Hi all - here is the entire correct problem - apologies again! Hi all, I have an interpolation problem as follows - fiddle available here: https://dbfiddle.uk/?rdbms=postgres_12&fiddle=428aa76d49b37961088d3dfef190757f A table: CREATE TABLE data ( s SERIAL PRIMARY KEY, t TIMESTAMP, lat NUMERIC ); and data: INSERT INTO data (t, lat) VALUES ('2019-01-01 00:00:00', 5.07), ('2019-01-01 01:00:00', 4.60), ('2019-01-01 02:00:00', NULL), ('2019-01-01 03:00:00', NULL), ('2019-01-01 04:00:00', 4.7), ('2019-01-01 05:00:00', 4.20), ('2019-01-01 06:00:00', NULL), ('2019-01-01 07:00:00', 4.98), ('2019-01-01 08:00:00', 4.50), ('2019-01-01 09:00:00', 4.7), ('2019-01-01 10:00:00', NULL), ('2019-01-01 11:00:00', NULL), ('2019-01-01 12:00:00', NULL), ('2019-01-01 13:00:00', 6.45), ('2019-01-01 14:00:00', 3.50); There are gaps in the data as you can see - I'm trying to fill them using the algorithm: - a sequence of 1 NULL - take the average of the reading above and the reading below - a sequence of 2 NULLs - the top assigned value is the average of the two records above it and the bottom assigned one is the average of the two records below. So far, so good - I'm able to do this (but see discussion below) - a sequence of 3 NULLs - the middle one is assigned a value equal to average of the non-NULL record above and the non-null record below, and then the remaining NULLs above and below the average of the middle one and the non-NULL ones above and below. This is where it gets tricky - I'm getting answers, but I don't think they're correct. The result of the massive SQL shown below are here (also on fiddle): s lat final_val 1 5.07 5.07 2 4.60 4.60 3 NULL 4.84 4 NULL 4.45 5 4.7 4.7 6 4.20 4.20 7 NULL 4.59 8 4.98 4.98 9 4.50 4.50 10 4.7 4.7 11 NULL 4.60 12 NULL 5.58 13 NULL 4.98 14 6.45 6.45 15 3.50 3.50 The value for record 12 is correct, ,but not those above and below it. I think my *MAJOR* problem is that I've developed what is, essentially, a totally brute force approach - and this simply won't work at the scenario becomes more complex - take a look at the CASE statement - it's horrible and would only become exponentially worse as the number NULLs rises. So, my question is: Is there a recognised technique (using SQL only, not PL/pgSQL - soutions based on the latter are easy to find) whereby I can do a basic Linear Interpolation? Should you require any further information, please don't hesitate to contact me. TIA and rgs, Pól... ========================================================= My mega SQL: WITH cte1 AS ( SELECT d1.s, d1.t AS t1, d1.lat AS l1, LAG(d1.lat, 2) OVER (ORDER BY t ASC) AS lag_t1_2, LAG(d1.lat, 1) OVER (ORDER BY t ASC) AS lag_t1, LEAD(d1.lat, 1) OVER (ORDER BY t ASC) AS lead_t1, LEAD(d1.lat, 2) OVER (ORDER BY t ASC) AS lead_t1_2 FROM data d1 ), cte2 AS ( SELECT d2.t AS t2, d2.lat AS l2, LAG(d2.lat, 1) OVER(ORDER BY t DESC) AS lag_t2, LEAD(d2.lat, 1) OVER(ORDER BY t DESC) AS lead_t2 FROM data d2 ), cte3 AS ( SELECT t1.s, t1.t1, t1.lag_t1_2, t1.lag_t1, t2.lag_t2, t1.l1, t2.l2, t1.lead_t1, t2.lead_t2, t1.lead_t1_2 FROM cte1 t1 JOIN cte2 t2 ON t1.t1 = t2.t2 ), cte4 AS ( SELECT t1.s, t1.l1 AS lat, CASE -- The WHEN for the middle of 3 NULLs has to be at the beginning -- of the CASE - if at the end, it remains NULL - why? WHEN (t1.lag_t1 IS NULL) AND (t1.lag_t2 IS NULL) AND (t1.l1 IS NULL) AND (t1.lead_t1 IS NULL) AND (t1.lead_t2 IS NULL) THEN ROUND((t1.lag_t1_2 + t1.lead_t1_2)/2, 2) WHEN (t1.l1 IS NOT NULL) THEN t1.l1 WHEN (t1.l1 IS NULL) AND (t1.l2) IS NULL AND (t1.lag_t1 IS NOT NULL) AND (t1.lag_t2 IS NOT NULL) THEN ROUND((t1.lag_t1 + t1.lag_t2)/2, 2) WHEN (t1.lag_t2 IS NULL) AND (t1.l1 IS NULL) AND (t1.l2 IS NULL) AND (t1.lead_t1 IS NULL) THEN ROUND((t1.lag_t1 + t1.lag_t1_2)/2, 2) WHEN (t1.l1 IS NULL) AND (t1.l2 IS NULL) AND (t1.lag_t1 IS NULL) AND (t1.lead_t2 IS NULL) THEN ROUND((t1.lead_t1 + t1.lead_t1_2)/2, 2) ELSE 0 END AS final_val FROM cte3 t1 ) SELECT s, lat, final_val FROM cte4;
