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To add to this discussion - I believe "the python idea" may be relevant here.
Option 2 - with python support over QDB data running natively (and by extention much quickly - which is the point of this); then the QDB team don't need to add SQL support for the above mentioned, but just the python one. Is my understanding correct @bluestreak01 or no? |
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Hi, I am writing this here as a spec on which to base discussions toward the design of this feature. My understanding of window functions, these are functions that are applied to a set of rows around the current row (comparable to aggregation functions but rows are not grouped into a single row at the end). Syntaxfunction_name ([expr [, expr ... ]])
OVER ( [ window_definition ] ) The presence of OVER makes the function a window function. function_name: general-purpose window or aggregate function one of [ row_number, first_value, last_value, nth_value, lag, lead, rank, dense_rank, (window functions)
avg, count, count_distinct, first, haversine_dist_deg, ksum, last, max, min, nsum, sum (aggregate functions)
mean, stddev, variance, percentile (aggregate functions extra) ] [ PARTITION BY expr [, ...] ]
[ ORDER BY expr [ ASC | DESC ]]
[ frame_spec ] frame_spec: { RANGE | ROWS } BETWEEN frame_start AND frame_end frame_start, frame_end:
Default frame spec:
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Relates to #1268 |
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Relates to #258 |
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We've created an issue to track the progress of this feature -> #1351 |
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related to #2995 |
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A Sliding window or Moving average is pretty important in many use cases. It would be nice if questdb has this built in.
For reference, here's clickhouse's:
https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/grouparraymovingavg/
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