Query last N related rows per row

Question

I have the following query which fetches the id of the latest N observations for each station:

SELECT id
FROM (
  SELECT station_id, id, created_at,
         row_number() OVER(PARTITION BY station_id
                           ORDER BY created_at DESC) AS rn
  FROM (
      SELECT station_id, id, created_at
      FROM observations
  ) s
) s
WHERE rn <= #{n}
ORDER BY station_id, created_at DESC;

I have indexes on id, station_id, created_at.

This is the only solution I have come up with that can fetch more than a single record per station. However it is quite slow (154.0 ms for a table of 81000 records).

How can I speed up the query?

Answer 1

Assuming at least Postgres 9.3.

Index

First, a multicolumn index will help:

CREATE INDEX observations_special_idx
ON observations(station_id, created_at DESC, id)

created_at DESC is a slightly better fit, but the index would still be scanned backwards at almost the same speed without DESC.

Assuming created_at is defined NOT NULL, else consider DESC NULLS LAST in index and query:

• PostgreSQL sort by datetime asc, null first?

The last column id is only useful if you get an index-only scan out of it, which probably won't work if you add lots of new rows constantly. In this case, remove id from the index.

Simpler query (still slow)

Simplify your query, the inner subselect doesn't help:

SELECT id
FROM  (
  SELECT station_id, id, created_at
       , row_number() OVER (PARTITION BY station_id
                            ORDER BY created_at DESC) AS rn
  FROM   observations
  ) s
WHERE  rn <= #{n}  -- your limit here
ORDER  BY station_id, created_at DESC;

Should be a bit faster, but still slow.

Fast query

• Assuming you have relatively few stations and relatively many observations per station.
• Also assuming station_id id defined as NOT NULL.

To be really fast, you need the equivalent of a loose index scan (not implemented in Postgres, yet). Related answer:

• Optimize GROUP BY query to retrieve latest record per user

If you have a separate table of stations (which seems likely), you can emulate this with JOIN LATERAL (Postgres 9.3+):

SELECT o.id
FROM   stations s
CROSS  JOIN LATERAL (
   SELECT o.id
   FROM   observations o
   WHERE  o.station_id = s.station_id  -- lateral reference
   ORDER  BY o.created_at DESC
   LIMIT  #{n}  -- your limit here
   ) o
ORDER  BY s.station_id, o.created_at DESC;

If you don't have a table of stations, the next best thing would be to create and maintain one. Possibly add a foreign key reference to enforce relational integrity.

If that's not an option, you can distill such a table on the fly. Simple options would be:

SELECT DISTINCT station_id FROM observations;
SELECT station_id FROM observations GROUP BY 1;

But either would need a sequential scan and be slow. Make Postgres use above index (or any btree index with station_id as leading column) with a recursive CTE:

WITH RECURSIVE stations AS (
   (                  -- extra pair of parentheses ...
   SELECT station_id
   FROM   observations
   ORDER  BY station_id
   LIMIT  1
   )                  -- ... is required!
   UNION ALL
   SELECT (SELECT o.station_id
           FROM   observations o
           WHERE  o.station_id > s.station_id
           ORDER  BY o.station_id
           LIMIT  1)
   FROM   stations s
   WHERE  s.station_id IS NOT NULL  -- serves as break condition
   )
SELECT station_id
FROM   stations
WHERE  station_id IS NOT NULL;      -- remove dangling row with NULL

Use that as drop-in replacement for the stations table in the above simple query:

WITH RECURSIVE stations AS (
   (
   SELECT station_id
   FROM   observations
   ORDER  BY station_id
   LIMIT  1
   )
   UNION ALL
   SELECT (SELECT o.station_id
           FROM   observations o
           WHERE  o.station_id > s.station_id
           ORDER  BY o.station_id
           LIMIT  1)
   FROM   stations s
   WHERE  s.station_id IS NOT NULL
   )
SELECT o.id
FROM   stations s
CROSS  JOIN LATERAL (
   SELECT o.id, o.created_at
   FROM   observations o
   WHERE  o.station_id = s.station_id
   ORDER  BY o.created_at DESC
   LIMIT  #{n}  -- your limit here
   ) o
WHERE  s.station_id IS NOT NULL
ORDER  BY s.station_id, o.created_at DESC;

This should still be faster than what you had by orders of magnitude.

SQL Fiddle here (9.6)
db<>fiddle here

Answer 2

This is a good anwser only if you are not required to query up-to-date live data.

Preparation (requires postgresql 9.3)

drop materialized view test;
create materialized view test as select * from (
  SELECT station_id, id, created_at,
      row_number() OVER(
          PARTITION BY station_id
          ORDER BY created_at DESC
      ) as rn
  FROM (
      SELECT
          station_id,
          id,
          created_at
      FROM observations
  ) s
 ) q WHERE q.rn <= 100 -- use a value that will be your max limit number for further queries
ORDER BY station_id, rn DESC ;


create index idx_test on test(station_id,rn,created_at);

How to query data:

select * from test where rn<10 order by station_id,created_at;

Your original query was 281 ms on my machine and this new was 15 ms.

How to update the view with fresh data:

refresh materialized view test;

I have another solution that does not require materialized view and works with live, up-to-date data. But given that you don't need up-to-date data, this materialized view is much more efficient.