Re: BUG #14020: row_number() over(partition by order by) - weird behavior - Mailing list pgsql-bugs
From | Boyko Yordanov |
---|---|
Subject | Re: BUG #14020: row_number() over(partition by order by) - weird behavior |
Date | |
Msg-id | 926E6EDE-8959-4209-B3F0-E894987FD4E0@gmail.com Whole thread Raw |
In response to | Re: BUG #14020: row_number() over(partition by order by) - weird behavior ("David G. Johnston" <david.g.johnston@gmail.com>) |
Responses |
Re: BUG #14020: row_number() over(partition by order by) - weird behavior
|
List | pgsql-bugs |
Hi and thanks for your time on this. You haven't proven to us that a single row in offers_testing cannot = match more than one row in offers_past_data. Assuming a 1-to-many = situation the update count for offers_past_data can definitely be more = than the number of rows returned by the sub-query. It is a one-to-one relationship between the tables as there is a primary = key on (id, feed) on both tables (which I missed to point out): Indexes: "offers_past_data_id_feed" PRIMARY KEY, btree (id, feed) Indexes: "offers_testing_id_feed" PRIMARY KEY, btree (id, feed) I assume that this guarantees that a single grossprice change in = offers_testing where product =3D 2 translates to up to (count(id,feed) = where product =3D 2) position updates in both offers_testing and = offers_past_data. Adding "returning *" to the questionable query, it seems to update rows = that are not related to product 2 (and on my opinion should not have = changed positions). Also, "ORDER BY grossprice" seems inadequate. The potential for = duplicates here - which would then make the assignment of row numbers = within the product partition random - is non-zero and is a quite likely = source of your problem - along with the probable one-to-many = relationship between offers_testing and offers_past_data. Dismissing the one-to-many relationship suggestion as it isn't the case. Your point on duplicate grossprices is valid, but I believe that if I = update a single grossprice, even in the case of duplicate grossprices, = this should not translate in more position updates than the rows in the = modified product partition. And in offers_testing there are no more than = 148 rows per product partition: db=3D# select max(partition_count) from (select count(*) over (partition = by product) as partition_count from offers_testing) sq; max ----- 148 (1 row) And yet the update query updates 28k records for some reason, most of = which are outside the modified product partition. Boyko -- Boyko 2016-03-15 6:00 GMT+02:00 David G. Johnston <david.g.johnston@gmail.com = <mailto:david.g.johnston@gmail.com>>: On Mon, Mar 14, 2016 at 1:43 PM, <b.yordanov2@gmail.com = <mailto:b.yordanov2@gmail.com>> wrote: db=3D# update offers_past_data a set position =3D b.position from = (select id, feed, row_number() over(partition by product order by grossprice asc) as position from offers_testing) b where a.id <http://a.id/> =3D b.id = <http://b.id/> and a.feed =3D b.feed and a.position <> b.position; UPDATE 0 =E2=80=8BUpdating offers_past_data =E2=80=8B=20 This should update every row in offers_past_data when its =E2=80=9Cpositio= n=E2=80=9D changes. In the example above no changes were introduced since the last = run so nothing is updated (expected). db=3D# select count(*) from offers_testing where product =3D 2; count ------- 99 (1 row) So there are 99 offers for product 2. =E2=80=8BCounting offers_testing=E2=80=8B Getting a single offer: db=3D# select id,grossprice from offers_testing where product =3D 2 = limit 1; id | grossprice ---------+------------ 4127918 | 5000.00 (1 row) =E2=80=8BCounting offers_testing=E2=80=8B Updating its grossprice: db=3D# update offers_testing set grossprice =3D 20 where id =3D 4127918; UPDATE 1 =E2=80=8BUpdating offers_testing=E2=80=8B Now when executing the first query again I expect that no more than 99 = rows get updated in offers_past_data since this is the maximum amount of positions that would be affected by offer 4127918 grossprice change. You haven't proven to us that a single row in offers_testing cannot = match more than one row in offers_past_data. Assuming a 1-to-many = situation the update count for offers_past_data can definitely be more = than the number of rows returned by the sub-query. =E2=80=8B=E2=80=8B db=3D# update offers_past_data a set position =3D b.position from = (select id, feed, row_number() over(partition by product order by grossprice asc) as position from offers_testing) b where a.id <http://a.id/> =3D b.id = <http://b.id/> and a.feed =3D b.feed and a.position <> b.position; UPDATE 104 104 rows get updated. Executing the same query again a few minutes later (no changes meanwhile = in either table): db=3D# update offers_past_data a set position =3D b.position from = (select id, feed, row_number() over(partition by product order by grossprice asc) as position from offers_testing) b where a.id <http://a.id/> =3D b.id = <http://b.id/> and a.feed =3D b.feed and a.position <> b.position; UPDATE 28058 This time it updates 28058 rows. This is a test environment and nothing reads or writes to these tables. Is this a bug or am I missing something obvious? =E2=80=8BIts likely data related, not a bug. Using the "UPDATE ... RETURNING *" form should provide good insight. = Specifically, look for all rows having the same (id, feed) pair. Also, "ORDER BY grossprice" seems inadequate. The potential for = duplicates here - which would then make the assignment of row numbers = within the product partition random - is non-zero and is a quite likely = source of your problem - along with the probable one-to-many = relationship between offers_testing and offers_past_data. David J. =E2=80=8B=20
pgsql-bugs by date: