Обсуждение: Query slower on 8.0.3 (Windows) vs 7.3 (cygwin)
I currently have a Postgres 7.3 database running under WIN2K using cygwin
and want to move to Postgres 8.0.3 (native windows version).
I am finding most simple queries are significantly faster on the native
windows version compared to 7.3 (under cygwin).
However, for a complex query, that involve multiple JOINs, the 7.3 version
is actually faster (about 2X faster).
The query that I am running was optimized to run under 7.3. It was
specifically modified to control the planner with explicit JOINs.
When I run the same query on the 8.0.3 version with the join_collapse_limit
set to 1 the query is slower.
Can someone tell me why setting the join_collapse_limit to 1 in the 8.0
version does not produce similar results to the 7.3 version?
Does anyone have any suggestions on what I can do? Do I have to rewrite the
query?
Here are the results of an explain analyze on the query.
Explain analyze Postgres 7.3 running on WIN2K using cygwin.
Hash Join (cost=21808.27..1946264.80 rows=2982 width=1598) (actual
time=2186.00..2320.00 rows=50 loops=1)
Hash Cond: ("outer".doc_internalparentomxref = "inner".doc_documentid)
-> Hash Join (cost=20948.78..1945323.29 rows=2982 width=1534) (actual
time=2110.00..2227.00 rows=50 loops=1)
Hash Cond: ("outer".doc_internalrootxref = "inner".doc_documentid)
-> Hash Join (cost=20089.29..1944381.79 rows=2982 width=1484)
(actual time=2067.00..2179.00 rows=50 loops=1)
Hash Cond: ("outer".doc_documentid = "inner".doc_documentid)
Join Filter: ("inner".dc_doccontacttype = 'FROM'::character
varying)
-> Hash Join (cost=7455.14..1928613.59 rows=2982
width=1138) (actual time=1216.00..1539.00 rows=50 loops=1)
Hash Cond: ("outer".doc_documentid =
"inner".doc_documentid)
Join Filter: ("inner".dc_doccontacttype =
'TO'::character varying)
-> Hash Join (cost=183.49..1918519.06 rows=2860
width=792) (actual time=64.00..301.00 rows=50 loops=1)
Hash Cond: ("outer".doc_documentid =
"inner".doc_documentid)
-> Seq Scan on document finaldoc
(cost=0.00..1918256.94 rows=2860 width=717) (actual time=13.00..254.00
rows=50 loops=1)
Filter: (subplan)
SubPlan
-> Materialize (cost=335.27..335.27
rows=50 width=160) (actual time=0.00..0.01 rows=50 loops=5719)
-> Limit (cost=0.00..335.27
rows=50 width=160) (actual time=3.00..8.00 rows=50 loops=1)
-> Nested Loop
(cost=0.00..38347.95 rows=5719 width=160) (actual time=3.00..8.00 rows=51
loops=1)
-> Merge Join
(cost=0.00..3910.14 rows=5719 width=120) (actual time=3.00..3.00 rows=51
loops=1)
Merge Cond:
("outer".doc_documentid = "inner".doc_documentid)
-> Index Scan
using pk_document on document doc (cost=0.00..3256.48 rows=5719 width=80)
(actual time=1.00..1.00 rows=51 loops=1)
-> Index Scan
using pk_folder_document on folder_document (cost=0.00..553.91 rows=5719
width=40) (actual time=2.00..2.00 rows=51 loops=1)
-> Index Scan using
pk_document on document root (cost=0.00..6.01 rows=1 width=40) (actual
time=0.10..0.10 rows=1 loops=51)
Index Cond:
("outer".doc_internalrootxref = root.doc_documentid)
-> Hash (cost=169.19..169.19 rows=5719
width=75) (actual time=31.00..31.00 rows=0 loops=1)
-> Seq Scan on folder_document
(cost=0.00..169.19 rows=5719 width=75) (actual time=0.00..11.00 rows=5719
loops=1)
-> Hash (cost=1328.80..1328.80 rows=34280 width=346)
(actual time=846.00..846.00 rows=0 loops=1)
-> Seq Scan on doccontact dcto
(cost=0.00..1328.80 rows=34280 width=346) (actual time=0.00..175.00
rows=34280 loops=1)
-> Hash (cost=1328.80..1328.80 rows=34280 width=346)
(actual time=445.00..445.00 rows=0 loops=1)
-> Seq Scan on doccontact dcfrom (cost=0.00..1328.80
rows=34280 width=346) (actual time=0.00..223.00 rows=34280 loops=1)
-> Hash (cost=845.19..845.19 rows=5719 width=50) (actual
time=42.00..42.00 rows=0 loops=1)
-> Seq Scan on document root (cost=0.00..845.19 rows=5719
width=50) (actual time=0.00..2.00 rows=5719 loops=1)
-> Hash (cost=845.19..845.19 rows=5719 width=64) (actual
time=73.00..73.00 rows=0 loops=1)
-> Seq Scan on document parentom (cost=0.00..845.19 rows=5719
width=64) (actual time=0.00..30.00 rows=5719 loops=1)
SubPlan
-> Limit (cost=0.00..5.56 rows=1 width=40) (actual time=0.06..0.06
rows=0 loops=50)
-> Result (cost=0.00..7.20 rows=1 width=40) (actual
time=0.06..0.06 rows=0 loops=50)
One-Time Filter: ($0 = true)
-> Index Scan using documentevent_index on documentevent
de (cost=0.00..7.20 rows=1 width=40) (actual time=0.07..0.07 rows=0
loops=44)
Index Cond: (($1 = doc_documentid) AND
(de_processedflag = false) AND (de_documenteventstatus = 'ERROR'::character
varying))
-> Limit (cost=0.00..3.86 rows=1 width=40) (actual time=0.10..0.10
rows=0 loops=50)
Explain analyze Postgres 8.0.3 running natively under WIN2K.
Hash IN Join (cost=5293.09..7121.89 rows=50 width=1369) (actual
time=1062.000..5558.000 rows=50 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=4798.24..6199.29 rows=5741 width=1369) (actual
time=751.000..4236.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_internalparentomxref)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=3956.48..5271.41 rows=5741 width=1345)
(actual time=541.000..3105.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_internalrootxref)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=3114.72..4343.53 rows=5741
width=1335) (actual time=501.000..2313.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=1649.92..2721.09 rows=5741
width=1039) (actual time=180.000..1342.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=185.13..1098.65
rows=5741 width=743) (actual time=40.000..592.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_documentid)::text
= ("inner".doc_documentid)::text)
-> Seq Scan on document finaldoc
(cost=0.00..827.41 rows=5741 width=708) (actual time=0.000..41.000 rows=5719
loops=1)
-> Hash (cost=170.70..170.70 rows=5770
width=75) (actual time=40.000..40.000 rows=0 loops=1)
-> Seq Scan on folder_document
(cost=0.00..170.70 rows=5770 width=75) (actual time=0.000..10.000 rows=5719
loops=1)
-> Hash (cost=1450.50..1450.50 rows=5718
width=336) (actual time=140.000..140.000 rows=0 loops=1)
-> Seq Scan on doccontact dcto
(cost=0.00..1450.50 rows=5718 width=336) (actual time=0.000..130.000
rows=5718 loops=1)
Filter: ((dc_doccontacttype)::text =
'TO'::text)
-> Hash (cost=1450.50..1450.50 rows=5718 width=336)
(actual time=321.000..321.000 rows=0 loops=1)
-> Seq Scan on doccontact dcfrom
(cost=0.00..1450.50 rows=5718 width=336) (actual time=10.000..291.000
rows=5718 loops=1)
Filter: ((dc_doccontacttype)::text =
'FROM'::text)
-> Hash (cost=827.41..827.41 rows=5741 width=50) (actual
time=40.000..40.000 rows=0 loops=1)
-> Seq Scan on document root (cost=0.00..827.41
rows=5741 width=50) (actual time=0.000..30.000 rows=5719 loops=1)
-> Hash (cost=827.41..827.41 rows=5741 width=64) (actual
time=210.000..210.000 rows=0 loops=1)
-> Seq Scan on document parentom (cost=0.00..827.41
rows=5741 width=64) (actual time=0.000..160.000 rows=5719 loops=1)
-> Hash (cost=494.73..494.73 rows=50 width=42) (actual
time=261.000..261.000 rows=0 loops=1)
-> Subquery Scan "IN_subquery" (cost=185.13..494.73 rows=50
width=42) (actual time=101.000..261.000 rows=50 loops=1)
-> Limit (cost=185.13..494.23 rows=50 width=40) (actual
time=101.000..261.000 rows=50 loops=1)
-> Nested Loop Left Join (cost=185.13..35676.18
rows=5741 width=40) (actual time=101.000..261.000 rows=50 loops=1)
-> Hash Left Join (cost=185.13..1098.65
rows=5741 width=80) (actual time=91.000..91.000 rows=50 loops=1)
Hash Cond: (("outer".doc_documentid)::text
= ("inner".doc_documentid)::text)
-> Seq Scan on document doc
(cost=0.00..827.41 rows=5741 width=80) (actual time=10.000..10.000 rows=50
loops=1)
-> Hash (cost=170.70..170.70 rows=5770
width=40) (actual time=81.000..81.000 rows=0 loops=1)
-> Seq Scan on folder_document
(cost=0.00..170.70 rows=5770 width=40) (actual time=10.000..61.000 rows=5719
loops=1)
-> Index Scan using pk_document on document root
(cost=0.00..6.01 rows=1 width=40) (actual time=3.400..3.400 rows=1 loops=50)
Index Cond:
(("outer".doc_internalrootxref)::text = (root.doc_documentid)::text)
SubPlan
-> Limit (cost=0.00..1.96 rows=1 width=40) (actual time=0.400..0.400
rows=0 loops=50)
-> Seq Scan on followup_document fd (cost=0.00..3.91 rows=2
width=40) (actual time=0.400..0.400 rows=0 loops=50)
Filter: (($1)::text = (doc_documentid)::text)
-> Limit (cost=0.00..6.01 rows=1 width=40) (actual
time=17.620..17.620 rows=0 loops=50)
-> Result (cost=0.00..6.01 rows=1 width=40) (actual
time=17.620..17.620 rows=0 loops=50)
One-Time Filter: ($0 = true)
-> Index Scan using documentevent_index on documentevent
de (cost=0.00..6.01 rows=1 width=40) (actual time=28.419..28.419 rows=0
loops=31)
Index Cond: ((($1)::text = (doc_documentid)::text)
AND (de_processedflag = false) AND ((de_documenteventstatus)::text =
'ERROR'::text))
Total runtime: 5558.000 ms
I have started to break my query down and analyze each piece.
What I have discovered is very interesting.
First here is a small piece of my query.
EXPLAIN ANALYZE SELECT doc.doc_documentid FROM document AS doc
LEFT JOIN document as root ON doc.doc_internalRootXref =
root.doc_documentId
LEFT JOIN folder_document ON doc.doc_documentid =
folder_document.doc_documentId LIMIT 500 OFFSET 0
When I run this on Postgres 8.0.3 running under windows this is the result
QUERY PLAN
Limit (cost=183.49..753.41 rows=500 width=40) (actual time=47.000..79.000
rows=500 loops=1)
-> Hash Left Join (cost=183.49..6702.23 rows=5719 width=40) (actual
time=47.000..79.000 rows=500 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Merge Left Join (cost=0.00..6432.96 rows=5719 width=40) (actual
time=0.000..16.000 rows=500 loops=1)
Merge Cond: (("outer".doc_internalrootxref)::text =
("inner".doc_documentid)::text)
-> Index Scan using doc_internalrootxref_index on document
doc (cost=0.00..3172.64 rows=5719 width=80) (actual time=0.000..0.000
rows=500 loops=1)
-> Index Scan using pk_document on document root
(cost=0.00..3174.53 rows=5719 width=40) (actual time=0.000..0.000 rows=863
loops=1)
-> Hash (cost=169.19..169.19 rows=5719 width=40) (actual
time=47.000..47.000 rows=0 loops=1)
-> Seq Scan on folder_document (cost=0.00..169.19 rows=5719
width=40) (actual time=0.000..16.000 rows=5719 loops=1)
Total runtime: 79.000 ms
Here is the result of running the same query on the Postgres 7.3 running
under Cygwin
QUERY PLAN
Limit (cost=183.49..775.31 rows=500 width=160) (actual time=13.00..44.00
rows=500 loops=1)
-> Hash Join (cost=183.49..6952.79 rows=5719 width=160) (actual
time=13.00..44.00 rows=501 loops=1)
Hash Cond: ("outer".doc_documentid = "inner".doc_documentid)
-> Merge Join (cost=0.00..6612.03 rows=5719 width=120) (actual
time=0.00..29.00 rows=775 loops=1)
Merge Cond: ("outer".doc_internalrootxref =
"inner".doc_documentid)
-> Index Scan using doc_internalrootxref_index on document
doc (cost=0.00..3254.39 rows=5719 width=80) (actual time=0.00..7.00
rows=775 loops=1)
-> Index Scan using pk_document on document root
(cost=0.00..3257.88 rows=5719 width=40) (actual time=0.00..15.00 rows=1265
loops=1)
-> Hash (cost=169.19..169.19 rows=5719 width=40) (actual
time=12.00..12.00 rows=0 loops=1)
-> Seq Scan on folder_document (cost=0.00..169.19 rows=5719
width=40) (actual time=0.00..9.00 rows=5719 loops=1)
Total runtime: 45.00 msec
What is really interesting is the time it takes for the Hash to occur. For
the first hash, on the 7.3 it takes only 12ms while on the 8.0 it takes
47ms.
Now the databases are created from the same data and I have run
vacuumdb -f -z on the databases.
Now I have read something on the archives that stated that perhaps the data
is in the filesystem (not database) cache. Would this be the case?. If so
how would I improve the performance under WIN2K?
Anyone have any ideas?
-----Original Message-----
From: pgsql-performance-owner@postgresql.org
[mailto:pgsql-performance-owner@postgresql.org]On Behalf Of Gurpreet
Aulakh
Sent: September 21, 2005 12:38 PM
To: pgsql-performance@postgresql.org
Subject: [PERFORM] Query slower on 8.0.3 (Windows) vs 7.3 (cygwin)
I currently have a Postgres 7.3 database running under WIN2K using cygwin
and want to move to Postgres 8.0.3 (native windows version).
I am finding most simple queries are significantly faster on the native
windows version compared to 7.3 (under cygwin).
However, for a complex query, that involve multiple JOINs, the 7.3 version
is actually faster (about 2X faster).
The query that I am running was optimized to run under 7.3. It was
specifically modified to control the planner with explicit JOINs.
When I run the same query on the 8.0.3 version with the join_collapse_limit
set to 1 the query is slower.
Can someone tell me why setting the join_collapse_limit to 1 in the 8.0
version does not produce similar results to the 7.3 version?
Does anyone have any suggestions on what I can do? Do I have to rewrite the
query?
Here are the results of an explain analyze on the query.
Explain analyze Postgres 7.3 running on WIN2K using cygwin.
Hash Join (cost=21808.27..1946264.80 rows=2982 width=1598) (actual
time=2186.00..2320.00 rows=50 loops=1)
Hash Cond: ("outer".doc_internalparentomxref = "inner".doc_documentid)
-> Hash Join (cost=20948.78..1945323.29 rows=2982 width=1534) (actual
time=2110.00..2227.00 rows=50 loops=1)
Hash Cond: ("outer".doc_internalrootxref = "inner".doc_documentid)
-> Hash Join (cost=20089.29..1944381.79 rows=2982 width=1484)
(actual time=2067.00..2179.00 rows=50 loops=1)
Hash Cond: ("outer".doc_documentid = "inner".doc_documentid)
Join Filter: ("inner".dc_doccontacttype = 'FROM'::character
varying)
-> Hash Join (cost=7455.14..1928613.59 rows=2982
width=1138) (actual time=1216.00..1539.00 rows=50 loops=1)
Hash Cond: ("outer".doc_documentid =
"inner".doc_documentid)
Join Filter: ("inner".dc_doccontacttype =
'TO'::character varying)
-> Hash Join (cost=183.49..1918519.06 rows=2860
width=792) (actual time=64.00..301.00 rows=50 loops=1)
Hash Cond: ("outer".doc_documentid =
"inner".doc_documentid)
-> Seq Scan on document finaldoc
(cost=0.00..1918256.94 rows=2860 width=717) (actual time=13.00..254.00
rows=50 loops=1)
Filter: (subplan)
SubPlan
-> Materialize (cost=335.27..335.27
rows=50 width=160) (actual time=0.00..0.01 rows=50 loops=5719)
-> Limit (cost=0.00..335.27
rows=50 width=160) (actual time=3.00..8.00 rows=50 loops=1)
-> Nested Loop
(cost=0.00..38347.95 rows=5719 width=160) (actual time=3.00..8.00 rows=51
loops=1)
-> Merge Join
(cost=0.00..3910.14 rows=5719 width=120) (actual time=3.00..3.00 rows=51
loops=1)
Merge Cond:
("outer".doc_documentid = "inner".doc_documentid)
-> Index Scan
using pk_document on document doc (cost=0.00..3256.48 rows=5719 width=80)
(actual time=1.00..1.00 rows=51 loops=1)
-> Index Scan
using pk_folder_document on folder_document (cost=0.00..553.91 rows=5719
width=40) (actual time=2.00..2.00 rows=51 loops=1)
-> Index Scan using
pk_document on document root (cost=0.00..6.01 rows=1 width=40) (actual
time=0.10..0.10 rows=1 loops=51)
Index Cond:
("outer".doc_internalrootxref = root.doc_documentid)
-> Hash (cost=169.19..169.19 rows=5719
width=75) (actual time=31.00..31.00 rows=0 loops=1)
-> Seq Scan on folder_document
(cost=0.00..169.19 rows=5719 width=75) (actual time=0.00..11.00 rows=5719
loops=1)
-> Hash (cost=1328.80..1328.80 rows=34280 width=346)
(actual time=846.00..846.00 rows=0 loops=1)
-> Seq Scan on doccontact dcto
(cost=0.00..1328.80 rows=34280 width=346) (actual time=0.00..175.00
rows=34280 loops=1)
-> Hash (cost=1328.80..1328.80 rows=34280 width=346)
(actual time=445.00..445.00 rows=0 loops=1)
-> Seq Scan on doccontact dcfrom (cost=0.00..1328.80
rows=34280 width=346) (actual time=0.00..223.00 rows=34280 loops=1)
-> Hash (cost=845.19..845.19 rows=5719 width=50) (actual
time=42.00..42.00 rows=0 loops=1)
-> Seq Scan on document root (cost=0.00..845.19 rows=5719
width=50) (actual time=0.00..2.00 rows=5719 loops=1)
-> Hash (cost=845.19..845.19 rows=5719 width=64) (actual
time=73.00..73.00 rows=0 loops=1)
-> Seq Scan on document parentom (cost=0.00..845.19 rows=5719
width=64) (actual time=0.00..30.00 rows=5719 loops=1)
SubPlan
-> Limit (cost=0.00..5.56 rows=1 width=40) (actual time=0.06..0.06
rows=0 loops=50)
-> Result (cost=0.00..7.20 rows=1 width=40) (actual
time=0.06..0.06 rows=0 loops=50)
One-Time Filter: ($0 = true)
-> Index Scan using documentevent_index on documentevent
de (cost=0.00..7.20 rows=1 width=40) (actual time=0.07..0.07 rows=0
loops=44)
Index Cond: (($1 = doc_documentid) AND
(de_processedflag = false) AND (de_documenteventstatus = 'ERROR'::character
varying))
-> Limit (cost=0.00..3.86 rows=1 width=40) (actual time=0.10..0.10
rows=0 loops=50)
Explain analyze Postgres 8.0.3 running natively under WIN2K.
Hash IN Join (cost=5293.09..7121.89 rows=50 width=1369) (actual
time=1062.000..5558.000 rows=50 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=4798.24..6199.29 rows=5741 width=1369) (actual
time=751.000..4236.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_internalparentomxref)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=3956.48..5271.41 rows=5741 width=1345)
(actual time=541.000..3105.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_internalrootxref)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=3114.72..4343.53 rows=5741
width=1335) (actual time=501.000..2313.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=1649.92..2721.09 rows=5741
width=1039) (actual time=180.000..1342.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_documentid)::text =
("inner".doc_documentid)::text)
-> Hash Left Join (cost=185.13..1098.65
rows=5741 width=743) (actual time=40.000..592.000 rows=5719 loops=1)
Hash Cond: (("outer".doc_documentid)::text
= ("inner".doc_documentid)::text)
-> Seq Scan on document finaldoc
(cost=0.00..827.41 rows=5741 width=708) (actual time=0.000..41.000 rows=5719
loops=1)
-> Hash (cost=170.70..170.70 rows=5770
width=75) (actual time=40.000..40.000 rows=0 loops=1)
-> Seq Scan on folder_document
(cost=0.00..170.70 rows=5770 width=75) (actual time=0.000..10.000 rows=5719
loops=1)
-> Hash (cost=1450.50..1450.50 rows=5718
width=336) (actual time=140.000..140.000 rows=0 loops=1)
-> Seq Scan on doccontact dcto
(cost=0.00..1450.50 rows=5718 width=336) (actual time=0.000..130.000
rows=5718 loops=1)
Filter: ((dc_doccontacttype)::text =
'TO'::text)
-> Hash (cost=1450.50..1450.50 rows=5718 width=336)
(actual time=321.000..321.000 rows=0 loops=1)
-> Seq Scan on doccontact dcfrom
(cost=0.00..1450.50 rows=5718 width=336) (actual time=10.000..291.000
rows=5718 loops=1)
Filter: ((dc_doccontacttype)::text =
'FROM'::text)
-> Hash (cost=827.41..827.41 rows=5741 width=50) (actual
time=40.000..40.000 rows=0 loops=1)
-> Seq Scan on document root (cost=0.00..827.41
rows=5741 width=50) (actual time=0.000..30.000 rows=5719 loops=1)
-> Hash (cost=827.41..827.41 rows=5741 width=64) (actual
time=210.000..210.000 rows=0 loops=1)
-> Seq Scan on document parentom (cost=0.00..827.41
rows=5741 width=64) (actual time=0.000..160.000 rows=5719 loops=1)
-> Hash (cost=494.73..494.73 rows=50 width=42) (actual
time=261.000..261.000 rows=0 loops=1)
-> Subquery Scan "IN_subquery" (cost=185.13..494.73 rows=50
width=42) (actual time=101.000..261.000 rows=50 loops=1)
-> Limit (cost=185.13..494.23 rows=50 width=40) (actual
time=101.000..261.000 rows=50 loops=1)
-> Nested Loop Left Join (cost=185.13..35676.18
rows=5741 width=40) (actual time=101.000..261.000 rows=50 loops=1)
-> Hash Left Join (cost=185.13..1098.65
rows=5741 width=80) (actual time=91.000..91.000 rows=50 loops=1)
Hash Cond: (("outer".doc_documentid)::text
= ("inner".doc_documentid)::text)
-> Seq Scan on document doc
(cost=0.00..827.41 rows=5741 width=80) (actual time=10.000..10.000 rows=50
loops=1)
-> Hash (cost=170.70..170.70 rows=5770
width=40) (actual time=81.000..81.000 rows=0 loops=1)
-> Seq Scan on folder_document
(cost=0.00..170.70 rows=5770 width=40) (actual time=10.000..61.000 rows=5719
loops=1)
-> Index Scan using pk_document on document root
(cost=0.00..6.01 rows=1 width=40) (actual time=3.400..3.400 rows=1 loops=50)
Index Cond:
(("outer".doc_internalrootxref)::text = (root.doc_documentid)::text)
SubPlan
-> Limit (cost=0.00..1.96 rows=1 width=40) (actual time=0.400..0.400
rows=0 loops=50)
-> Seq Scan on followup_document fd (cost=0.00..3.91 rows=2
width=40) (actual time=0.400..0.400 rows=0 loops=50)
Filter: (($1)::text = (doc_documentid)::text)
-> Limit (cost=0.00..6.01 rows=1 width=40) (actual
time=17.620..17.620 rows=0 loops=50)
-> Result (cost=0.00..6.01 rows=1 width=40) (actual
time=17.620..17.620 rows=0 loops=50)
One-Time Filter: ($0 = true)
-> Index Scan using documentevent_index on documentevent
de (cost=0.00..6.01 rows=1 width=40) (actual time=28.419..28.419 rows=0
loops=31)
Index Cond: ((($1)::text = (doc_documentid)::text)
AND (de_processedflag = false) AND ((de_documenteventstatus)::text =
'ERROR'::text))
Total runtime: 5558.000 ms
---------------------------(end of broadcast)---------------------------
TIP 5: don't forget to increase your free space map settings
"Gurpreet Aulakh" <gaulakh@ecmarket.com> writes:
> What is really interesting is the time it takes for the Hash to occur. For
> the first hash, on the 7.3 it takes only 12ms while on the 8.0 it takes
> 47ms.
You haven't told us a thing about the column datatypes involved (much
less what the query actually is) ... but I wonder if this is a textual
datatype and the 8.0 installation is using a non-C locale where the 7.3
installation is using C locale. That could account for a considerable
slowdown in text comparison speeds.
regards, tom lane
Hi,
Here is the information that you requested.
The sub query that I am using is
EXPLAIN ANALYZE SELECT doc.doc_documentid FROM document AS doc
LEFT JOIN document as root
ON doc.doc_internalRootXref = root.doc_documentId
LEFT JOIN folder_document ON doc.doc_documentid =
folder_document.doc_documentId
LIMIT 500 OFFSET 0
The column doc_documentid is character varying(48) on both tables (document,
folder_document).
The column doc_internalRootXref is also character varying(48)
doc_documentid and doc_internalRootXref are UUIDs that is 36 chars long.
The document table has 58 columns.
31 columns are varchar ranging from size 8 to 80
7 booleans
4 numeric(12,2)
8 timestamp with time zone
1 integer
1 bigint
5 text
The folder_documen table has 6 columns
4 varchar (2 of length 16 2 of length 48)
The following indexes are on the document table
pk_document primary key btree (doc_documentid),
document_pk unique btree (doc_documentid),
doc_deliverydate_index btree (doc_deliverydate),
doc_externalxref_index btree (doc_externalxref),
doc_internalparentomxref_index btree (doc_internalparentomxref),
doc_internalrootxref_index btree (doc_internalrootxref)
The following indexes are on the folder_document table
pk_folder_document primary key btree (doc_documentid)
fk_folder_document1 FOREIGN KEY (fld_folderid) REFERENCES
folder(fld_folderid)
ON UPDATE RESTRICT ON DELETE CASCADE,
fk_folder_document2 FOREIGN KEY (doc_documentid) REFERENCES
document(doc_documentid)
ON UPDATE RESTRICT ON DELETE CASCADE
After reading your hint about locale settings, I reinstalled postgres and
made sure the locale was set
to C and that the encoding was SQL_ASCII. (these are the settings on the
cygwin installation).
I still get the same results in the last post.
-----Original Message-----
From: Tom Lane [mailto:tgl@sss.pgh.pa.us]
Sent: September 21, 2005 8:13 PM
To: Gurpreet Aulakh
Cc: pgsql-performance@postgresql.org
Subject: Re: [PERFORM] Query slower on 8.0.3 (Windows) vs 7.3 (cygwin)
"Gurpreet Aulakh" <gaulakh@ecmarket.com> writes:
> What is really interesting is the time it takes for the Hash to occur. For
> the first hash, on the 7.3 it takes only 12ms while on the 8.0 it takes
> 47ms.
You haven't told us a thing about the column datatypes involved (much
less what the query actually is) ... but I wonder if this is a textual
datatype and the 8.0 installation is using a non-C locale where the 7.3
installation is using C locale. That could account for a considerable
slowdown in text comparison speeds.
regards, tom lane
After further investigation I have found that the reason why the query is slower on 8.0.3 is that the hash and hash joins are slower on the 8.0.3. So the question comes down to : Why are hash and hash joins slower? Is this a postgres configuration setting that I am missing? Is the locale still screwing me up? I have set the locale to 'C' without any improvements. Is it because the column type is a varchar that the hash is slower?
"Gurpreet Aulakh" <gaulakh@ecmarket.com> writes:
> After further investigation I have found that the reason why the query is
> slower on 8.0.3 is that the hash and hash joins are slower on the 8.0.3.
> So the question comes down to : Why are hash and hash joins slower?
I looked into this a bit and determined that the problem seems to have
been introduced here:
2002-12-30 10:21 tgl
* src/: backend/executor/nodeHash.c,
backend/executor/nodeHashjoin.c, backend/optimizer/path/costsize.c,
include/executor/nodeHash.h: Better solution to integer overflow
problem in hash batch-number computation: reduce the bucket number
mod nbatch. This changes the association between original bucket
numbers and batches, but that doesn't matter. Minor other cleanups
in hashjoin code to help centralize decisions.
(which means it's present in 7.4 as well as 8.0). The code now
groups tuples into hash batches according to
(hashvalue % totalbuckets) % nbatch
When a tuple that is not in the first batch is reloaded, it is placed
into a bucket according to
(hashvalue % nbuckets)
This means that if totalbuckets, nbatch, and nbuckets have a common
factor F, the buckets won't be evenly used; in fact, only one in every F
buckets will be used at all, the rest remaining empty. The ones that
are used accordingly will contain about F times more tuples than
intended. The slowdown comes from having to compare these extra tuples
against the outer-relation tuples.
7.3 uses a different algorithm for grouping tuples that avoids this
problem, but it has performance issues of its own (in particular, to
avoid integer overflow we have to limit the number of batches we can
have). So just reverting this patch doesn't seem very attractive.
The problem no longer exists in 8.1 because of rewrites undertaken for
another purpose, so I'm sort of tempted to do nothing. To fix this in
the back branches we'd have to develop new code that won't ever go into
CVS tip and thus will never get beta-tested. The risk of breaking
things seems higher than I'd like.
If we did want to fix it, my first idea is to increment nbatch looking
for a value that has no common factor with nbuckets.
regards, tom lane
Hello fellow Postgresql'ers.
I've been stumbled on this RAID card which looks nice. It is a PCI-X SATA
Raid card with 6 channels, and does RAID 0,1,5,10,50.
It is a HP card with an Adaptec chip on it, and 64 MB cache.
HP Part # : 372953-B21
Adaptec Part # : AAR-2610SA/64MB/HP
There' even a picture :
http://megbytes.free.fr/Sata/DSC05970.JPG
I know it isn't as good as a full SCSI system. I just want to know if
some of you have had experiences with these, and if this cards belong to
the "slower than no RAID" camp, like some DELL card we often see mentioned
here, or to the "decent performance for the price" camp. It is to run on a
Linux.
Thanks in advance for your time and information.
I would consider Software Raid PFC wrote: > > Hello fellow Postgresql'ers. > > I've been stumbled on this RAID card which looks nice. It is a > PCI-X SATA Raid card with 6 channels, and does RAID 0,1,5,10,50. > It is a HP card with an Adaptec chip on it, and 64 MB cache. > > HP Part # : 372953-B21 > Adaptec Part # : AAR-2610SA/64MB/HP > > There' even a picture : > http://megbytes.free.fr/Sata/DSC05970.JPG > > I know it isn't as good as a full SCSI system. I just want to know > if some of you have had experiences with these, and if this cards > belong to the "slower than no RAID" camp, like some DELL card we > often see mentioned here, or to the "decent performance for the > price" camp. It is to run on a Linux. > > Thanks in advance for your time and information. > > ---------------------------(end of broadcast)--------------------------- > TIP 4: Have you searched our list archives? > > http://archives.postgresql.org -- -------------------------- Canaan Surfing Ltd. Internet Service Providers Ben-Nes Michael - Manager Tel: 972-4-6991122 Cel: 972-52-8555757 Fax: 972-4-6990098 http://www.canaan.net.il --------------------------
I would think software raid would be quite inappropriate considering postgres when it is working is taking a fair amount of CPU as would software RAID. Does anyone know if this is really the case ? Dave On 25-Sep-05, at 6:17 AM, Michael Ben-Nes wrote: > I would consider Software Raid > > > PFC wrote: > > >> >> Hello fellow Postgresql'ers. >> >> I've been stumbled on this RAID card which looks nice. It is a >> PCI-X SATA Raid card with 6 channels, and does RAID 0,1,5,10,50. >> It is a HP card with an Adaptec chip on it, and 64 MB cache. >> >> HP Part # : 372953-B21 >> Adaptec Part # : AAR-2610SA/64MB/HP >> >> There' even a picture : >> http://megbytes.free.fr/Sata/DSC05970.JPG >> >> I know it isn't as good as a full SCSI system. I just want to >> know if some of you have had experiences with these, and if this >> cards belong to the "slower than no RAID" camp, like some DELL >> card we often see mentioned here, or to the "decent performance >> for the price" camp. It is to run on a Linux. >> >> Thanks in advance for your time and information. >> >> ---------------------------(end of >> broadcast)--------------------------- >> TIP 4: Have you searched our list archives? >> >> http://archives.postgresql.org >> > > > -- > -------------------------- > Canaan Surfing Ltd. > Internet Service Providers > Ben-Nes Michael - Manager > Tel: 972-4-6991122 > Cel: 972-52-8555757 > Fax: 972-4-6990098 > http://www.canaan.net.il > -------------------------- > > > ---------------------------(end of > broadcast)--------------------------- > TIP 9: In versions below 8.0, the planner will ignore your desire to > choose an index scan if your joining column's datatypes do not > match > >
On 9/25/05, Dave Cramer <pg@fastcrypt.com> wrote: > I would think software raid would be quite inappropriate considering > postgres when it is working is taking a fair amount of CPU as would > software RAID. Does anyone know if this is really the case ? > I attempted to get some extra speed out of my Compaq/HP SA6404 card by using software RAID1 across to hardware RAID10 sets. It didn't help, but there was no noticeable load or drop in performance because of it. Granted, this was on a 4-way Opteron, but, anecdotally speaking, the linux software RAID has surprisingly low overhead. My $0.02, hope it helps. -- Mike Rylander mrylander@gmail.com GPLS -- PINES Development Database Developer http://open-ils.org
On Sun, Sep 25, 2005 at 10:57:56AM -0400, Dave Cramer wrote: >I would think software raid would be quite inappropriate considering >postgres when it is working is taking a fair amount of CPU as would >software RAID. Does anyone know if this is really the case ? It's not. Modern cpu's can handle raid operations without even noticing. At the point where your raid ops become a significant fraction of the cpu you'll be i/o bound anyway. Mike Stone
Dave Cramer wrote: > I would think software raid would be quite inappropriate considering > postgres when it is working is taking a fair amount of CPU as would > software RAID. Does anyone know if this is really the case ? The common explanation is that CPUs are so fast now that it doesn't make a difference. From my experience software raid works very, very well. However I have never put software raid on anything that is very heavily loaded. I would still use hardware raid if it is very heavily loaded. Sincerely, Joshua D. Drake -- Your PostgreSQL solutions company - Command Prompt, Inc. 1.800.492.2240 PostgreSQL Replication, Consulting, Custom Programming, 24x7 support Managed Services, Shared and Dedicated Hosting Co-Authors: plPHP, plPerlNG - http://www.commandprompt.com/
> The common explanation is that CPUs are so fast now that it doesn't make
> a difference.
> From my experience software raid works very, very well. However I have
> never put
> software raid on anything that is very heavily loaded.
Even for RAID5 ? it uses a bit more CPU for the parity calculations.
An advantage of software raid, is that if the RAID card dies, you have to
buy the same one ; whether I think that you can transfer a bunch of
software RAID5 disks to another machine if the machine they're in dies...
> > Even for RAID5 ? it uses a bit more CPU for the parity calculations. I honestly can't speak to RAID 5. I don't (and won't) use it. RAID 5 is a little brutal when under heavy write load. I use either 1, or 10. > An advantage of software raid, is that if the RAID card dies, you > have to buy the same one ; whether I think that you can transfer a > bunch of software RAID5 disks to another machine if the machine > they're in dies... There is a huge advantage to software raid on all kinds of levels. If you have the CPU then I suggest it. However you will never get the performance out of software raid on the high level (think 1 gig of cache) that you would on a software raid setup. It is a bit of a tradeoff but for most installations software raid is more than adequate. Sincerely, Joshua D. Drake -- Your PostgreSQL solutions company - Command Prompt, Inc. 1.800.492.2240 PostgreSQL Replication, Consulting, Custom Programming, 24x7 support Managed Services, Shared and Dedicated Hosting Co-Authors: plPHP, plPerlNG - http://www.commandprompt.com/
> There is a huge advantage to software raid on all kinds of levels. If
> you have the CPU then I suggest
> it. However you will never get the performance out of software raid on
> the high level (think 1 gig of cache)
> that you would on a software raid setup.
>
> It is a bit of a tradeoff but for most installations software raid is
> more than adequate.
Which makes me think that I will use Software Raid 5 and convert the
price of the card into RAM.
This should be nice for a budget server.
Gonna investigate now if Linux software RAID5 is rugged enough. Can
always buy the a card later if not.
Thanks all for the advice, you were really helpful.
PFC <lists@boutiquenumerique.com> writes: > Which makes me think that I will use Software Raid 5 and convert the > price of the card into RAM. > This should be nice for a budget server. > Gonna investigate now if Linux software RAID5 is rugged enough. Can > always buy the a card later if not. Raid 5 is perhaps the exception here. For Raid 5 a substantial amount of CPU power is needed. Also, Raid 5 is particularly inappropriate for write-heavy Database traffic. Raid 5 actually hurts write latency dramatically and Databases are very sensitive to latency. On the other hand if your database is primarily read-only then Raid 5 may not be a problem and may be faster than raid 1+0. -- greg
On Sun, Sep 25, 2005 at 01:41:06PM -0400, Greg Stark wrote: >Also, Raid 5 is particularly inappropriate for write-heavy Database traffic. >Raid 5 actually hurts write latency dramatically and Databases are very >sensitive to latency. Software raid 5 actually may have an advantage here. The main cause for high raid5 write latency is the necessity of having blocks from each disk available to calculate the parity. The chances of a pc with several gigs of ram having all the blocks cached (thus not requiring any reads) are higher than on a hardware raid with several hundred megs of ram. Mike Stone
On Sun, Sep 25, 2005 at 06:53:57PM +0200, PFC wrote: > Gonna investigate now if Linux software RAID5 is rugged enough. Can > always buy the a card later if not. Note that 2.6.13 and 2.6.14 have several improvements to the software RAID code, some with regard to ruggedness. You might want to read the changelogs. /* Steinar */ -- Homepage: http://www.sesse.net/
jd@commandprompt.com ("Joshua D. Drake") writes:
> There is a huge advantage to software raid on all kinds of
> levels. If you have the CPU then I suggest it. However you will
> never get the performance out of software raid on the high level
> (think 1 gig of cache) that you would on a software raid setup.
This appears to be a case where the "ludicrous MHz increases" on
desktop CPUs has actually provided a material benefit.
The sorts of embedded controllers typically used on RAID controllers
are StrongARMs and i960s, and, well, 250MHz is actually fast for
these.
When AMD and Intel fight over adding gigahertz and megabytes of cache
to their chips, this means that the RAID work can get pushed over to
one's "main CPU" without chewing up terribly much of its bandwidth.
That says to me that in the absence of battery backed cache, it's not
worth having a "bottom-end" RAID controller. Particularly if the
death of the controller would be likely to kill your data.
Battery-backed cache changes the value proposition, of course...
--
select 'cbbrowne' || '@' || 'acm.org';
http://cbbrowne.com/info/linuxdistributions.html
All generalizations are false, including this one.
Thanks for your help Tom.
While testing 8.1, I found that simple joins take longer in 8.1 than 8.0.
For example the sub query
SELECT doc.doc_documentid FROM document AS doc LEFT JOIN folder_document ON
doc.doc_documentid = folder_document.doc_documentId LEFT JOIN document as
root ON doc.doc_internalRootXref = root.doc_documentId
is actually slower on 8.1 than 8.0.
However, the full query that I will be running is much faster. In my
evaluation I found the same pattern. That simple joins were slower but
complex joins were faster.
Overall though, 8.1 is faster and we will probably be moving to it when it's
officially released.
-----Original Message-----
From: Tom Lane [mailto:tgl@sss.pgh.pa.us]
Sent: September 23, 2005 2:13 PM
To: Gurpreet Aulakh
Cc: pgsql-performance@postgresql.org
Subject: Re: [PERFORM] Query slower on 8.0.3 (Windows) vs 7.3 (cygwin)
"Gurpreet Aulakh" <gaulakh@ecmarket.com> writes:
> After further investigation I have found that the reason why the query is
> slower on 8.0.3 is that the hash and hash joins are slower on the 8.0.3.
> So the question comes down to : Why are hash and hash joins slower?
I looked into this a bit and determined that the problem seems to have
been introduced here:
2002-12-30 10:21 tgl
* src/: backend/executor/nodeHash.c,
backend/executor/nodeHashjoin.c, backend/optimizer/path/costsize.c,
include/executor/nodeHash.h: Better solution to integer overflow
problem in hash batch-number computation: reduce the bucket number
mod nbatch. This changes the association between original bucket
numbers and batches, but that doesn't matter. Minor other cleanups
in hashjoin code to help centralize decisions.
(which means it's present in 7.4 as well as 8.0). The code now
groups tuples into hash batches according to
(hashvalue % totalbuckets) % nbatch
When a tuple that is not in the first batch is reloaded, it is placed
into a bucket according to
(hashvalue % nbuckets)
This means that if totalbuckets, nbatch, and nbuckets have a common
factor F, the buckets won't be evenly used; in fact, only one in every F
buckets will be used at all, the rest remaining empty. The ones that
are used accordingly will contain about F times more tuples than
intended. The slowdown comes from having to compare these extra tuples
against the outer-relation tuples.
7.3 uses a different algorithm for grouping tuples that avoids this
problem, but it has performance issues of its own (in particular, to
avoid integer overflow we have to limit the number of batches we can
have). So just reverting this patch doesn't seem very attractive.
The problem no longer exists in 8.1 because of rewrites undertaken for
another purpose, so I'm sort of tempted to do nothing. To fix this in
the back branches we'd have to develop new code that won't ever go into
CVS tip and thus will never get beta-tested. The risk of breaking
things seems higher than I'd like.
If we did want to fix it, my first idea is to increment nbatch looking
for a value that has no common factor with nbuckets.
regards, tom lane
"Gurpreet Aulakh" <gaulakh@ecmarket.com> writes:
> While testing 8.1, I found that simple joins take longer in 8.1 than 8.0.
> For example the sub query
> SELECT doc.doc_documentid FROM document AS doc LEFT JOIN folder_document ON
> doc.doc_documentid = folder_document.doc_documentId LEFT JOIN document as
> root ON doc.doc_internalRootXref = root.doc_documentId
> is actually slower on 8.1 than 8.0.
With no more detail than that, this report is utterly unhelpful. Let's
see the table schemas and the EXPLAIN ANALYZE results in both cases.
regards, tom lane