> I have a table with the following simplified form:
>
> create table t (
> run_id integer,
> domain_id integer,
> mta_id integer,
> attribute1 integer,
> attribute2 integer,
> unique(run_id, domain_id, mta_id)
> );
>
> The table has about 1 million rows with run_id=1, another 1 million
> rows with run_id=2, and so on.
>
> I need to efficiently query the differences between "runs" - i.e. For
> each (domain_id, mta_id) tuple in run 1, is there a coresponding
> tuple in run 2 where either attribute1 or attribute2 have changed?
>
> The only way I have been able to think of doing this so far is an
> o(n^2) search, which even with indexes takes a long time. e.g.
>
> select * from t t1 where exists (select 1 from t t2 where
> t2.mta_id=t1.mta_id and t2.domain_id=t1.domain_id and (t2.attribute1
> != t1.attribute1 or t2.attribute2 != t1.attribute2)
>
> This query takes millenia...
>
first, add a change flag change_tf that is set through a trigger
whether this record different from record in the previous run. second,
create an index on domain and mta where change_tf, so you're only
indexing changed records.
this would allow you to find your changes very efficiently at the
relatively small cost of adding one lookup and one extra index per
insert.
____________________________________________________________________________________
Pinpoint customers who are looking for what you sell.
http://searchmarketing.yahoo.com/