我有一个表格，其中有各种属性，如地区产品，年份，季节，月份，销售。我必须计算具有相同区域的每个产品的avg_qtr销售并显示他们之前的avg_qtr销售。我已经阅读了关于滞后但是这里不可能使用，因为它将在重复多少行之后不固定。我的表结构是这样的
Region Product Year Qtr Month Sales
NORTH P1 2015 1 JAN 1000
NORTH P1 2015 1 FEB 2000
NORTH P1 2015 1 MAR 3000
NORTH P1 2015 2 APR 4000
NORTH P1 2015 2 MAY 5000
NORTH P1 2015 2 JUN 6000
NORTH P1 2015 3 JUL 7000
NORTH P1 2015 3 AUG 8000
NORTH P1 2015 3 SEP 9000
NORTH P1 2015 4 OCT 1000
NORTH P1 2015 4 DEC 4000
NORTH P1 2015 4 NOV 2000
NORTH P3 2015 1 FEB 1000
NORTH P3 2015 1 FEB 9000
NORTH P3 2015 2 APR 2000
NORTH P3 2015 3 JUL 8000
NORTH P1 2016 1 MAR 3000
NORTH P1 2016 1 FEB 1000
NORTH P1 2016 1 JAN 2000
SOUTH P1 2015 1 JAN 2000
SOUTH P1 2015 1 FEB 3000
SOUTH P1 2015 1 JAN 4000
SOUTH P2 2015 1 MAR 1000
SOUTH P2 2015 1 JAN 8000
SOUTH P2 2015 1 FEB 9000
SOUTH P2 2015 2 JUN 9000
SOUTH P2 2015 2 MAY 8000
SOUTH P2 2015 2 APR 2000
SOUTH P2 2015 3 SEP 4000
SOUTH P2 2015 3 AUG 2000
SOUTH P2 2015 3 JUL 1000
SOUTH P2 2015 4 NOV 2000
SOUTH P2 2015 4 DEC 1000
SOUTH P2 2015 4 OCT 5000
SOUTH P3 2015 3 AUG 9000
SOUTH P3 2015 4 OCT 1000
SOUTH P3 2015 4 NOV 3000
SOUTH P2 2016 1 JAN 2000
SOUTH P2 2016 1 JAN 4000
我写了一个计算当前qtr的查询，并显示前一个avg，当前为一个
WITH AvgSales
AS (SELECT
region,
product,
year,
qtr,
ROUND(AVG(sales), 2) AS avg_Sale
FROM one
GROUP BY region,
product,
year,qtr
)
SELECT
s.region,
s.product,
s.year,
s.month,
s.sales,
avg.qtr,
avg.avg_Sale AS Qtr_Avg_Sale,
prev.avg_sale AS Prev_Qtr_Avg_Sale
FROM one s
JOIN AvgSales avg
ON s.region = avg.region
AND s.product = avg.product
AND s.QTR = avg.qtr
AND s.year = avg.year
LEFT JOIN AvgSales prev
ON (s.region = prev.region
AND s.product = prev.product
AND s.year - 1 = prev.year
and s.qtr=1
AND prev.qtr = 4) or
(s.region = prev.region
AND s.product = prev.product
AND s.year = prev.year
AND s.qtr - 1 = prev.qtr) ;
我能够获得该产品的当前平均值和之前的平均值，但反之亦然。我不知道如何显示该季度以前没有任何销售的季度。 我想要这样的输出 -
Region Product Year qtr month sale avg_Sale prev_avg_sale
NORTH P1 2015 1 JAN 1000 2000
NORTH P1 2015 1 FEB 2000 2000
NORTH P1 2015 1 MAR 3000 2000
NORTH P1 2015 2 APR 4000 5000 2000
NORTH P1 2015 2 MAY 5000 5000 2000
NORTH P1 2015 2 JUN 6000 5000 2000
NORTH P1 2015 3 JUL 7000 8000 5000
NORTH P1 2015 3 AUG 8000 8000 5000
NORTH P1 2015 3 SEP 9000 8000 5000
NORTH P1 2015 4 OCT 1000 2333.33 8000
NORTH P1 2015 4 NOV 2000 2333.33 8000
NORTH P1 2015 4 DEC 4000 2333.33 8000
SOUTH P2 2015 1 JAN 8000 6000
SOUTH P2 2015 1 FEB 9000 6000
SOUTH P2 2015 1 MAR 1000 6000
SOUTH P2 2015 2 APR 2000 6333.33 6000
SOUTH P2 2015 2 MAY 8000 6333.33 6000
SOUTH P2 2015 2 JUN 9000 6333.33 6000
SOUTH P2 2015 3 JUL 1000 2333.33 6333.33
SOUTH P2 2015 3 AUG 2000 2333.33 6333.33
SOUTH P2 2015 3 SEP 4000 2333.33 6333.33
SOUTH P2 2015 4 OCT 5000 2666.67 2333.33
SOUTH P2 2015 4 NOV 2000 2666.67 2333.33
SOUTH P2 2015 4 DEC 1000 2666.67 2333.33
NORTH P3 2015 1 FEB 9000 5000
NORTH P3 2015 1 FEB 1000 5000
NORTH P3 2015 2 APR 2000 2000 5000
NORTH P3 2015 3 JUL 8000 8000 2000
SOUTH P3 2015 3 AUG 9000 9000
SOUTH P3 2015 4 OCT 1000 2000 9000
SOUTH P3 2015 4 NOV 3000 2000 9000
NORTH P1 2016 1 JAN 2000 2000 2333.33
NORTH P1 2016 1 FEB 1000 2000 2333.33
NORTH P1 2016 1 MAR 3000 2000 2333.33
NORTH P2 2016 2 2000
SOUTH P2 2016 1 JAN 2000 3000 2666.67
SOUTH P2 2016 1 JAN 4000 3000 2666.67
SOUTH P2 2016 2 3000
SOUTH P1 2015 1 JAN 4000 3000
SOUTH P1 2015 1 JAN 2000 3000
SOUTH P1 2015 1 FEB 3000 3000