On Wed, 15 Sep 2010, Merlin Moncure wrote:
> On Wed, Sep 15, 2010 at 2:32 AM, Gerhard Wiesinger <lists@wiesinger.com> wrote:
>> On Tue, 14 Sep 2010, Merlin Moncure wrote:
>>>
>>> np -- this felt particularly satisfying for some reason. btw, I think
>>> you have some more low hanging optimization fruit. I think (although
>>> it would certainly have to be tested) hiding your attribute
>>> description under keyid is buying you nothing but headaches. If you
>>> used natural key style, making description primary key of
>>> key_description (or unique), and had log_details have a description
>>> column that directly referenced that column, your subquery:
>>>
>>> (
>>> SELECT value FROM log_details d WHERE l.id = d.fk_id AND d.fk_keyid =
>>> (
>>> SELECT keyid FROM key_description WHERE description =
>>> 'Kesselsolltemperatur'
>>> )
>>> ) AS Kesselsolltemperatur,
>>>
>>> would look like this:
>>> (
>>> SELECT value FROM log_details d WHERE l.id = d.fk_id AND
>>> d.description = 'Kesselsolltemperatur'
>>> ) AS Kesselsolltemperatur,
>>>
>>> your index on log_details(fk_id, description) is of course fatter, but
>>> quite precise...does require rebuilding your entire dataset however.
>>> food for thought.
>>
>> I think your suggestion might be slower because the WHERE clause and
>> possible JOINS with BIGINT is much faster (especially when a lot of data is
>> queried) than with a VARCHAR. With the latest query plan key_description is
>> only queried once per subselect which is perfect. I've also chosen that
>> indirection that I can change description without changing too much in data
>> model and all data rows on refactoring.
>
> You're not joining -- you're filtering (and your assumption that
> bigint is always going to be faster is quite debatable depending on
> circumstances). The join is skipped because of the key (yes, it's
> cheap lookup, but w/50 columns each doing it, nothing is cheap).
I know that I'm not JOINing in that case - as discussed I ment possible
JOINs in other query scenarios.
BTW: Latest query plan is also optimal that only the
used columns from the view are evaluated. With the full joined version
all columns where used even when dropped in the result-set, e.g.:
SELECT col1, col2 FROM view1; -- Equivalent to SELECT * FROM view1; as col1, col2 are all colums in that view
SELECT col1 FROM view1; -- less effort with subselects when less columns are needed, joins have same "full view" effort
here
Ciao,
Gerhard
--
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