PostgreSQL Aggregates with Multiple Parameters

问题

I've been trying to wrap my head around creating aggregates in PostgreSQL (either 8.4 or 9.1) that accept one or more option parameters.

An example would be creating a PL/R extension to compute the p-th quantile, with 0 <= p <= 1. This would look something like quantile(x,p), and as part of a query:

select category,quantile(x,0.25)
from TABLE
group by category
order by category;

Where TABLE (category:text, x:float).

Suggestions?

回答1:

Hopefully this example will help. You need a function that takes (accumulator, aggregate-arguments) and returns the new accumulator value. Play around with the code below and that should give you a feel for how it all fits together.

BEGIN;

CREATE FUNCTION sum_product_fn(int,int,int) RETURNS int AS $$
    SELECT $1 + ($2 * $3);
$$ LANGUAGE SQL;           

CREATE AGGREGATE sum_product(int, int) (
    sfunc = sum_product_fn,
    stype = int, 
    initcond = 0
);

SELECT 
    sum(i) AS one,     
    sum_product(i, 2) AS double,
    sum_product(i,3) AS triple
FROM generate_series(1,3) i;

ROLLBACK;

That should give you something like:

 one | double | triple 
-----+--------+--------
   6 |     12 |     18

回答2:

This can be achieved with the ntile windowing function

-- To calculate flexible quantile ranges in postgresql, for example to calculate n equal 
-- frequency buckets for your data for use in a visualisation (such as binning for a 
-- choropleth map), you can use the following SQL:

-- this functions returns 6 equal frequency bucket ranges for my_column.
SELECT ntile, avg(my_column) AS avgAmount, max(my_column) AS maxAmount, min(my_column) AS     minAmount 
FROM (SELECT my_column, ntile(6) OVER (ORDER BY my_column) AS ntile FROM my_table) x
GROUP BY ntile ORDER BY ntile

You can find more on the ntile() function and windowing at http://database-programmer.blogspot.com/2010/11/really-cool-ntile-window-function.html

来源：https://stackoverflow.com/questions/8529985/postgresql-aggregates-with-multiple-parameters

标签

postgresql

aggregates