Thanks a lot tomas, i will try it.
I have find out that there is a 'aggregation' function in the frontend.
But this is MySQL specific and I have no idea the transform it to postgres.
It looks like:
'REPLACE INTO aggregate (channel_id, type, timestamp, value, count)
SELECT channel_id, ? AS type, MAX(agg.timestamp) AS timest
amp, COALESCE( SUM(agg.val_by_time) / (MAX(agg.timestamp) -
MIN(agg.prev_timestamp)), AVG(agg.value)) AS value, COUNT(agg.value) AS
count FROM ( SELECT channel_id,
timestamp, value, value * (timestamp - @prev_timestamp) AS
val_by_time, COALESCE(@prev_timestamp, 0) AS prev_timestamp,
@prev_timestamp := timestamp FROM data CROSS
JOIN (SELECT @prev_timestamp := NULL) AS vars WHERE channel_id = ?
AND timestamp < UNIX_TIMESTAMP(DATE_FORMAT(NOW(), "%Y-%m-%d")) * 1000 )
AS agg GROUP BY channel_
id, DATE_TRUNC('day', TIMESTAMP 'epoch' + timestamp * INTERVAL '1
millisecond')' with params [3, 5]:
SQLSTATE[42601]: Syntax error: 7 ERROR: syntax error at or near
"REPLACE"
LINE 1: REPLACE INTO aggregate (channel_id, type, timestamp, value,
...
Am 17.07.23 um 13:21 schrieb Tomas Vondra:
On 7/17/23 13:20, Tomas Vondra wrote:
...
It's always going to be slow with the COUNT(DISTINCT), I'm afraid.
Not sure how much you can modify the query / database, and how accurate
results you need. If you're OK with estimates, you can try postgres-hll
extension [2] which estimates count(distinct). For exact reaults, I
wrote count_distinct extension [2] that uses hashtable. Might be worth a
try, I guess.
Damn, I forgot to add the links:
[1] https://github.com/citusdata/postgresql-hll
[2] https://github.com/tvondra/count_distinct
regards
