Re: time series query

Would it speed things up siginficantly if you set the dtval_smaller()
function to be immutable? Volatile is the default, so it may be
redundantly evaluating things.

Jaime Silvela wrote:
> In case anyone is interested, I was able to solve this, more or less.
> Here's my new "Latest value" query:
>
> select obj_id, val_type_id, (max(row(observation_date, val))).val
> from measurements
> group by obj_id, val_type_id
>
> It was only necessary to define a new (date, numeric) type. Below is the
> code. The performance is actually slower than using a JOIN between the
> table and its GROUP-BY version. I guess for performance, I should code
> the functions in C, but at the moment, the value for me is that it
> simplifies a lot of my 12-way join queries!
>
> create type dtval as (
> dt date,
> val numeric
> );
>
> create function dtval_smaller(dtval, dtval) returns dtval as $$
> select case when $1.dt < $2.dt then $1 else $2 end
> $$ language sql;
>
> create aggregate min (
> sfunc = dtval_smaller,
> basetype = dtval,
> stype = dtval
> );
>
> create function dtval_larger(dtval, dtval) returns dtval as $$
> select case when $1.dt > $2.dt then $1 else $2 end
> $$ language sql;
>
> create aggregate max (
> sfunc = dtval_larger,
> basetype = dtval,
> stype = dtval
> );
>
>
>
> Jaime Silvela wrote:
>> The problem I'm trying to solve is pretty standard. I have a table
>> that records measurements of different types at different times.
>>
>> CREATE TABLE measurements (
>> obj_id int4,
>> val_type_id int4 references lu_val_type(val_type_id),
>> val numeric,
>> observation_date date
>> );
>>
>> I want a query as simple and fast as possible to return the latest
>> observation of each type for each object.
>> I sent a message to this list a while ago, and the suggestion I found
>> to be the best compromise of clarity and speed was:
>> a) create an index on (obj_id, val_type_id, observation_date)
>> b) the "obvious" query becomes fast thanks to the index.
>> select ms.*
>> from (
>> select obj_id, val_type_id, max(observation_date) as
>> observation_date
>> from measurements
>> group by obj_id, val_type_id
>> ) ms_last
>> join measurements ms using (obj_id, val_type_id, observation_date);
>>
>> It still bugged me a bit that this requires a JOIN, especially since
>> in a procedural language, it would have been so easy to return the
>> value associated with the max(observation_date).
>> I think I've found a pretty good alternative. This at the moment works
>> if we keep track of time with an integer, rather than a date, but it
>> would be readily extensible.
>>
>> The idea is to in fact, associate the value with the
>> max(observation_date) like so:
>> select obj_id, val_type_id, max(array[observation_date, val])
>> group by obj_id, val_type_id;
>>
>> There are two caveats:
>> a) array requires elements to be of the same type, so observation_type
>> must be kept as "time from"
>> b) a row constructor would be ideal here, but there is now max
>> function for rowtypes.
>>
>> If I did have a max() function for row types, it would be clean to do
>> this:
>> select obj_id, val_type_id, max(row(observation_date, val))
>> group by obj_id, val_type_id;
>>
>> Now, it seems that since rowtype comparison is built in, it should be
>> pretty easy to build a max() aggregate for it. Has anybody done this?
>> I'd have looked at the code for max(anyarray) but I don't know how to
>> access it. Can someone point me in the right direction?
>>
>> Also, has someone thought about this before? I'm wondering if there
>> will be a speed gain coming from this.
>>
>> Thank you,
>> Jaime
>>
>>
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>
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