Optimizing queries on a range of timestamps (two columns) I use PostgreSQL 9.1 on Ubuntu 12.04.

I need to select records inside a range of time: my table time_limits has two timestamp fields and one integer property. There are additional columns in my actual table that are not involved with this query.

create table (
   start_date_time timestamp,
   end_date_time timestamp, 
   id_phi integer, 
   primary key(start_date_time, end_date_time,id_phi);


This table contains roughly 2M records.

Queries like the following took enormous amounts of time:

select * from time_limits as t 
where t.id_phi=0 
and t.start_date_time &lt;= timestamp'2010-08-08 00:00:00'
and t.end_date_time   &gt;= timestamp'2010-08-08 00:05:00';


So I tried adding another index - the inverse of the PK:

create index idx_inversed on time_limits(id_phi, start_date_time, end_date_time);


I got the impression that performance improved: The time for accessing records in the middle of the table seems to be more reasonable: somewhere between 40 and 90 seconds.

But it's still several tens of seconds for values in the middle of the time range. And twice more when targeting the end of the table (chronologically speaking).

I tried explain analyze for the first time to get this query plan:

 Bitmap Heap Scan on time_limits  (cost=4730.38..22465.32 rows=62682 width=36) (actual time=44.446..44.446 rows=0 loops=1)
   Recheck Cond: ((id_phi = 0) AND (start_date_time &lt;= '2011-08-08 00:00:00'::timestamp without time zone) AND (end_date_time &gt;= '2011-08-08 00:05:00'::timestamp without time zone))
   -&gt;  Bitmap Index Scan on idx_time_limits_phi_start_end  (cost=0.00..4714.71 rows=62682 width=0) (actual time=44.437..44.437 rows=0 loops=1)
         Index Cond: ((id_phi = 0) AND (start_date_time &lt;= '2011-08-08 00:00:00'::timestamp without time zone) AND (end_date_time &gt;= '2011-08-08 00:05:00'::timestamp without time zone))
 Total runtime: 44.507 ms


See the results on depesz.com.

What could I do to optimize the search? You can see all the time is spent scanning the two timestamps columns once id_phi is set to 0. And I don't understand the big scan (60K rows!) on the timestamps. Aren't they indexed by the primary key and idx_inversed I added?

Should I change from timestamp types to something else?

I have read a little about GIST and GIN indexes. I gather they can be more efficient on certain conditions for custom types. Is it a viable option for my use case?
For Postgres 9.1 or later:
CREATE INDEX idx_time_limits_ts_inverse
ON time_limits (id_phi, start_date_time, end_date_time DESC);
In most cases the sort order of an index is hardly relevant. Postgres can scan backwards practically as fast. But for range queries on multiple columns it can make a huge difference. Closely related:

PostgreSQL index not used for query on range

Consider your query:
SELECT *
FROM   time_limits
WHERE  id_phi = 0
AND    start_date_time &lt;= '2010-08-08 00:00'
AND    end_date_time   &gt;= '2010-08-08 00:05';

Sort order of the first column id_phi in the index is irrelevant. Since it's checked for equality (=), it should come first. You got that right. More in this related answer:

Multicolumn index and performance

Postgres can jump to id_phi = 0 in next to no time and consider the following two columns of the matching index. These are queried with range conditions of inverted sort order (&lt;=, &gt;=). In my index, qualifying rows come first. Should be the fastest possible way with a B-Tree index1:

You want start_date_time &lt;= something: index has the earliest timestamp first.
If it qualifies, also check column 3.
Recurse until the first row fails to qualify (super fast).
You want end_date_time &gt;= something: index has the latest timestamp first.
If it qualifies, keep fetching rows until the first one doesn't (super fast).
Continue with next value for column 2 ..

Postgres can either scan forward or backward. The way you had the index, it has to read all rows matching on the first two columns and then filter on the third. Be sure to read the chapter Indexes and ORDER BY in the manual. It fits your question pretty well.
How many rows match on the first two columns?
Only few with a start_date_time close to the start of the time range of the table. But almost all rows with id_phi = 0 at the chronological end of the table! So performance deteriorates with later start times.
Planner estimates
The planner estimates rows=62682 for your example query. Of those, none qualify (rows=0). You might get better estimates if you increase the statistics target for the table. For 2.000.000 rows ...
ALTER TABLE time_limits ALTER start_date_time SET STATISTICS 1000;
ALTER TABLE time_limits ALTER end_date_time   SET STATISTICS 1000;

... might pay. Or even higher. More in this related answer:

Check statistics targets in PostgreSQL

I guess you don't need that for id_phi (only few distinct values, evenly distributed), but for the timestamps (lots of distinct values, unevenly distributed).
I also don't think it matters much with the improved index.
CLUSTER / pg_repack / pg_squeeze
If you want it faster, yet, you could streamline the physical order of rows in your table. If you can afford to lock your table exclusively (at off hours for instance), rewrite your table and order rows according to the index with CLUSTER:
CLUSTER time_limits USING idx_time_limits_inversed;

Or consider pg_repack or the later pg_squeeze, which can do the same without exclusive lock on the table.
Either way, the effect is that fewer blocks need to be read from the table and everything is pre-sorted. It's a one-time effect deteriorating over time with writes on the table fragmenting the physical sort order.
GiST index in Postgres 9.2+
1 With pg 9.2+ there is another, possibly faster option: a GiST index for a range column.

There are built-in range types for timestamp and timestamp with time zone: tsrange, tstzrange. A btree index is typically faster for an additional integer column like id_phi. Smaller and cheaper to maintain, too. But the query will probably still be faster overall with the combined index.

Change your table definition or use an expression index.

For the multicolumn GiST index at hand you also need the additional module btree_gist installed (once per database) which provides the operator classes to include an integer.


The trifecta! A multicolumn functional GiST index:
CREATE EXTENSION IF NOT EXISTS btree_gist;  -- if not installed, yet

CREATE INDEX idx_time_limits_funky ON time_limits USING gist
(id_phi, tsrange(start_date_time, end_date_time, '[]'));

Use the &quot;contains range&quot; operator @&gt; in your query now:
SELECT *
FROM   time_limits
WHERE  id_phi = 0
AND    tsrange(start_date_time, end_date_time, '[]')
    @&gt; tsrange('2010-08-08 00:00', '2010-08-08 00:05', '[]')

SP-GiST index in Postgres 9.3+
An SP-GiST index might be even faster for this kind of query - except that, quoting the manual:

Currently, only the B-tree, GiST, GIN, and BRIN index types support multicolumn indexes.

Still true in Postgres 12.
You would have to combine an spgist index on just (tsrange(...)) with a second btree index on (id_phi). With the added overhead, I'm not sure this can compete.
Related answer with a benchmark for just a tsrange column:

Perform this hours of operation query in PostgreSQL