From: | Boyko Yordanov <b(dot)yordanov2(at)gmail(dot)com> |
---|---|
To: | "David G(dot) Johnston" <david(dot)g(dot)johnston(at)gmail(dot)com> |
Cc: | pgsql-bugs(at)postgresql(dot)org |
Subject: | Re: BUG #14020: row_number() over(partition by order by) - weird behavior |
Date: | 2016-03-15 08:20:25 |
Message-ID: | 926E6EDE-8959-4209-B3F0-E894987FD4E0@gmail.com |
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Thread: | |
Lists: | 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 = 2 translates to up to (count(id,feed) where product = 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=# 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(dot)g(dot)johnston(at)gmail(dot)com <mailto:david(dot)g(dot)johnston(at)gmail(dot)com>>:
On Mon, Mar 14, 2016 at 1:43 PM, <b(dot)yordanov2(at)gmail(dot)com <mailto:b(dot)yordanov2(at)gmail(dot)com>> wrote:
db=# update offers_past_data a set position = 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/> = b.id <http://b.id/> and a.feed = b.feed and
a.position <> b.position;
UPDATE 0
Updating offers_past_data
This should update every row in offers_past_data when its “position”
changes. In the example above no changes were introduced since the last run
so nothing is updated (expected).
db=# select count(*) from offers_testing where product = 2;
count
-------
99
(1 row)
So there are 99 offers for product 2.
Counting offers_testing
Getting a single offer:
db=# select id,grossprice from offers_testing where product = 2 limit 1;
id | grossprice
---------+------------
4127918 | 5000.00
(1 row)
Counting offers_testing
Updating its grossprice:
db=# update offers_testing set grossprice = 20 where id = 4127918;
UPDATE 1
Updating offers_testing
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.
db=# update offers_past_data a set position = 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/> = b.id <http://b.id/> and a.feed = 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=# update offers_past_data a set position = 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/> = b.id <http://b.id/> and a.feed = 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?
Its 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.
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