Simulate query over a range of dates - sql

Question

I have a fairly long query that looks over the past 13 weeks and determines if the current day's performance is an anomaly compared to the last 13 weeks. It just returns a single row that has the date, the performance of the current day and a flag saying if it is an anomaly or not. To make matters a little more complicated: The performance isn't just a single day but rather a running 24 hour window. This query is then run every hour to monitor the KPI over the last 24 hours. i.e. If it is 2pm on Tuesday, it will look from 2pm the previous day (Monday) to now, and compare it to every other 2pm-to-2pm for the last 13 weeks.
To test if this code is working I would like simulate it running over the past month.
The code goes as follows:
WITH performance AS(
SELECT TRUNC(dateColumn - to_number(to_char(sysdate, 'hh24')/24) as startdate,
KPI_a,
KPI_b,
KPI_c
FROM table
WHERE someConditions
GROUP BY TRUNC(dateColumn - to_number(to_char(sysdate, 'hh24')/24)),
compare_t AS(
-- looks at relationships of the KPIs),
variables AS(
-- calculates the variables required for the anomaly detection),
... ok I don't know how much of the query needs to be given but it's basically I need to simulate 'sysdate'. Instead of inputting the current date, input each hour for the last month so this query will run approx 720 times and return the result 720 times, for each hour of each day.
I'm thinking a FOR loop, but I'm not sure.

Answer 1

You can use a recursive subquery:
with times(time) as
(
select sysdate - interval '1' month as time from dual
union all
select time + interval '1' hour from times
where time < sysdate
)
, performance as ()
, compare_t as ()
, variables as ()
select *
from times
join ...
order by time;

Answer 2

I don't understand your specific requirements but I had to solve similar problems. To give you an idea here are two proposals:
Calculate average and standard deviation of KPI value from past 13 weeks to yesterday. If current value from today it lower than "AVG - 10*STDDEV" then select record, i.e. mark as anomaly.
WITH t AS
(SELECT dateColumn, KPI_A,
AVG(KPI_A) OVER (ORDER BY dateColumn RANGE BETWEEN 13 * INTERVAL '7' DAY PRECEDING AND INTERVAL '1' DAY PRECEDING) AS REF_AVG,
STDDEV(KPI_A) OVER (ORDER BY dateColumn RANGE BETWEEN 13 * INTERVAL '7' DAY PRECEDING AND INTERVAL '1' DAY PRECEDING) AS REF_STDDEV
FROM TABLE
WHERE someConditions)
SELECT dateColumn, REF_AVG, KPI_A, REF_STDDEV
FROM t
WHERE TRUNC(dateColumn, 'HH') = TRUNC(LOCALTIMESTAMP, 'HH')
AND KPI_A < REF_AVG - 10 * REF_STDDEV;
Take hourly values from last week (i.e. the same weekday as yesterday) and make correlation with hourly values from yesterday. If correlation is less than certain value (I use 95%) then consider this day as anomaly.
WITH t AS
(SELECT dateColumn, KPI_A,
FIRST_VALUE(KPI_A) OVER (ORDER BY dateColumn RANGE BETWEEN INTERVAL '7' DAY PRECEDING AND CURRENT ROW) AS KPI_A_LAST_WEEK,
dateColumn - FIRST_VALUE(dateColumn) OVER (ORDER BY dateColumn RANGE BETWEEN INTERVAL '7' DAY PRECEDING AND CURRENT ROW) AS RANGE_INT
FROM table
WHERE ...)
SELECT 100*ROUND(CORR(KPI_A, KPI_A_LAST_WEEK), 2) AS CORR_VAL
FROM t
WHERE KPI_A_LAST_WEEK IS NOT NULL
AND RANGE_INT = INTERVAL '7' DAY
AND TRUNC(dateColumn) = TRUNC(LOCALTIMESTAMP - INTERVAL '1' DAY)
GROUP BY TRUNC(dateColumn);