Обсуждение: 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@sss.pgh.pa.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@gmail.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 uncompressingtoast 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 (tablescan !) 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