Identifying trend with SQL query

前端 未结 1 1875
耶瑟儿~
耶瑟儿~ 2021-02-04 12:21

I have a table (let\'s call it Data) with a set of object IDs, numeric values and dates. I would like to identify the objects whose values had a positive trend over the last X m

1条回答
  •  孤独总比滥情好
    2021-02-04 12:28

    You inspired me to go and implement linear regression in SQL Server. This could be modified for MySQL/Oracle/Whatever without too much trouble. It's the mathematically best way of determining the trend over the hour for each entity_id and it will select out only the ones with a positive trend.

    It implements the formula for calculating B1hat listed here: https://en.wikipedia.org/wiki/Regression_analysis#Linear_regression

    create table #temp
    (
        entity_id int,
        value int,
        [date] datetime
    )
    
    insert into #temp (entity_id, value, [date])
    values
    (1,10,'20140102 07:00:00 AM'),
    (1,20,'20140102 07:15:00 AM'),
    (1,30,'20140102 07:30:00 AM'),
    (2,50,'20140102 07:00:00 AM'),
    (2,20,'20140102 07:47:00 AM'),
    (3,40,'20140102 07:00:00 AM'),
    (3,40,'20140102 07:52:00 AM')
    
    select entity_id, 1.0*sum((x-xbar)*(y-ybar))/sum((x-xbar)*(x-xbar)) as Beta
    from
    (
        select entity_id,
            avg(value) over(partition by entity_id) as ybar,
            value as y,
            avg(datediff(second,'20140102 07:00:00 AM',[date])) over(partition by entity_id) as xbar,
            datediff(second,'20140102 07:00:00 AM',[date]) as x
        from #temp
        where [date]>='20140102 07:00:00 AM' and [date]<'20140102 08:00:00 AM'
    ) as Calcs
    group by entity_id
    having 1.0*sum((x-xbar)*(y-ybar))/sum((x-xbar)*(x-xbar))>0
    

    0 讨论(0)
提交回复
热议问题