why SSD is slower than HDD SAS 15K ?
Hello all,
Someone help me analyze the two execution plans below (Explain ANALYZE
used), is the query 9 of TPC-H benchmark [1].
I'm using two servers HP Intel Xeon 2.8GHz/4-core - Memory 8GB. O.S.
Debian8, using EXT4 filesystem.
Server 1
- HDD SAS 15 Krpm - 320 GB (Location where O.S. Debian and Postgresql are
installed).
Server 2
- Samsung Evo SSD 500 GB (Location where Postgresql is Installed)
- HDD Sata 7500 Krpm - 1TB (Location where O.S Debian is installed)
My DBMS parameters presents in postgresql.conf is default, but in SSD I
have changed random_page_cost = 1.0.
I do not understand, because running on an HDD SAS a query used half the
time. I explain better, in HDD spends on average 12 minutes the query
execution and on SSD spent 26 minutes.
I think maybe the execution plan is using more write operations, and so the
HDD SAS 15Krpm has been faster.
I checked that the temporary tablespace pg_default is on the SSD in server
2, because when running show temp_tablespaces in psql returns empty, will
be in the default directory, where I installed the DBMS in:
/media/ssd500gb/opt/pgv101norssd/data.
Anyway, I always thought that an SSD would be equal or faster, but in the
case and four more cases we have here, it lost a lot for the HDDs.
Any help in understanding, is welcome
Best Regards
Neto
----------------- Query execution Time on SSD ---------------
execution 1: 00:23:29
execution 2: 00:28:38
execution 3: 00:27:32
execution 4: 00:27:54
execution 5: 00:27:35
execution 6: 00:26:19
Average: 26min 54 seconds
------------Query execution Time on HDD SAS 15K
--------------------------------------
execution 1: 00:12:44
execution 2: 00:12:30
execution 3: 00:12:47
execution 4: 00:13:02
execution 5: 00:13:00
execution 6: 00:12:47
Average: 12 minutes 48 seconds
----------------- EXECUTION PLAN (ANALYZE, BUFFERS) on SSD
Storage--------------------------------------------------
Finalize GroupAggregate (cost=15822228.33..15980046.69 rows=60150
width=66) (actual time=1569793.025..1573969.614 rows=175 loops=1) Group
Key: nation.n_name, (date_part(_year_::text,
(orders.o_orderdate)::timestamp without time zone)) Buffers: shared
hit=1237677 read=2399403, temp read=1186697 written=1183781 -> Gather
Merge (cost=15822228.33..15977791.06 rows=120300 width=66) (actual
time=1569767.662..1573968.933 rows=525 loops=1) Workers Planned:
2 Workers Launched: 2 Buffers: shared hit=1237677
read=2399403, temp read=1186697 written=1183781 -> Partial
GroupAggregate (cost=15821228.31..15962905.44 rows=60150 width=66) (actual
time=1547834.941..1552040.073 rows=175 loops=3) Group Key:
nation.n_name, (date_part(_year_::text, (orders.o_orderdate)::timestamp
without time zone)) Buffers: shared hit=3522992 read=7371656,
temp read=3551003 written=3542253 -> Sort
(cost=15821228.31..15838806.37 rows=7031225 width=57) (actual
time=1547819.849..1548887.629 rows=4344197 loops=3) Sort
Key: nation.n_name, (date_part(_year_::text,
(orders.o_orderdate)::timestamp without time zone)) DESC
Sort Method: external merge Disk: 321648kB Buffers:
shared hit=3522992 read=7371656, temp read=3551003
written=3542253 -> Hash Join
(cost=4708859.28..14719466.13 rows=7031225 width=57) (actual
time=1220169.593..1541279.300 rows=4344197
loops=3) Hash Cond: (lineitem.l_suppkey =
supplier.s_suppkey) Buffers: shared hit=3522922
read=7371656, temp read=3220661 written=3211373
-> Hash Join (cost=4683017.71..14434606.65 rows=7071075 width=43) (actual
time=1142575.564..1535092.395 rows=4344197
loops=3) Hash Cond: (lineitem.l_orderkey =
orders.o_orderkey) Buffers: shared
hit=3503999 read=7362903, temp read=3114233
written=3104987 -> Hash Join
(cost=1993687.71..11297331.33 rows=7071075 width=47) (actual
time=275104.573..1213552.106 rows=4344197
loops=3) Hash Cond:
((lineitem.l_suppkey = partsupp.ps_suppkey) AND (lineitem.l_partkey =
partsupp.ps_partkey)) Buffers: shared
hit=1478115 read=6073916, temp read=2369833
written=2366725 -> Hash Join
(cost=273201.71..9157213.44 rows=7071075 width=45) (actual
time=24569.390..895992.716 rows=4344197
loops=3) Hash Cond:
(lineitem.l_partkey =
part.p_partkey) Buffers: shared
hit=314284 read=5038767, temp read=1742656
written=1742614 -> Parallel Seq
Scan on lineitem (cost=0.00..5861333.20 rows=100005120 width=41) (actual
time=0.147..712469.002 rows=80004097
loops=3) Buffers: shared
hit=482 read=4860800 -> Hash
(cost=263921.00..263921.00 rows=565657 width=4) (actual
time=24556.402..24556.402 rows=434469
loops=3) Buckets: 131072
Batches: 8 Memory Usage:
2933kB Buffers: shared
hit=313796 read=177967, temp
written=3327 -> Seq Scan
on part (cost=0.00..263921.00 rows=565657 width=4) (actual
time=0.073..24418.923 rows=434469
loops=3) Filter:
((p_name)::text ~~
_%orchid%_::text)
Rows Removed by Filter:
7565531 Buffers:
shared hit=313796 read=177967 ->
Hash (cost=1052986.00..1052986.00 rows=32000000 width=22) (actual
time=250328.161..250328.161 rows=32000000
loops=3) Buckets: 65536
Batches: 512 Memory Usage:
3941kB Buffers: shared
hit=1163809 read=1035149, temp
written=513846 -> Seq Scan on
partsupp (cost=0.00..1052986.00 rows=32000000 width=22) (actual
time=0.042..238352.960 rows=32000000
loops=3) Buffers: shared
hit=1163809 read=1035149 -> Hash
(cost=1704955.00..1704955.00 rows=60000000 width=8) (actual
time=272705.587..272705.587 rows=60000000
loops=3) Buckets: 131072 Batches:
1024 Memory Usage: 3316kB Buffers:
shared hit=2025878 read=1288987, temp
written=613128 -> Seq Scan on orders
(cost=0.00..1704955.00 rows=60000000 width=8) (actual
time=0.149..256480.758 rows=60000000
loops=3) Buffers: shared
hit=2025878 read=1288987 -> Hash
(cost=18106.56..18106.56 rows=400000 width=30) (actual
time=597.929..597.929 rows=400000 loops=3)
Buckets: 65536 Batches: 8 Memory Usage:
3549kB Buffers: shared hit=18841 read=8753,
temp written=6396 -> Hash Join
(cost=1.56..18106.56 rows=400000 width=30) (actual time=0.269..518.588
rows=400000 loops=3) Hash Cond:
(supplier.s_nationkey =
nation.n_nationkey) Buffers: shared
hit=18841 read=8753 -> Seq Scan on
supplier (cost=0.00..13197.00 rows=400000 width=12) (actual
time=0.246..435.109 rows=400000
loops=3) Buffers: shared
hit=18838 read=8753 -> Hash
(cost=1.25..1.25 rows=25 width=30) (actual time=0.016..0.016 rows=25
loops=3) Buckets: 1024 Batches:
1 Memory Usage: 10kB Buffers:
shared hit=3 -> Seq Scan on
nation (cost=0.00..1.25 rows=25 width=30) (actual time=0.007..0.010
rows=25 loops=3) Buffers:
shared hit=3Planning time: 2.319 msExecution time: 1574019.504 ms
------------------Execution plan (Explain Analyze) on HDD Storage
-------------------------------------------------
Finalize GroupAggregate (cost=14.865.093.59..14942715.87 rows=60150
width=66) (actual time=763039.932..767231.344 rows=175 loops=1) Group Key:
nation.n_name, (date_part(_year_::text, (orders.o_orderdate)::timestamp
without time zone)) -> Gather Merge (cost=14865093.59..14940460.24
rows=120300 width=66) (actual time=763014.187..767230.826 rows=525
loops=1) Workers Planned: 2 Workers Launched: 2 ->
Partial GroupAggregate (cost=14864093.57..14925574.61 rows=60150 width=66)
(actual time=758405.567..762576.512 rows=175 loops=3) Group
Key: nation.n_name, (date_part(_year_::text,
(orders.o_orderdate)::timestamp without time zone)) -> Sort
(cost=14864093.57..14871647.12 rows=3021421 width=57) (actual
time=758348.786..759400.608 rows=4344197 loops=3) Sort
Key: nation.n_name, (date_part(_year_::text,
(orders.o_orderdate)::timestamp without time zone)) DESC
Sort Method: external merge Disk: 324568kB -> Hash
Join (cost=4703389.12..14311687.00 rows=3021421 width=57) (actual
time=474033.697..736861.120 rows=4344197 loops=3)
Hash Cond: (lineitem.l_suppkey =
supplier.s_suppkey) -> Hash Join
(cost=4677547.56..14173154.89 rows=3030463 width=43) (actual
time=420246.635..728731.259 rows=4344197
loops=3) Hash Cond: (lineitem.l_orderkey =
orders.o_orderkey) -> Hash Join
(cost=1988224.59..11157928.33 rows=3030463 width=47) (actual
time=92246.411..545600.522 rows=4344197
loops=3) Hash Cond:
((lineitem.l_suppkey = partsupp.ps_suppkey) AND (lineitem.l_partkey =
partsupp.ps_partkey)) -> Hash Join
(cost=267897.64..9150646.81 rows=3030463 width=45) (actual
time=9247.722..368140.568 rows=4344197
loops=3) Hash Cond:
(lineitem.l_partkey =
part.p_partkey) -> Parallel Seq
Scan on lineitem (cost=0.00..5861333.40 rows=100005140 width=41) (actual
time=41.805..224438.909 rows=80004097
loops=3) -> Hash
(cost=263920.35..263920.35 rows=242423 width=4) (actual
time=9181.407..9181.407 rows=434469
loops=3) Buckets: 131072
(originally 131072) Batches: 8 (originally 4) Memory Usage:
3073kB -> Seq Scan on
part (cost=0.00..263920.35 rows=242423 width=4) (actual
time=5.608..9027.871 rows=434469
loops=3) Filter:
((p_name)::text ~~
_%orchid%_::text)
Rows Removed by Filter: 7565531 ->
Hash (cost=1052934.38..1052934.38 rows=31994838 width=22) (actual
time=82524.045..82524.045 rows=32000000
loops=3) Buckets: 65536
Batches: 512 Memory Usage:
3941kB -> Seq Scan on partsupp
(cost=0.00..1052934.38 rows=31994838 width=22) (actual
time=0.037..37865.003 rows=32000000 loops=3)
-> Hash (cost=1704952.32..1704952.32 rows=59999732 width=8) (actual
time=98182.919..98182.919 rows=60000000
loops=3) Buckets: 131072 Batches:
1024 Memory Usage: 3316kB -> Seq
Scan on orders (cost=0.00..1704952.32 rows=59999732 width=8) (actual
time=0.042..43977.490 rows=60000000 loops=3) ->
Hash (cost=18106.56..18106.56 rows=400000 width=30) (actual
time=555.225..555.225 rows=400000 loops=3)
Buckets: 65536 Batches: 8 Memory Usage:
3549kB -> Hash Join (cost=1.56..18106.56
rows=400000 width=30) (actual time=1.748..484.203 rows=400000
loops=3) Hash Cond:
(supplier.s_nationkey =
nation.n_nationkey) -> Seq Scan on
supplier (cost=0.00..13197.00 rows=400000 width=12) (actual
time=1.718..408.463 rows=400000
loops=3) -> Hash (cost=1.25..1.25
rows=25 width=30) (actual time=0.019..0.019 rows=25
loops=3) Buckets: 1024 Batches:
1 Memory Usage: 10kB -> Seq
Scan on nation (cost=0.00..1.25 rows=25 width=30) (actual
time=0.007..0.010 rows=25 loops=3)Planning time: 12.145 msExecution time:
767503.736 ms
-- Query SQL ------------------
select
nation,
o_year,
sum(amount) as sum_profit
from
(
select
n_name as nation,
extract(year from o_orderdate) as o_year,
l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity
as amount
from
part,
supplier,
lineitem,
partsupp,
orders,
nation
where
s_suppkey = l_suppkey
and ps_suppkey = l_suppkey
and ps_partkey = l_partkey
and p_partkey = l_partkey
and o_orderkey = l_orderkey
and s_nationkey = n_nationkey
and p_name like '%orchid%'
) as profit
group by
nation,
o_year
order by
nation,
o_year desc
Try random page cost 1.1. Way back when I started using SSD we had a
discussion here and came to the conclusion that it should be ever so
slightly higher than sequential page cost.
It is very hard to read your query plans (maybe gmail is wrapping them
funny or you need to use a fixed font on them or share them from
https://explain.depesz.com), but they do look substantially different. My
guess is that with the random page cost = sequential page cost you are
tricking Pg into using more sequential scans than index searches.
2018-01-15 9:13 GMT-08:00 Vick Khera <vivek@khera.org>:
Try random page cost 1.1. Way back when I started using SSD we had a
discussion here and came to the conclusion that it should be ever so
slightly higher than sequential page cost.
Very good tip, I'm running the query with random_page_cost = 1.1, but
notice that there are no secondary indexes on my database.
The test you were doing is to first run the query without index, and then
create an index to check the performance improvement.
But what I reported that having problem, is that the execution of the query
without index in a SAS HDD is being much faster, than the query (without
index) in the SSD, and I found this very strange, see below:
- Query execution Time on SSD - Average: 26min 54 seconds
- Query execution Time on HDD SAS 15K - Average: 12 minutes 48 seconds
It is very hard to read your query plans (maybe gmail is wrapping them
funny or you need to use a fixed font on them or share them from
https://explain.depesz.com), but they do look substantially different. My
guess is that with the random page cost = sequential page cost you are
tricking Pg into using more sequential scans than index searches.
The problem is that this plan is saved in the database, I have a Java
application that executes 6 times a query and saves the result of Explain
Analyze to a table in my Database. Upon regaining the execution plan, it
loses the line breaks, unfortunately. I'm checking how to change the java
application, I sent a question in the java forum because I do not know how
to solve this other problem yet: My question in Java forum:
https://stackoverflow.com/questions/48267819/save-line-break-in-database-in-text-field
On Mon, Jan 15, 2018 at 7:38 AM, Neto pr <netoprbr9@gmail.com> wrote:
Hello all,
Someone help me analyze the two execution plans below (Explain ANALYZE
used), is the query 9 of TPC-H benchmark [1].
I'm using two servers HP Intel Xeon 2.8GHz/4-core - Memory 8GB. O.S.
Debian8, using EXT4 filesystem.Server 1
- HDD SAS 15 Krpm - 320 GB (Location where O.S. Debian and Postgresql are
installed).Server 2
- Samsung Evo SSD 500 GB (Location where Postgresql is Installed)
- HDD Sata 7500 Krpm - 1TB (Location where O.S Debian is installed)My DBMS parameters presents in postgresql.conf is default, but in SSD I have
changed random_page_cost = 1.0.I do not understand, because running on an HDD SAS a query used half the
time. I explain better, in HDD spends on average 12 minutes the query
execution and on SSD spent 26 minutes.
I think maybe the execution plan is using more write operations, and so the
HDD SAS 15Krpm has been faster.
I checked that the temporary tablespace pg_default is on the SSD in server
2, because when running show temp_tablespaces in psql returns empty, will be
in the default directory, where I installed the DBMS in:
/media/ssd500gb/opt/pgv101norssd/data.Anyway, I always thought that an SSD would be equal or faster, but in the
case and four more cases we have here, it lost a lot for the HDDs.
Generally for reading data, yes, but you changed the query plan also.
To get to the bottom of this let's get SSD performance numbers for
both plans and HDD performance numbers for both plans. You're trying
to measure device performance about are probably measuring the
relative efficiencies of the generated plans.
merlin
I bet this is a ssd partition alignment problem there are erase block size
of 3mb and this should be taken in account, when You partition ssd drive,
creating a raid and filesystem etc...
---------- Původní e-mail ----------
Od: Merlin Moncure <mmoncure@gmail.com>
Komu: Neto pr <netoprbr9@gmail.com>
Datum: 15. 1. 2018 20:17:17
Předmět: Re: why SSD is slower than HDD SAS 15K ?
"On Mon, Jan 15, 2018 at 7:38 AM, Neto pr <netoprbr9@gmail.com> wrote:
Hello all,
Someone help me analyze the two execution plans below (Explain ANALYZE
used), is the query 9 of TPC-H benchmark [1].
I'm using two servers HP Intel Xeon 2.8GHz/4-core - Memory 8GB. O.S.
Debian8, using EXT4 filesystem.Server 1
- HDD SAS 15 Krpm - 320 GB (Location where O.S. Debian and Postgresql are
installed).Server 2
- Samsung Evo SSD 500 GB (Location where Postgresql is Installed)
- HDD Sata 7500 Krpm - 1TB (Location where O.S Debian is installed)My DBMS parameters presents in postgresql.conf is default, but in SSD I
have
changed random_page_cost = 1.0.
I do not understand, because running on an HDD SAS a query used half the
time. I explain better, in HDD spends on average 12 minutes the query
execution and on SSD spent 26 minutes.
I think maybe the execution plan is using more write operations, and so
the
HDD SAS 15Krpm has been faster.
I checked that the temporary tablespace pg_default is on the SSD in server
2, because when running show temp_tablespaces in psql returns empty, will
be
in the default directory, where I installed the DBMS in:
/media/ssd500gb/opt/pgv101norssd/data.Anyway, I always thought that an SSD would be equal or faster, but in the
case and four more cases we have here, it lost a lot for the HDDs.
Generally for reading data, yes, but you changed the query plan also.
To get to the bottom of this let's get SSD performance numbers for
both plans and HDD performance numbers for both plans. You're trying
to measure device performance about are probably measuring the
relative efficiencies of the generated plans.
merlin
"
Dear Merlin
2018-01-15 11:16 GMT-08:00 Merlin Moncure <mmoncure@gmail.com>:
On Mon, Jan 15, 2018 at 7:38 AM, Neto pr <netoprbr9@gmail.com> wrote:
Hello all,
Someone help me analyze the two execution plans below (Explain ANALYZE
used), is the query 9 of TPC-H benchmark [1].
I'm using two servers HP Intel Xeon 2.8GHz/4-core - Memory 8GB. O.S.
Debian8, using EXT4 filesystem.Server 1
- HDD SAS 15 Krpm - 320 GB (Location where O.S. Debian and Postgresql are
installed).Server 2
- Samsung Evo SSD 500 GB (Location where Postgresql is Installed)
- HDD Sata 7500 Krpm - 1TB (Location where O.S Debian is installed)My DBMS parameters presents in postgresql.conf is default, but in SSD I
have
changed random_page_cost = 1.0.
I do not understand, because running on an HDD SAS a query used half the
time. I explain better, in HDD spends on average 12 minutes the query
execution and on SSD spent 26 minutes.
I think maybe the execution plan is using more write operations, and sothe
HDD SAS 15Krpm has been faster.
I checked that the temporary tablespace pg_default is on the SSD inserver
2, because when running show temp_tablespaces in psql returns empty,
will be
in the default directory, where I installed the DBMS in:
/media/ssd500gb/opt/pgv101norssd/data.Anyway, I always thought that an SSD would be equal or faster, but in the
case and four more cases we have here, it lost a lot for the HDDs.Generally for reading data, yes, but you changed the query plan also.
To get to the bottom of this let's get SSD performance numbers for
both plans and HDD performance numbers for both plans. You're trying
to measure device performance about are probably measuring the
relative efficiencies of the generated plans.
Very good tip. I discovered that my SAS HDD drive has a transfer rate of
12Gb/s versus 6Gb/s of the SSD. Because of that reason the difference in
performance occurred. See below:
SSD: Samsung 500 GB SATA III 6Gb/s - Model: 850 Evo
http://www.samsung.com/semiconductor/minisite/ssd/product/consumer/850evo/
HDD: HPE 300GB 12G SAS Part-Number: 737261-B21
https://h20195.www2.hpe.com/v2/GetPDF.aspx%2Fc04111744.pdf
I intend to do my experiment, between HDD and SSD, abandon the SAS HDD and
use a SATA HDD, to compare with the SATA SSD.
I will use your strategy to put the OS and DBMS on the same disk, when it
is SSD and separate on the HDD.
Best Regards
Neto
Show quoted text
merlin
Dear NTPT
2018-01-15 16:54 GMT-08:00 NTPT <NTPT@seznam.cz>:
I bet this is a ssd partition alignment problem there are erase block size
of 3mb and this should be taken in account, when You partition ssd drive,
creating a raid and filesystem etc...
That is a good observation. I believe the block size was set by default
when I formatted the drive. I use Debian 64bits version 8, and all disks
are with ext4 file system. What size block do you suggest for SSD and HDD?
Neto
Show quoted text
---------- Původní e-mail ----------
Od: Merlin Moncure <mmoncure@gmail.com>
Komu: Neto pr <netoprbr9@gmail.com>
Datum: 15. 1. 2018 20:17:17
Předmět: Re: why SSD is slower than HDD SAS 15K ?On Mon, Jan 15, 2018 at 7:38 AM, Neto pr <netoprbr9@gmail.com> wrote:
Hello all,
Someone help me analyze the two execution plans below (Explain ANALYZE
used), is the query 9 of TPC-H benchmark [1].
I'm using two servers HP Intel Xeon 2.8GHz/4-core - Memory 8GB. O.S.
Debian8, using EXT4 filesystem.Server 1
- HDD SAS 15 Krpm - 320 GB (Location where O.S. Debian and Postgresqlare
installed).
Server 2
- Samsung Evo SSD 500 GB (Location where Postgresql is Installed)
- HDD Sata 7500 Krpm - 1TB (Location where O.S Debian is installed)My DBMS parameters presents in postgresql.conf is default, but in SSD I
have
changed random_page_cost = 1.0.
I do not understand, because running on an HDD SAS a query used half the
time. I explain better, in HDD spends on average 12 minutes the query
execution and on SSD spent 26 minutes.
I think maybe the execution plan is using more write operations, and sothe
HDD SAS 15Krpm has been faster.
I checked that the temporary tablespace pg_default is on the SSD inserver
2, because when running show temp_tablespaces in psql returns empty,
will be
in the default directory, where I installed the DBMS in:
/media/ssd500gb/opt/pgv101norssd/data.Anyway, I always thought that an SSD would be equal or faster, but in
the
case and four more cases we have here, it lost a lot for the HDDs.
Generally for reading data, yes, but you changed the query plan also.
To get to the bottom of this let's get SSD performance numbers for
both plans and HDD performance numbers for both plans. You're trying
to measure device performance about are probably measuring the
relative efficiencies of the generated plans.merlin
it depend of ssd type ie different ssd need diferent alignment. . on
samsung evo should be partition aligned to 3072 not default 2048 , to start
on erase block bounduary . And fs block should be 8kb (as I remember
correctly...)
---------- Původní e-mail ----------
Od: Neto pr <netoprbr9@gmail.com>
Komu: NTPT <NTPT@seznam.cz>, PostgreSQL General <pgsql-general@postgresql.
org>
Datum: 16. 1. 2018 2:54:49
Předmět: Re: why SSD is slower than HDD SAS 15K ?
"
Dear NTPT
2018-01-15 16:54 GMT-08:00 NTPT <NTPT@seznam.cz(mailto:NTPT@seznam.cz)>:
"
I bet this is a ssd partition alignment problem there are erase block size
of 3mb and this should be taken in account, when You partition ssd drive,
creating a raid and filesystem etc...
"
That is a good observation. I believe the block size was set by default when
I formatted the drive. I use Debian 64bits version 8, and all disks are with
ext4 file system. What size block do you suggest for SSD and HDD?
Neto
"
---------- Původní e-mail ----------
Od: Merlin Moncure <mmoncure@gmail.com(mailto:mmoncure@gmail.com)>
Komu: Neto pr <netoprbr9@gmail.com(mailto:netoprbr9@gmail.com)>
Datum: 15. 1. 2018 20:17:17
Předmět: Re: why SSD is slower than HDD SAS 15K ?
"On Mon, Jan 15, 2018 at 7:38 AM, Neto pr <netoprbr9@gmail.com
(mailto:netoprbr9@gmail.com)> wrote:
Hello all,
Someone help me analyze the two execution plans below (Explain ANALYZE
used), is the query 9 of TPC-H benchmark [1].
I'm using two servers HP Intel Xeon 2.8GHz/4-core - Memory 8GB. O.S.
Debian8, using EXT4 filesystem.Server 1
- HDD SAS 15 Krpm - 320 GB (Location where O.S. Debian and Postgresql are
installed).Server 2
- Samsung Evo SSD 500 GB (Location where Postgresql is Installed)
- HDD Sata 7500 Krpm - 1TB (Location where O.S Debian is installed)My DBMS parameters presents in postgresql.conf is default, but in SSD I
have
changed random_page_cost = 1.0.
I do not understand, because running on an HDD SAS a query used half the
time. I explain better, in HDD spends on average 12 minutes the query
execution and on SSD spent 26 minutes.
I think maybe the execution plan is using more write operations, and so
the
HDD SAS 15Krpm has been faster.
I checked that the temporary tablespace pg_default is on the SSD in server
2, because when running show temp_tablespaces in psql returns empty, will
be
in the default directory, where I installed the DBMS in:
/media/ssd500gb/opt/pgv101norssd/data.Anyway, I always thought that an SSD would be equal or faster, but in the
case and four more cases we have here, it lost a lot for the HDDs.
Generally for reading data, yes, but you changed the query plan also.
To get to the bottom of this let's get SSD performance numbers for
both plans and HDD performance numbers for both plans. You're trying
to measure device performance about are probably measuring the
relative efficiencies of the generated plans.
merlin
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