Using bitmap index scans-more efficient
| От | Kyle Bateman |
|---|---|
| Тема | Using bitmap index scans-more efficient |
| Дата | |
| Msg-id | 44DF6582.4000806@actarg.com обсуждение исходный текст |
| Ответы |
Re: Using bitmap index scans-more efficient
|
| Список | pgsql-sql |
How can I use bitmap index scans more effectively? (version 8.1.0)
I have a financial ledger (actually a view, grouping several other tables)
containing about a million records. Each record contains an account code and
a project code. I can query for all the transactions belonging to any single
project code and it is very fast and efficient (milliseconds/project).
But projects are organized in a hierarchical structure, so I also need to
query the ledger for transactions belonging to a particular project and/or all
its progeny. Depending on the method, this is taking several seconds to
several minutes per project.
For testing purposes, I'll present results using a smaller version of the
ledger with the following query times:
It is most efficient to enumerate the group of projects using "in" (0.144 seconds)
select * from ledger where proj in (4737,4789,4892,4893,4894,4895,4933,4934,4935);
---------------------------------------------------------------------------Nested Loop Left Join (cost=19.73..4164.10
rows=7width=85) -> Nested Loop (cost=19.73..4139.08 rows=7 width=81) -> Nested Loop (cost=19.73..4100.07
rows=7width=63) -> Bitmap Heap Scan on apinv_items i (cost=19.73..1185.71 rows=487 width=55)
Recheck Cond: ((proj = 4737) OR (proj = 4789) OR (proj = 4892) OR (proj = 4893) OR (proj = 4894) OR (proj = 4895)
OR(proj = 4933) OR (proj = 4934
) OR (proj = 4935)) Filter: ((status = 'en'::bpchar) OR (status = 'cl'::bpchar) OR (status =
'pd'::bpchar)) -> BitmapOr (cost=19.73..19.73 rows=495 width=0) -> Bitmap
IndexScan on i_apinv_items_proj (cost=0.00..2.19 rows=55 width=0) Index Cond: (proj =
4737) -> Bitmap Index Scan on i_apinv_items_proj (cost=0.00..2.19 rows=55 width=0)
Index Cond: (proj = 4789) -> Bitmap Index Scan on i_apinv_items_proj
(cost=0.00..2.19rows=55 width=0) Index Cond: (proj = 4892) ->
BitmapIndex Scan on i_apinv_items_proj (cost=0.00..2.19 rows=55 width=0) Index Cond:
(proj= 4893) -> Bitmap Index Scan on i_apinv_items_proj (cost=0.00..2.19 rows=55 width=0)
Index Cond: (proj = 4894) -> Bitmap Index Scan on
i_apinv_items_proj (cost=0.00..2.19 rows=55 width=0) Index Cond: (proj = 4895)
-> Bitmap Index Scan on i_apinv_items_proj (cost=0.00..2.19 rows=55 width=0)
Index Cond: (proj = 4933) -> Bitmap Index Scan on i_apinv_items_proj (cost=0.00..2.19
rows=55width=0) Index Cond: (proj = 4934) -> Bitmap Index Scan
oni_apinv_items_proj (cost=0.00..2.19 rows=55 width=0) Index Cond: (proj = 4935)
-> Index Scan using apinv_hdr_pkey on apinv_hdr h (cost=0.00..5.97 rows=1 width=21) Index
Cond:(("outer".vendid = h.vendid) AND (("outer".invnum)::text = (h.invnum)::text)) -> Index Scan using
vend_org_pkeyon vend_org v (cost=0.00..5.56 rows=1 width=26) Index Cond: (v.org_id = "outer".vendid) ->
SeqScan on acct a (cost=0.00..3.54 rows=1 width=4) Filter: ((code)::text = 'ap'::text)
---------------------------------------------------------------------------
Problem is, the project list has to be hard-coded into the SQL statement.
What I really need is transactions belonging to "project 4737 and all its progeny."
So I've tried using a many-to-many table proj_prog that describes which projects
are progeny of which other projects. Unfortunately, the query time then goes up
by a factor of 6 (to 0.85 seconds).
Examples: select * from ledger where proj = any (array(select prog_id from proj_prog where proj_id = 4737)); select *
fromledger where proj = any (array[4737,4789,4892,4893,4894,4895,4933,4934,4935]);"
---------------------------------------------------------------------------Nested Loop Left Join
(cost=13584.99..17647.39rows=850 width=85) InitPlan -> Index Scan using proj_prog_pkey on proj_prog
(cost=0.00..38.04rows=21 width=4) Index Cond: (proj_id = 4737) -> Merge Join (cost=13543.42..17565.44
rows=850width=81) Merge Cond: ("outer".vendid = "inner".org_id) -> Merge Join (cost=13543.42..17405.05
rows=850width=63) Merge Cond: (("outer".vendid = "inner".vendid) AND (("outer".invnum)::text =
"inner"."?column10?")) -> Index Scan using apinv_hdr_pkey on apinv_hdr h (cost=0.00..3148.16 rows=51016
width=21) -> Sort (cost=13543.42..13693.47 rows=60020 width=55) Sort Key: i.vendid,
(i.invnum)::text -> Seq Scan on apinv_items i (cost=0.00..7197.27 rows=60020 width=55)
Filter: (((status = 'en'::bpchar) OR (status = 'cl'::bpchar) OR (status = 'pd'::bpchar)) AND (proj = ANY
($0))) -> Index Scan using vend_org_pkey on vend_org v (cost=0.00..145.52 rows=1799 width=26) -> Materialize
(cost=3.54..3.55rows=1 width=4) -> Seq Scan on acct a (cost=0.00..3.54 rows=1 width=4) Filter:
((code)::text= 'ap'::text)
---------------------------------------------------------------------------
The worst case is the following types of queries (about 5 seconds):
select * from ledger where proj in (select prog_id from proj_prog where proj_id = 4737); select l.* from ledger l,
proj_progp where l.proj = p.prog_id and p.proj_id = 4737;
---------------------------------------------------------------------------Hash Join (cost=19032.47..23510.23 rows=6
width=85) Hash Cond: ("outer".proj = "inner".prog_id) -> Nested Loop Left Join (cost=18994.38..23378.41 rows=1700
width=85) -> Hash Join (cost=18990.84..23340.87 rows=1700 width=81) Hash Cond: ("outer".vendid =
"inner".org_id) -> Merge Join (cost=18935.35..23255.64 rows=1700 width=63) Merge Cond:
(("outer".vendid= "inner".vendid) AND (("outer".invnum)::text = "inner"."?column10?")) -> Index
Scanusing apinv_hdr_pkey on apinv_hdr h (cost=0.00..3148.16 rows=51016 width=21) -> Sort
(cost=18935.35..19235.45rows=120041 width=55) Sort Key: i.vendid, (i.invnum)::text
-> Seq Scan on apinv_items i (cost=0.00..4152.99 rows=120041 width=55)
Filter:((status = 'en'::bpchar) OR (status = 'cl'::bpchar) OR (status = 'pd'::bpchar)) -> Hash
(cost=50.99..50.99rows=1799 width=26) -> Seq Scan on vend_org v (cost=0.00..50.99 rows=1799
width=26) -> Materialize (cost=3.54..3.55 rows=1 width=4) -> Seq Scan on acct a (cost=0.00..3.54
rows=1width=4) Filter: ((code)::text = 'ap'::text) -> Hash (cost=38.04..38.04 rows=21 width=4)
-> Index Scan using proj_prog_pkey on proj_prog p (cost=0.00..38.04 rows=21 width=4) Index Cond:
(proj_id= 4737)
---------------------------------------------------------------------------
I would like to be able to get the best performance like in the first query but
without having to enumerate the projects (i.e. using a single query).
The secret seems to be the bitmap index scans.
Any ideas about whether/how this can be done?
Thanks!
Kyle Bateman
---------------------------------------------------------------------------
BTW, The ledger view is built roughly as follows:
create view rp_v_api as select h.adate as adate, (i.price *
i.quant)::numeric(14,2) as amount, substring(v.org_name from 1 for 40) as descr,
i.proj as proj, i.acct as acct, 1 as
cr_proj, a.acct_id as cr_acct
from ( apinv_hdr h join apinv_items i on i.vendid = h.vendid and i.invnum
=h.invnum join vend_org v on v.org_id = h.vendid left join acct a on
a.code = 'ap' ) where i.status in ('en','cl','pd');
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