EXPLAIN EXTENDED

From Stack Overflow:

I have a query like this:

SELECT  EXTRACT(WEEK FROM j.updated_at) as "week",  count(j.id)
FROM    jobs
WHERE   EXTRACT(YEAR FROM j.updated_at)=2009
GROUP BY
EXTRACT(WEEK FROM j.updated_at)
ORDER BY
week

, which works fine, but I only want to show the last 12 weeks.

LIMIT 12 works, but only gives me the first twelve and I need the order to be in sequential week order (i. e. not reversed) for charting purposes.

To select last 12 rows in ascending order it's enough to select first 12 rows in descending order and resort them in a subquery:

SELECT  *
FROM    (
SELECT  EXTRACT(week FROM updated_at) AS week, COUNT(*) AS cnt
FROM    jobs
WHERE   EXTRACT(year FROM updated_at) = 2008
GROUP BY
week
ORDER BY
week DESC
LIMIT 12
) q
ORDER BY
week

However, this is rather inefficient. This query selects and aggregate all the year data just to fetch 12 last weeks.

More than that, EXTRACT(year FROM updated) is not a sargable predicate, and all table rows (or index rows) need to be examined.

On a sample table of 1,000,000 rows, this query runs for more that 3.5 seconds:

SELECT  *
FROM    (
SELECT  EXTRACT(week FROM updated) AS week, COUNT(*) AS cnt
FROM    t_week
WHERE   EXTRACT(year FROM updated) = 2008
GROUP BY
week
ORDER BY
week DESC
LIMIT 12
) q
ORDER BY
week

Sort  (cost=58517.44..58517.47 rows=11 width=16)
  Sort Key: (date_part('week'::text, t_week.updated))
  ->  Limit  (cost=58517.11..58517.14 rows=11 width=8)
        ->  Sort  (cost=58517.11..58517.14 rows=11 width=8)
              Sort Key: (date_part('week'::text, t_week.updated))
              ->  HashAggregate  (cost=58516.75..58516.92 rows=11 width=8)
                    ->  Seq Scan on t_week  (cost=0.00..58491.75 rows=5000 width=8)
                          Filter: (date_part('year'::text, updated) = 2008::double precision)

However, this query can be easily improved. For each year, we can easily calculate the beginning and the end of each of last 12 weeks, and use these values in a more index-friendly query.

Let's create a sample table and see how to do this:

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