-----Original Message-----
From: Tom Lane <t...@sss.pgh.pa.us>
Sent: Thursday, July 22, 2021 11:57
To: l...@laurent-hasson.com
Cc: David Rowley <dgrowle...@gmail.com>; Peter Geoghegan <p...@bowt.ie>; Justin
Pryzby <pry...@telsasoft.com>; pgsql-performa...@postgresql.org
Subject: Re: Big performance slowdown from 11.2 to 13.3
I wrote:
> "l...@laurent-hasson.com" <l...@laurent-hasson.com> writes:
>> It's still spilling to disk and seems to cap at 2.5GB of memory usage in
>> spite of configuration.
> That is ... weird.
Oh: see get_hash_mem:
hash_mem = (double) work_mem * hash_mem_multiplier;
/*
* guc.c enforces a MAX_KILOBYTES limitation on work_mem in order to
* support the assumption that raw derived byte values can be stored in
* 'long' variables. The returned hash_mem value must also meet this
* assumption.
*
* We clamp the final value rather than throw an error because it should
* be possible to set work_mem and hash_mem_multiplier independently.
*/
if (hash_mem < MAX_KILOBYTES)
return (int) hash_mem;
return MAX_KILOBYTES;
So basically, we now have a hard restriction that hashaggs can't use more than
INT_MAX kilobytes, or approximately 2.5GB, and this use case is getting eaten
alive by that restriction. Seems like we need to do something about that.
regards, tom lane
------------------------------------------------------------------------------------------------------------------------------------------------------
Hello!
Ah... int vs long then? Tried even more (multiplier=16) and this seems to be
definitely the case.
Is it fair then to deduce that the total memory usage would be 2,400,305kB +
126,560kB? Is this what under the covers V11 is consuming more or less?
Is it also expected that a spill over of just 100MB (on top of 2.4GB memory
consumption) would cause the query to collapse like this? I am still not
visualizing in my head how that would happen. 100MB just seems so small, and
our SSD is fast.
Generating a dataset would take me a lot of time. This is a clinical database
so I cannot reuse the current table. I would have to entirely mock the use case
and create a dummy dataset from scratch.
HashAggregate (cost=1774568.21..1774579.21 rows=200 width=1260) (actual
time=94618.303..1795311.542 rows=722853 loops=1)
Group Key: assessmenticcqa_raw.iccqar_iccassmt_fk
Batches: 1 Memory Usage: 1277985kB
Buffers: shared hit=14 read=169854, temp read=15777 written=27588
-> HashAggregate (cost=1360804.75..1374830.63 rows=1402588 width=56)
(actual time=30753.022..45384.558 rows=13852618 loops=1)
Group Key: assessmenticcqa_raw.iccqar_iccassmt_fk,
assessmenticcqa_raw.iccqar_ques_code
Batches: 5 Memory Usage: 2400305kB Disk Usage: 126560kB
Buffers: shared read=169851, temp read=15777 written=27588
-> Seq Scan on assessmenticcqa_raw (cost=0.00..1256856.62
rows=13859750 width=38) (actual time=0.110..14342.258 rows=13852618 loops=1)
Filter: ((iccqar_ques_code)::text = ANY ('{"DEBRIDEMENT
DATE","DEBRIDEMENT THIS VISIT","DEBRIDEMENT TYPE","DEPTH (CM)","DEPTH
DESCRIPTION","DOES PATIENT HAVE PAIN ASSOCIATED WITH THIS WOUND?","DRAIN
PRESENT","DRAIN TYPE","EDGE / SURROUNDING TISSUE -
MACERATION",EDGES,EPITHELIALIZATION,"EXUDATE AMOUNT","EXUDATE
TYPE","GRANULATION TISSUE","INDICATE OTHER TYPE OF WOUND CLOSURE","INDICATE
TYPE","INDICATE WOUND CLOSURE","IS THIS A CLOSED SURGICAL WOUND OR SUSPECTED
DEEP TISSUE INJURY?","LENGTH (CM)","MEASUREMENTS TAKEN","NECROTIC TISSUE
AMOUNT","NECROTIC TISSUE TYPE",ODOR,"OTHER COMMENTS REGARDING DEBRIDEMENT
TYPE","OTHER COMMENTS REGARDING DRAIN TYPE","OTHER COMMENTS REGARDING PAIN
INTERVENTIONS","OTHER COMMENTS REGARDING PAIN QUALITY","OTHER COMMENTS
REGARDING REASON MEASUREMENTS NOT TAKEN","PAIN FREQUENCY","PAIN
INTERVENTIONS","PAIN QUALITY","PERIPHERAL TISSUE EDEMA","PERIPHERAL TISSUE
INDURATION","REASON MEASUREMENTS NOT TAKEN","RESPONSE TO PAIN
INTERVENTIONS",SHAPE,"SIGNS AND SYMPTOMS OF INFECTION","SKIN COLOR SURROUNDING
WOUND",STATE,"SURFACE AREA (SQ CM)","TOTAL NECROTIC TISSUE ESCHAR","TOTAL
NECROTIC TISSUE SLOUGH",TUNNELING,"TUNNELING SIZE(CM)/LOCATION - 12 - 3
O''CLOCK","TUNNELING SIZE(CM)/LOCATION - 3 - 6 O''CLOCK","TUNNELING
SIZE(CM)/LOCATION - 6 - 9 O''CLOCK","TUNNELING SIZE(CM)/LOCATION - 9 - 12
O''CLOCK",UNDERMINING,"UNDERMINING SIZE(CM)/LOCATION - 12 - 3
O''CLOCK","UNDERMINING SIZE(CM)/LOCATION - 3 - 6 O''CLOCK","UNDERMINING
SIZE(CM)/LOCATION - 6 - 9 O''CLOCK","UNDERMINING SIZE(CM)/LOCATION - 9 - 12
O''CLOCK","WIDTH (CM)","WOUND PAIN LEVEL, WHERE 0 = \"NO PAIN\" AND 10 =
\"WORST POSSIBLE PAIN\""}'::text[]))
Rows Removed by Filter: 171680
Buffers: shared read=169851
Settings: effective_cache_size = '52GB', from_collapse_limit = '24',
hash_mem_multiplier = '16', jit = 'off', jit_above_cost = '2e+08',
jit_inline_above_cost = '5e+08', jit_optimize_above_cost = '5e+08',
join_collapse_limit = '24', max_parallel_workers = '20',
max_parallel_workers_per_gather = '8', random_page_cost = '1.1', temp_buffers =
'4GB', work_mem = '1GB'
Planning:
Buffers: shared hit=186 read=37
Planning Time: 55.709 ms
Execution Time: 1795921.717 ms
Thank you,
Laurent.
