Re: Need some tips on query generating averages on time series data
From: <tonkuma_at_fiberbit.net>
Date: Thu, 31 Oct 2013 04:21:30 -0700 (PDT)
Message-ID: <91b1b32c-5fe2-49a3-bf3f-f369bb0520cc_at_googlegroups.com>
FROM trades AS t
)
SELECT time
; Received on Thu Oct 31 2013 - 12:21:30 CET
Date: Thu, 31 Oct 2013 04:21:30 -0700 (PDT)
Message-ID: <91b1b32c-5fe2-49a3-bf3f-f369bb0520cc_at_googlegroups.com>
Another revised example.
(1) Remove a nested subquery in add_cum cte.
(2) Remove some columns in GROUP BY and ORDER BY clause.
WITH
add_cum AS (
SELECT t.*
, SUM(quantity)
OVER( PARTITION BY position , direction ORDER BY time ) AS cumulative
, NVL(
SUM(quantity) OVER( PARTITION BY position , direction ORDER BY time ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING ) , 0) AS lag_cumul
FROM trades AS t
)
SELECT time
, SUM(cumul - lag_cumul) AS qnt
, cumul
, hold_time
, SUM( hold_time * (cumul - lag_cumul) )
AS weighted_hold_time
, NULLIF(GROUPING(cumul) , 0)
* SUM( hold_time * (cumul - lag_cumul) ) / SUM(cumul - lag_cumul) AS weighted_avg_hold_time FROM (SELECT b.time , MAX(s.lag_cumul , b.lag_cumul) AS lag_cumul , MIN(s.cumulative , b.cumulative) AS cumul , s.time - b.time AS hold_time FROM add_cum AS s INNER JOIN add_cum AS b ON s.direction = 'S' AND b.direction = 'B' AND s.cumulative > b.lag_cumul AND b.cumulative > s.lag_cumul ) GROUP BY ROLLUP ( ( time , cumul , hold_time ) ) ORDER BY cumul
; Received on Thu Oct 31 2013 - 12:21:30 CET