Query performance

I have a table with some seven million rows.

The query:

select count(rdate),rdate from reading where sensor_id in 
(1137,1138,1139) group by rdate order by rdate desc limit 1;

takes a few seconds but:

select count(rdate),rdate from reading where sensor_id in 
(1137,1138,1139,1140) group by rdate order by rdate desc limit 1;

(anything with four or more values in the "in" list) takes several 
minutes.

Is there any way to make the "larger" queries more efficient?

Both rdate and sensor_id are indexed and the database is vacuumed every 
night.

Explain outputs are:

benparts=# explain select count(rdate),rdate from reading where 
sensor_id in (1137,1138,1139,1140) group by rdate order by rdate desc 
limit 1;                                           QUERY PLAN
---------------------------------------------------------------------------------------------------Limit
(cost=0.00..39890.96rows=1 width=8)  ->  GroupAggregate  (cost=0.00..7938300.21 rows=199 width=8)        ->  Index Scan
Backwardusing date on reading  
 
(cost=0.00..7937884.59 rows=82625 width=8)              Filter: (sensor_id = ANY 
('{1137,1138,1139,1140}'::integer[]))
(4 rows)

benparts=# explain select count(rdate),rdate from reading where 
sensor_id in (1137,1138,1139) group by rdate order by rdate desc limit 
1;                                            QUERY PLAN
-----------------------------------------------------------------------------------------------------Limit
(cost=48364.32..48364.32rows=1 width=8)  ->  Sort  (cost=48364.32..48364.49 rows=69 width=8)        Sort Key: rdate
  ->  HashAggregate  (cost=48361.35..48362.21 rows=69 width=8)              ->  Bitmap Heap Scan on reading
(cost=535.53..48218.10
 
rows=28650 width=8)                    Recheck Cond: (sensor_id = ANY 
('{1137,1138,1139}'::integer[]))                    ->  Bitmap Index Scan on reading_sensor  
(cost=0.00..528.37 rows=28650 width=0)                          Index Cond: (sensor_id = ANY 
('{1137,1138,1139}'::integer[]))
(8 rows)

TIA,
Stephen Davies
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