HDD vs SSD without explanation

Dear 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 a server HP Intel Xeon 2.8GHz/4-core - Memory 8GB HDD SAS 320GB
15 Krpm AND SSD Sansung EVO 500GB.
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 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.
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
-------------------------------------------------------------------------------
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 SSD
Storage--------------------------------------------------------
Finalize GroupAggregate (cost=15.694.362.41..15842178.65 rows=60150
width=66) (actual time=1670577.649..1674717.444 rows=175 loops=1) Group
Key: nation.n_name, (date_part(_year_::text,
(orders.o_orderdate)::timestamp without time zone)) -> Gather Merge
(cost=15694362.41..15839923.02 rows=120300 width=66) (actual
time=1670552.446..1674716.748 rows=525 loops=1) Workers Planned:
2 Workers Launched: 2 -> Partial GroupAggregate
(cost=15693362.39..15825037.39 rows=60150 width=66) (actual
time=1640482.164..1644619.574 rows=175 loops=3) Group Key:
nation.n_name, (date_part(_year_::text, (orders.o_orderdate)::timestamp
without time zone)) -> Sort (cost=15693362.39..15709690.19
rows=6531119 width=57) (actual time=1640467.384..1641511.970 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:
319512kB -> Hash Join (cost=4708869.23..14666423.78
rows=6531119 width=57) (actual time=1366753.586..1634128.122 rows=4344197
loops=3) Hash Cond: (lineitem.l_suppkey =
supplier.s_suppkey) -> Hash Join
(cost=4683027.67..14400582.74 rows=6531119 width=43) (actual
time=1328019.213..1623919.675 rows=4344197
loops=3) Hash Cond: (lineitem.l_orderkey =
orders.o_orderkey) -> Hash Join
(cost=1993678.29..11279593.98 rows=6531119 width=47) (actual
time=245906.330..1316201.213 rows=4344197
loops=3) Hash Cond:
((lineitem.l_suppkey = partsupp.ps_suppkey) AND (lineitem.l_partkey =
partsupp.ps_partkey)) -> Hash Join
(cost=273200.59..9157211.71 rows=6531119 width=45) (actual
time=5103.563..1007657.993 rows=4344197
loops=3) Hash Cond:
(lineitem.l_partkey =
part.p_partkey) -> Parallel Seq
Scan on lineitem (cost=0.00..5861332.93 rows=100005093 width=41) (actual
time=3.494..842667.110 rows=80004097
loops=3) -> Hash
(cost=263919.95..263919.95 rows=565651 width=4) (actual
time=4973.807..4973.807 rows=434469
loops=3) Buckets: 131072
Batches: 8 Memory Usage:
2933kB -> Seq Scan on
part (cost=0.00..263919.95 rows=565651 width=4) (actual
time=11.810..4837.287 rows=434469
loops=3) Filter:
((p_name)::text ~~
_%orchid%_::text)
Rows Removed by Filter: 7565531 ->
Hash (cost=1052983.08..1052983.08 rows=31999708 width=22) (actual
time=240711.936..240711.936 rows=32000000
loops=3) Buckets: 65536
Batches: 512 Memory Usage:
3941kB -> Seq Scan on partsupp
(cost=0.00..1052983.08 rows=31999708 width=22) (actual
time=0.033..228828.149 rows=32000000
loops=3) -> Hash
(cost=1704962.28..1704962.28 rows=60000728 width=8) (actual
time=253669.242..253669.242 rows=60000000
loops=3) Buckets: 131072 Batches:
1024 Memory Usage: 3316kB -> Seq
Scan on orders (cost=0.00..1704962.28 rows=60000728 width=8) (actual
time=0.038..237545.226 rows=60000000 loops=3) ->
Hash (cost=18106.56..18106.56 rows=400000 width=30) (actual
time=277.283..277.283 rows=400000 loops=3)
Buckets: 65536 Batches: 8 Memory Usage:
3549kB -> Hash Join (cost=1.56..18106.56
rows=400000 width=30) (actual time=45.155..205.372 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=45.094..129.333 rows=400000
loops=3) -> Hash (cost=1.25..1.25
rows=25 width=30) (actual time=0.038..0.038 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=0.026..0.029 rows=25 loops=3)Planning time: 2.251 msExecution time:
1674790.954 ms

--------------------------------------------------Execution plan 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