the complaint here of poor estimation for GIN
> indexscans:
> > http://archives.postgresql.org/pgsql-performance/2012-02/msg00028.php
> > At first glance it sounds like a mistake in selectivity estimation,
> > but it isn't: the rowcount estimates are pretty nearly dead on.
> > The problem is in the planner's estimate of the cost of executing the
> > @@ operator. We have pg_proc.procost set to 1 for ts_match_vq, but
> > actually it's a good deal more expensive than that. Some
> > experimentation suggests that @@ might be about 500 times as expensive
> > as a simple integer comparison. I don't propose pushing its procost
> > up that much, but surely at least 10 would be appropriate, maybe even
> > 100.
> >
> > However ... if you just alter pg_proc.procost in Marc's example, the
> > planner *still* picks a seqscan, even though its estimate of the
> > seqscan
> > cost surely does go up. The reason is that its estimate of the GIN
> > indexscan cost goes up just as much, since we charge one qual eval
> cost
> > per returned tuple in gincostestimate. It is easy to tell from the
> > actual runtimes that that is not what's happening in a GIN indexscan;
> > we are not re-executing the @@ operator for every tuple. But the
> > planner's cost model doesn't know that.
>
> Hello,
>
> many thanks for your feedback.
>
> I've repeated my test with a table using plain storage, which halved the
> query time.
> This confirms that detoasting is the major issue for cost estimation,
> but even with plain storage the table scan remains about 30% slower
> compared to the index scan.
>

Hi Marc,

Do you happen to know in which function, the extra time for the toast
storage is spent -- zlib compression? I saw a mention of the LZ4 compression
algorithm that is BSD licensed as a Google summer of code project:

http://code.google.com/p/lz4/

that compresses at almost 7X than zlib (-1) and decompresses at 6X.

Regards,
Ken

> Hi Marc,
>
> Do you happen to know in which function, the extra time for the toast
> storage is spent -- zlib compression? I saw a mention of the LZ4
> compression
> algorithm that is BSD licensed as a Google summer of code project:
>
> http://code.google.com/p/lz4/
>
> that compresses at almost 7X than zlib (-1) and decompresses at 6X.
>
> Regards,
> Ken

Hi,

No,

and my concern is more about cost estimation for ts_queries / gin
indexes as for the detoasting issue.

regards,

Marc Mamin