You can do much with window functions. Presenting two solutions: one with and one without materialized view.
Test case
Building on this table:
CREATE TABLE hotel_data (
hotel_id int
, day date -- using "day", not "date"
, spaces int
, price int
, PRIMARY KEY (hotel_id, day) -- provides essential index automatically
);
Days per hotel_id
must be unique (enforced by PK here), or the rest is invalid.
Multicolumn index for base table:
CREATE INDEX mv_hotel_mult_idx ON mv_hotel (day, hotel_id);
Note the reversed order as compared to the PK. You will probably need both indexes, for the following query, the 2nd index is essential. Detailed explanation:
Direct query without MATERIALIZED VIEW
SELECT hotel_id, day, sum_price
FROM (
SELECT hotel_id, day, price, spaces
, sum(price) OVER w * 2 AS sum_price
, min(spaces) OVER w AS min_spaces
, last_value(day) OVER w - day AS day_diff
, count(*) OVER w AS day_ct
FROM hotel_data
WHERE day BETWEEN '2014-01-01'::date AND '2014-01-31'::date
AND spaces >= 2
WINDOW w AS (PARTITION BY hotel_id ORDER BY day
ROWS BETWEEN CURRENT ROW AND 3 FOLLOWING) -- adapt to nights - 1
) sub
WHERE day_ct = 4
AND day_diff = 3 -- make sure there is not gap
AND min_spaces >= 2
ORDER BY sum_price, hotel_id, day;
-- LIMIT 1 to get only 1 winner;
Also see @ypercube's variant with lag()
, which can replace day_ct
and day_diff
with a single check.
How?
In the subquery, only consider days within your time frame ("in January" means, the last day is included in the time frame).
The frame for the window functions spans the current row plus the next num_nights - 1
(4 - 1 = 3
) rows (days). Calculate the difference in days , the count of rows and the minimum of spaces to make sure the range is long enough, gapless and always has enough spaces.
- Unfortunately, the frame clause of window functions does not accept dynamic values, so
ROWS BETWEEN CURRENT ROW AND 3 FOLLOWING`
cannot be parameterized for a prepared statement.
I carefully drafted all window functions in the subquery to reuse the same window, using a single sort step.
The resulting price sum_price
is already multiplied by the number of spaces requested.
To avoid inspecting many rows without chance of success, save only the columns you need plus three redundant, calculated values from the base table. Be sure the MV is up to date. If you are not familiar with the concept, read the manual first.
CREATE MATERIALIZED VIEW mv_hotel AS
SELECT hotel_id, day
, first_value(day) OVER (w ORDER BY day) AS range_start
, price, spaces
,(count(*) OVER w)::int2 AS range_len
,(max(spaces) OVER w)::int2 AS max_spaces
FROM (
SELECT *
, day - row_number() OVER (PARTITION BY hotel_id ORDER BY day)::int AS grp
FROM hotel_data
) sub1
WINDOW w AS (PARTITION BY hotel_id, grp);
range_start
stores the first day of each continuous range for two purposes:
- to mark a set of rows as members of a common range
- to show the start of the range for possible other purposes.
range_len
is the number of days in the gapless range.
max_spaces
is the maximum of open spaces in the range.
- Both columns are used to exclude impossible rows from the query immediately.
I cast both to smallint
( max. 32768 should be plenty for both) to optimize storage: only 52 bytes per row (incl. heap tuple header and item identifier). Details:
Multicolumn index for MV:
CREATE INDEX mv_hotel_mult_idx ON mv_hotel (range_len, max_spaces, day);
Query based on MV
SELECT hotel_id, day, sum_price
FROM (
SELECT hotel_id, day, price, spaces
, sum(price) OVER w * 2 AS sum_price
, min(spaces) OVER w AS min_spaces
, count(*) OVER w AS day_ct
FROM mv_hotel
WHERE day BETWEEN '2014-01-01'::date AND '2014-01-31'::date
AND range_len >= 4 -- exclude impossible rows
AND max_spaces >= 2 -- exclude impossible rows
WINDOW w AS (PARTITION BY hotel_id, range_start ORDER BY day
ROWS BETWEEN CURRENT ROW AND 3 FOLLOWING) -- adapt to $nights - 1
) sub
WHERE day_ct = 4
AND min_spaces >= 2
ORDER BY sum_price, hotel_id, day;
-- LIMIT 1 to get only 1 winner;
This is faster than the query on the table because more rows can be eliminated immediately. Again, the index is essential. Since partitions are gapless here, checking day_ct
is enough.
SQL Fiddle demonstrating both.
Repeated use
If you use it a lot, I would create an SQL function and only pass parameters. Or a PL/pgSQL function with dynamic SQL and EXECUTE
to allow adapting the frame clause.
Alternative
Range types with date_range
to store continuous ranges in a single row might be an alternative - complicated in your case with potential variations on prices or spaces per day.
Related:
Your questions, with my responses:
- Does event_config need a reference to event via event_id? It makes sense to know to which event the config belongs to, but at the same time it feels redundant since it's implicit from the relationship with dates.
Adding the event_id to the event_config table allows you to easily design a user-interface for modifying the event_config table, without needing a complex reference to an actual event instance. This might be useful for "default" configs.
This also allows an easier code path for presenting data to the user prior to the user choosing a date.
- Isn't event_config an unneeded complexity? Its sole purpose is to provide shared fields to event_date and event_recurrence. Wouldn't it be better just to have the price and capacity columns both in date and recurrence?
event_config
looks like a good optimization to me. I see it as a way to manage configurations independently of specific events in time. For instance, you might have a "holiday" config, a config for each weekday, and a config for "saturday" and "sunday", each of which might be exactly the same for each and every event that occurs on those days. Why duplicate that data by storing the info in event_date
and event_recurrence
?
Best Answer
generate_series()
returns aSETOF
dates between the first and second argument, at intervals specified by the third argument. Seems to be what you're looking for.