PostgreSQL – Group By Month with Overlapping Years

You seem to be misinterpreting a part of my advice to your previous question:

so I can not Truncate and rename the temp_tables since the system should be on all the time.

There was no renaming involved. After TRUNCATE you run an INSERT. The only blocking operation is the TRUNCATE. I quote the manual:

TRUNCATE acquires an ACCESS EXCLUSIVE lock on each table it operates on, which blocks all other concurrent operations on the table. (...) If concurrent access to a table is required, then the DELETE command should be used instead.

INSERT may still work, if it is not time-critical and allowed to wait until the lock is released. TRUNCATE is usually very fast, if you run it in a separate transaction, it should only block for a couple of milliseconds. Note: separate transaction, not separate session! Your temporary table lives and dies with the session.

The drawback of a separate transaction: if you lose your session before you are able to re-insert from the temporary table, you loose data. To be sure, you could use a plain table instead. (Which would offer the alternative path to drop the old and rename the new table.)

Either way, your updated question makes clear that you want to run this repeatedly, accumulating old rows in the same table. In this case, TRUNCATE is not a good option anyway. You can always just use a plain DELETE. Considerably slower with big tables, but concurrent INSERT is not blocked at all. The autovacuuming daemon will have to do some more work, too.

It's mostly a trade-off between speed and security.

SQL

The DELETE command for the slow and sure method could look like this:

DELETE FROM TABLE tbl t
USING (
   SELECT created_at FROM tbl WHERE created_at < now() - (interval '3 month')
   ) d
LEFT   JOIN (
   SELECT min(created_at) AS created_at
   FROM   tbl
   GROUP  BY date_trunc('minute', created_at)
   WHERE  created_at < now() - (interval '3 month')
   ) x USING (created_at)
WHERE  x.created_at IS NULL
AND    d.created_at = t.created_at;

You need to do a left outer join on the generate_series with an ON clause that matches the date of each report.

Without a schema or sample data it's a bit fiddly to cook up an example modification of your actual query.

Here's a simplified example to show you how it works:

CREATE TABLE sparse_dates(
    bakedgood text primary key,
    firstbaked date not null
);

INSERT INTO sparse_dates (bakedgood, firstbaked) VALUES
('tart', '2012-02-01'),
('baguette', '2012-02-01'),
('cookie', '2012-03-01'),
('macaron', '2012-08-01');

To get the number of baked goods first baked on a given month:

SELECT monthtimestamp, count(bakedgood) 
FROM generate_series( 
    (SELECT min(firstbaked) FROM sparse_dates),
    (SELECT max(firstbaked) FROM sparse_dates),
    INTERVAL '1' MONTH) 
    AS monthtimestamp
LEFT OUTER JOIN sparse_dates ON (monthtimestamp = firstbaked)
GROUP BY monthtimestamp;

with output like:

     monthtimestamp     | count 
------------------------+-------
 2012-02-01 00:00:00+08 |     2
 2012-03-01 00:00:00+08 |     1
 2012-04-01 00:00:00+08 |     0
 2012-05-01 00:00:00+08 |     0
 2012-06-01 00:00:00+08 |     0
 2012-07-01 00:00:00+08 |     0
 2012-08-01 00:00:00+08 |     1
(7 rows)