Optimizing multiple joins

Question

I\'m trying to figure out a way to speed up a particularly cumbersome query which aggregates some data by date across a couple of tables. The full (ugly) query is below along w

Answer 1

I uninstalled my PostgreSQL server a couple of days ago, so you'll likely have to play around with this, but hopefully it's a good start for you.

The keys are:

1. You shouldn't need the subqueries - just do the direct joins and aggregate
2. You should be able to use INNER JOINs, which are typically more performant than OUTER JOINs

If nothing else, I think that the query below is a bit clearer.

I used a calendar table in my query, but you can replace that with the generate_series as you were using it.

Also, depending on indexing, it might be better to compare the body_date with >= and < rather than pulling out the date part and comparing. I don't know enough about PostgreSQL to know how it works behind the scenes, so I would try both approaches to see which the server can optimize better. In pseudo-code you would be doing: body_date >= date (time=midnight) AND body_date < date + 1 (time=midnight).

SELECT
    CAL.calendar_date AS period,
    SUM(O.body_size) AS outbound,
    SUM(I.body_size) AS inbound
FROM
    Calendar CAL
INNER JOIN Body OB ON
    OB.body_time::date = CAL.calendar_date
INNER JOIN Envelope OE ON
    OE.message_id = OB.message_id AND
    OE.envelope_command = 1
INNER JOIN Body IB ON
    IB.body_time::date = CAL.calendar_date
INNER JOIN Envelope IE ON
    IE.message_id = IB.message_id AND
    IE.envelope_command = 2
GROUP BY
    CAL.calendar_date