I am trying to compute efficiently (using SQL Server 2008) the moving average of the ProductCount over a period of 24 hours. For every single row in the Product table, I'd like to know what was the average of ProductCount (for that given products) over the last 24 hours. One problem with our data is that not all the dates/hours are present (see example below). If a TimeStamp is missing, it means that the ProductCount was 0.
I have a table with millions or rows with a Date, Product and Count. Below is a simplified example of the data I have to deal with.
Any idea on how to acheive that?
EDIT: One other piece of data that I need is the MIN and MAX ProductCount for the period (i.e. 24h). Computing the MIN/MAX is a bit trickier because of the missing values...
+---------------------+-------------+--------------+
| Date | ProductName | ProductCount |
+---------------------+-------------+--------------+
| 2012-01-01 00:00:00 | Banana | 15000 |
| 2012-01-01 01:00:00 | Banana | 16000 |
| 2012-01-01 02:00:00 | Banana | 17000 |
| 2012-01-01 05:00:00 | Banana | 12000 |
| 2012-01-01 00:00:00 | Apple | 5000 |
| 2012-01-01 05:00:00 | Apple | 6000 |
+---------------------+-------------+--------------+
SQL
CREATE TABLE ProductInventory (
[Date] DATETIME,
[ProductName] NVARCHAR(50),
[ProductCount] INT
)
INSERT INTO ProductInventory VALUES ('2012-01-01 00:00:00', 'Banana', 15000)
INSERT INTO ProductInventory VALUES ('2012-01-01 01:00:00', 'Banana', 16000)
INSERT INTO ProductInventory VALUES ('2012-01-01 02:00:00', 'Banana', 17000)
INSERT INTO ProductInventory VALUES ('2012-01-01 05:00:00', 'Banana', 12000)
INSERT INTO ProductInventory VALUES ('2012-01-01 00:00:00', 'Apple', 5000)
INSERT INTO ProductInventory VALUES ('2012-01-01 05:00:00', 'Apple', 6000)
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