RE: Postgres12 looking for possible HashAggregate issue workarounds?

2022-12-19 Thread João Paulo Luís
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De: David Rowley 
Enviado: 18 de dezembro de 2022 11:06
Para: João Paulo Luís 
Cc: Justin Pryzby ; 
pgsql-performance@lists.postgresql.org 
Assunto: Re: Postgres12 looking for possible HashAggregate issue workarounds?

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On Sun, 18 Dec 2022 at 23:44, João Paulo Luís  wrote:
> Meanwhile, as a one-time workaround I've disabled the hashagg algorithm,

The way the query planner determines if Hash Aggregate's hash table
will fit in work_mem or not is based on the n_distinct estimate of the
columns being grouped on.  You may want to review what analyze set
n_distinct to on this table. That can be done by looking at:

select attname,n_distinct from pg_Stats where tablename =
'sentencesource' and attname = 'sentence';

If what that's set to does not seem realistic, then you can overwrite this with:

ALTER TABLE sentencesource ALTER COLUMN sentence SET (n_distinct = N);

Please see the paragraph in [1] about n_distinct.  Using an absolute
value is likely not a great idea if the table is going to grow. You
could maybe give it a better estimate about how many times values are
repeated by setting some negative value, as described in the
documents. You'll need to analyze the table again after changing this
setting.

David

[1] https://www.postgresql.org/docs/12/sql-altertable.html


Re: Postgres12 looking for possible HashAggregate issue workarounds?

2022-12-18 Thread David Rowley
On Sun, 18 Dec 2022 at 23:44, João Paulo Luís  wrote:
> Meanwhile, as a one-time workaround I've disabled the hashagg algorithm,

The way the query planner determines if Hash Aggregate's hash table
will fit in work_mem or not is based on the n_distinct estimate of the
columns being grouped on.  You may want to review what analyze set
n_distinct to on this table. That can be done by looking at:

select attname,n_distinct from pg_Stats where tablename =
'sentencesource' and attname = 'sentence';

If what that's set to does not seem realistic, then you can overwrite this with:

ALTER TABLE sentencesource ALTER COLUMN sentence SET (n_distinct = N);

Please see the paragraph in [1] about n_distinct.  Using an absolute
value is likely not a great idea if the table is going to grow. You
could maybe give it a better estimate about how many times values are
repeated by setting some negative value, as described in the
documents. You'll need to analyze the table again after changing this
setting.

David

[1] https://www.postgresql.org/docs/12/sql-altertable.html




RE: Postgres12 looking for possible HashAggregate issue workarounds?

2022-12-18 Thread João Paulo Luís
Thank you. It seems it is precisely that problem.

(I will discuss with the rest of the team upgrade possibilities, as I guess it 
will never be backported to the bugfixes of version 12.)

Meanwhile, as a one-time workaround I've disabled the hashagg algorithm,

SET enable_hashagg=off;

repeated the query, and it finished in 1h28m (and the RAM resident memory 
stayed just a little above the 16GB of shared_buffers).

Happy holidays!


João Luís

Senior Developer

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De: Justin Pryzby 
Enviado: 16 de dezembro de 2022 16:06
Para: João Paulo Luís 
Cc: pgsql-performance@lists.postgresql.org 

Assunto: Re: Postgres12 looking for possible HashAggregate issue workarounds?

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On Fri, Dec 16, 2022 at 03:24:17PM +, João Paulo Luís wrote:
> Hi! Sorry to post to this mailing list, but I could not find many tips 
> working around HashAggregate issues.
>
> In a research project involving text repetition analysis (on top of public 
> documents)
> I have a VirtualMachine (CPU AMD Epyc 7502P, 128GB RAM, 12TB HDD, 2TB SSD),
> running postgres 12.12 (Ubuntu 12.12-0ubuntu0.20.04.1)
> and some tables with many rows:

> 1 - the query is making a postgresql project have 76.7 GB resident RAM usage.
> Having a WORK_MEM setting of 2GB (and "simple" COUNT() results),
> that was not expected.
> (I risk oom-killer killing my postgres as soon as I run another concurrent
> query.)

> The rows=261275 on HashAggregate  (cost=26397219.92..26399832.67 rows=261275 
> width=8) seems VERY WRONG!
> I was expecting something like rows=1.0E+09 instead.

> I would guess that HashAggregate is behaving very badly (using to much RAM 
> beyond WORK_MEM, amd also badly estimating the #rows and taking forever...)

Huge memory use sounds like what was fixed in postgres 13.

https://www.postgresql.org/docs/13/release-13.html

Allow hash aggregation to use disk storage for large aggregation result
sets (Jeff Davis)

Previously, hash aggregation was avoided if it was expected to use more
than work_mem memory. Now, a hash aggregation plan can be chosen despite
that. The hash table will be spilled to disk if it exceeds work_mem
times hash_mem_multiplier.

This behavior is normally preferable to the old behavior, in which once
hash aggregation had been chosen, the hash table would be kept in memory
no matter how large it got — which could be very large if the planner
had misestimated. If necessary, behavior similar to that can be obtained
by increasing hash_mem_multiplier.

--
Justin


Re: Postgres12 looking for possible HashAggregate issue workarounds?

2022-12-16 Thread Justin Pryzby
On Fri, Dec 16, 2022 at 03:24:17PM +, João Paulo Luís wrote:
> Hi! Sorry to post to this mailing list, but I could not find many tips 
> working around HashAggregate issues.
> 
> In a research project involving text repetition analysis (on top of public 
> documents)
> I have a VirtualMachine (CPU AMD Epyc 7502P, 128GB RAM, 12TB HDD, 2TB SSD),
> running postgres 12.12 (Ubuntu 12.12-0ubuntu0.20.04.1)
> and some tables with many rows:

> 1 - the query is making a postgresql project have 76.7 GB resident RAM usage.
> Having a WORK_MEM setting of 2GB (and "simple" COUNT() results),
> that was not expected.
> (I risk oom-killer killing my postgres as soon as I run another concurrent
> query.)

> The rows=261275 on HashAggregate  (cost=26397219.92..26399832.67 rows=261275 
> width=8) seems VERY WRONG!
> I was expecting something like rows=1.0E+09 instead.

> I would guess that HashAggregate is behaving very badly (using to much RAM 
> beyond WORK_MEM, amd also badly estimating the #rows and taking forever...)

Huge memory use sounds like what was fixed in postgres 13.

https://www.postgresql.org/docs/13/release-13.html

Allow hash aggregation to use disk storage for large aggregation result
sets (Jeff Davis)

Previously, hash aggregation was avoided if it was expected to use more
than work_mem memory. Now, a hash aggregation plan can be chosen despite
that. The hash table will be spilled to disk if it exceeds work_mem
times hash_mem_multiplier.

This behavior is normally preferable to the old behavior, in which once
hash aggregation had been chosen, the hash table would be kept in memory
no matter how large it got — which could be very large if the planner
had misestimated. If necessary, behavior similar to that can be obtained
by increasing hash_mem_multiplier.

-- 
Justin




Postgres12 looking for possible HashAggregate issue workarounds?

2022-12-16 Thread João Paulo Luís
Hi! Sorry to post to this mailing list, but I could not find many tips working 
around HashAggregate issues.

In a research project involving text repetition analysis (on top of public 
documents)
I have a VirtualMachine (CPU AMD Epyc 7502P, 128GB RAM, 12TB HDD, 2TB SSD),
running postgres 12.12 (Ubuntu 12.12-0ubuntu0.20.04.1)
and some tables with many rows:

nsoamt=> ANALYSE VERBOSE SentenceSource;
INFO:  analyzing "public.sentencesource"
INFO:  "sentencesource": scanned 3 of 9028500 pages, containing 3811990 
live rows and 268323 dead rows; 3 rows in sample, 1147218391 estimated 
total rows
ANALYZE
nsoamt=> ANALYSE VERBOSE SentenceToolCheck;
INFO:  analyzing "public.sentencetoolcheck"
INFO:  "sentencetoolcheck": scanned 3 of 33536425 pages, containing 498508 
live rows and 25143 dead rows; 3 rows in sample, 557272538 estimated total 
rows
ANALYZE
nsoamt=> ANALYZE VERBOSE Document;
INFO:  analyzing "public.document"
INFO:  "document": scanned 3 of 34570 pages, containing 1371662 live rows 
and 30366 dead rows; 3 rows in sample, 1580612 estimated total rows
ANALYZE

The estimates for the number of rows above are accurate.

I am running this query

SELECT COUNT(*), COUNT(NULLIF(Stchk.haserrors,'f'))
FROM SentenceToolCheck Stchk
WHERE EXISTS (SELECT SSrc.sentence
  FROM SentenceSource SSrc, Document Doc
  WHERE SSrc.sentence = Stchk.id
  AND Doc.id = SSrc.document
  AND Doc.source ILIKE 
'/bigpostgres/misc/arxiv/arxiv/arxiv/pdf/%');

and I have 2 (related?) problems


1 - the query is making a postgresql project have 76.7 GB resident RAM usage.
Having a WORK_MEM setting of 2GB (and "simple" COUNT() results),
that was not expected.
(I risk oom-killer killing my postgres as soon as I run another concurrent
query.)

The memory settings are:

work_mem = 2GB
shared_buffers = 16GB
maintenance_work_mem = 1GB



2 - the query never finishes... (it is over 3x24hours execution by now,
and I have no ideia how far from finishing it is).

The EXPLAIN plan is:

   QUERY PLAN

 Aggregate  (cost=28630195.79..28630195.80 rows=1 width=16)
   ->  Nested Loop  (cost=26397220.49..28628236.23 rows=261275 width=1)
 ->  HashAggregate  (cost=26397219.92..26399832.67 rows=261275 width=8)
   Group Key: ssrc.sentence
   ->  Hash Join  (cost=73253.21..23635527.52 rows=1104676957 
width=8)
 Hash Cond: (ssrc.document = doc.id)
 ->  Seq Scan on sentencesource ssrc  
(cost=0.00..20540394.02 rows=1151189402 width=16)
 ->  Hash  (cost=54310.40..54310.40 rows=1515425 width=4)
   ->  Seq Scan on document doc  (cost=0.00..54310.40 
rows=1515425 width=4)
 Filter: (source ~~* 
'/bigpostgres/misc/arxiv/arxiv/arxiv/pdf/%'::text)
 ->  Index Scan using pk_sentencetoolcheck on sentencetoolcheck stchk  
(cost=0.57..8.53 rows=1 width=9)
   Index Cond: (id = ssrc.sentence)
 JIT:
   Functions: 20
   Options: Inlining true, Optimization true, Expressions true, Deforming true
(15 rows)

The rows=1515425 estimate on Seq Scan on document doc  (cost=0.00..54310.40 
rows=1515425 width=4) seems right.

The rows=1104676957 estimate on Hash Join  (cost=73253.21..23635527.52 
rows=1104676957 width=8) also seems right.

The rows=261275 on HashAggregate  (cost=26397219.92..26399832.67 rows=261275 
width=8) seems VERY WRONG!
I was expecting something like rows=1.0E+09 instead.


On a laptop (with just 80% of the rows, 32GB RAM, but all SSD disks),
I finish the query in a few hours (+/- 2 hours).

The EXPLAIN plan is different on the laptop:

   QUERY PLAN
-
 Aggregate  (cost=216688374.89..216688374.90 rows=1 width=16)
   ->  Nested Loop  (cost=211388557.47..216686210.27 rows=288616 width=1)
 ->  Unique  (cost=211388556.90..215889838.75 rows=288616 width=8)
   ->  Sort  (cost=211388556.90..213639197.82 rows=900256370 
width=8)
 Sort Key: ssrc.sentence
 ->  Hash Join  (cost=56351.51..28261726.31 rows=900256370 
width=8)
   Hash Cond: (ssrc.document = doc.id)
   ->  Seq Scan on sentencesource ssrc  
(cost=0.00..16453055.44 rows=948142144 width=16)
   ->  Hash  (cost=38565.65..38565.65 rows=1084069 
width=4)
 ->  Seq Scan on document doc  
(cost=0.00..38565.65 rows=1084069 width=4)
   Filter: (source ~~* 
'/bigpostgres/misc/arxiv/arxiv/arxiv/pdf/%'::text)
 -