在 Oracle/SQL 中预测时间序列数据

有没有一种方法可以使用 Oracle 分析函数为数据集生成时间序列预测？我们如何在 SQL/ORACLE 中执行外推。

下面是我的需求

我有如下的数据集，我想预测/推断明年

Cust_id  Year  Revnue
1        2016  679862
1        2017  705365
1        2018  ?
2        2016  51074
2        2017  50611
2        2018  ?
3        2016  190706
3        2017  90393
3        2018  ?
4        2016  31649
4        2017  19566
4        2018  ?

您可以使用以下命令创建简单的预测REGR https://docs.oracle.com/en/database/oracle/oracle-database/18/sqlrf/REGR_-Linear-Regression-Functions.html#GUID-A675B68F-2A88-4843-BE2C-FCDE9C65F9A9线性回归函数。

--Ordinary least squares forecast for each customer for the next year.
select
    cust_id,
    max(year) +1 forecast_year,
    -- y = mx+b
    regr_slope(revenue, year)
        * (max(year) + 1)
        + regr_intercept(revenue, year) forecasted_revenue
from customer_data
group by cust_id;

CUST_ID   FORECAST_YEAR   FORECASTED_REVENUE
-------   -------------   ------------------
1                  2018               730868
2                  2018                50148
4                  2018                 7483
3                  2018                -9920

以下是示例架构。或者你可以使用这个 SQLFiddle http://sqlfiddle.com/#!4/e61ce/1.

create table customer_data
(
    cust_id number,
    year number,
    revenue number
);

insert into customer_data
select 1, 2016, 679862 from dual union all
select 1, 2017, 705365 from dual union all
select 2, 2016, 51074  from dual union all
select 2, 2017, 50611  from dual union all
select 3, 2016, 190706 from dual union all
select 3, 2017, 90393  from dual union all
select 4, 2016, 31649  from dual union all
select 4, 2017, 19566  from dual;

The REGR函数处理数字对，它不理解“收入不能低于 0”等业务规则。如果您想将预测限制为始终保持在 0 或以上，CASE表达可能有帮助：

--Forecasted revenue, with minimum forecast of 0.
select cust_id, forecast_year,
    case when forecasted_revenue < 0 then 0 else forecasted_revenue end forecasted_revenue
from
(
    --Ordinary least squares forecast for each customer for the next year.
    select
        cust_id,
        max(year) +1 forecast_year,
        -- y = mx+b
        regr_slope(revenue, year)
            * (max(year) + 1)
            + regr_intercept(revenue, year) forecasted_revenue
    from customer_data
    group by cust_id
);

CUST_ID   FORECAST_YEAR   FORECASTED_REVENUE
-------   -------------   ------------------
1                  2018               730868
2                  2018                50148
4                  2018                 7483
3                  2018                    0