PostgreSQL – Array Exceeds Allowed Size

arraypostgresql

I have a function that accepts as parameter an array like:

CREATE OR REPLACE FUNCTION my_func(some_data custom_datum[]) RETURNS VOID AS $$
    BEGIN
        create table foo_table as (

           select
           coalesce(foo_ind, bar_ind, ter_ind) as foobarter,
           import_date,

           -- do some stuff here

           from unnest (some_data) as T
           group by grouping sets ((foo_ind, import_date), (bar_ind, import_date), (ter_ind, import_date))
        );
    END
$$ LANGUAGE plpgsql;

The input array is generated by another function foo. So I call everything in this way:

select my_func(array(select foo()));

where the function foo is:

CREATE OR REPLACE FUNCTION foo() RETURNS SETOF custom_datum

The problem is that for a big amount of data array(select foo()) returns:

ERROR: array size exceeds the maximum allowed (1073741823)

What I am trying to workaround is the lack of possibility to pass different functions, as at the moment, the input array gets generated by different functions:

select my_func(array(select foo()));
select my_func(array(select bar()));
select my_func(array(select ter()));
.... etc

How can I workaround this problem?

Best Answer

What your my_func is essentially doing is creating a MATERIALIZED VIEW -- a materialized view is a cached copy of a result set stored as a table. Drop the function and use the normal MATERIALIZED VIEW.

Skip generating an array -- waste of a time and space and may even be serializing the result set to disk twice. And, instead, just use something like this:

CREATE MATERIALIZED VIEW foo_view
AS
  SELECT whatever
  FROM wherever
  GROUP BY GROUPING SETS (
    (foo_ind, import_date),
    (bar_ind, import_date),
    (ter_ind, import_date)
  );

Now you can "refresh" this by doing REFRESH foo_view;

Related Solutions

PostgreSQL – Concatenating SETOF Type or SETOF Record

The approach you're using is unnecessarily complex - and very inefficient. Instead of the first function use:

create or replace function compute_pair_id_value(id bigint, value integer)
    returns setof pair_id_value
as $$
SELECT $1, generate_series(0,$2);
$$                          
language sql;

or better, get rid of it entirely and write the whole operation like this:

-- Sample data creation:
CREATE TABLE my_obj(id bigint, obj_value integer);
insert into my_obj(id,obj_value) VALUES (1712437,2),(17000,5);

-- and the query:
SELECT id, generate_series(0,obj_value) FROM my_obj;

Resulting in:

regress=> SELECT id, generate_series(0,obj_value) FROM my_obj;
   id    | generate_series 
---------+-----------------
 1712437 |               0
 1712437 |               1
 1712437 |               2
   17000 |               0
   17000 |               1
   17000 |               2
   17000 |               3
   17000 |               4
   17000 |               5
(9 rows)

This exploits PostgreSQL's behaviour with set-returning functions called in the SELECT list. Once PostgreSQL 9.3 comes out it can be replaced with a standards-compliant LATERAL query.

Since it turns out your question was a simplified version of the real problem, let's tackle that. I'll work with the simplified compute_pair_id_value above to avoid the hassle of plpython3. Here's how to do what you want:

SELECT (compute_pair_id_value(id,obj_value)).* FROM my_obj;

Result:

regress=> SELECT (compute_pair_id_value(id,obj_value)).* FROM my_obj;
   id    | value 
---------+-------
 1712437 |     0
 1712437 |     1
 1712437 |     2
   17000 |     0
   17000 |     1
   17000 |     2
   17000 |     3
   17000 |     4
   17000 |     5
(9 rows)

but again, be warned that compute_pair_id_value will be called more than once. This is a limitation of PostgreSQL's query executor that can be avoided in 9.3 with LATERAL support, but as far as I know you're stuck with it in 9.2 and below. Observe:

create or replace function compute_pair_id_value(id bigint, value integer)
    returns setof pair_id_value
as $$
BEGIN
  RAISE NOTICE 'compute_pair_id_value(%,%)',id,value;
  RETURN QUERY SELECT $1, generate_series(0,$2);
END;
$$             
language plpgsql;

output:

regress=> SELECT (compute_pair_id_value(id,obj_value)).* FROM my_obj;
NOTICE:  compute_pair_id_value(1712437,2)
NOTICE:  compute_pair_id_value(1712437,2)
NOTICE:  compute_pair_id_value(17000,5)
NOTICE:  compute_pair_id_value(17000,5)
   id    | value 
---------+-------
 1712437 |     0
 1712437 |     1
 1712437 |     2
   17000 |     0
   17000 |     1
   17000 |     2
   17000 |     3
   17000 |     4
   17000 |     5
(9 rows)

See how compute_pair_id_value is called once per output column?

There is a workaround: Another layer of subquery to unpack the composite type result. See:

regress=> SELECT (val).* FROM (SELECT compute_pair_id_value(id,obj_value) FROM my_obj) x(val);
NOTICE:  compute_pair_id_value(1712437,2)
NOTICE:  compute_pair_id_value(17000,5)
   id    | value 
---------+-------
 1712437 |     0
 1712437 |     1
 1712437 |     2
   17000 |     0
   17000 |     1
   17000 |     2
   17000 |     3
   17000 |     4
   17000 |     5
(9 rows)

You can use the same technique in your code if you really must LOOP over the results (it's slow to do that, so avoid it if you can).

PostgreSQL – Is There a Type-Safe first() Aggregate Function?

`DISTINCT ON()`

Just as a side note, this is precisely what DISTINCT ON() does (not to be confused with DISTINCT)

SELECT DISTINCT ON ( expression [, ...] ) keeps only the first row of each set of rows where the given expressions evaluate to equal. The DISTINCT ON expressions are interpreted using the same rules as for ORDER BY (see above). Note that the "first row" of each set is unpredictable unless ORDER BY is used to ensure that the desired row appears first. For example

So if you were to write,

SELECT myFirstAgg(z)
FROM foo
GROUP BY x,y;

It's effectively

SELECT DISTINCT ON(x,y) z
FROM foo;
-- ORDER BY z;

In that it takes the first z. There are two important differences,

You can also select other columns at no cost of further aggregation..

SELECT DISTINCT ON(x,y) z, k, r, t, v
FROM foo;
-- ORDER BY z, k, r, t, v;

Because there is no GROUP BY you can not use (real) aggregates with it.

CREATE TABLE foo AS
SELECT * FROM ( VALUES
  (1,2,3),
  (1,2,4),
  (1,2,5)
) AS t(x,y,z);

SELECT DISTINCT ON (x,y) z, sum(z)
FROM foo;

-- fails, as you should expect.
SELECT DISTINCT ON (x,y) z, sum(z)
FROM foo;

-- would not otherwise fail.
SELECT myFirstAgg(z), sum(z)
FROM foo
GROUP BY x,y;

Don't forget `ORDER BY`

Also, while I didn't bold it then I will now

Note that the "first row" of each set is unpredictable unless ORDER BY is used to ensure that the desired row appears first. For example

Always use an ORDER BY with DISTINCT ON

Using an Ordered-Set Aggregate Function

I imagine a lot of people are looking for first_value, Ordered-Set Aggregate Functions. Just wanted to throw that out there. It would look like this, if the function existed:

SELECT a, b, first_value() WITHIN GROUP (ORDER BY z)    
FROM foo
GROUP BY a,b;

But, alas you can do this.

SELECT a, b, percentile_disc(0) WITHIN GROUP (ORDER BY z)   
FROM foo
GROUP BY a,b;