Group data by the change of grouping column value in order

Question

With the following data

create table #ph (product int, [date] date, price int)
insert into #ph select 1, '20120101', 1
insert into #ph select 1, '20120102', 1
insert into #ph select 1, '20120103', 1
insert into #ph select 1, '20120104', 1
insert into #ph select 1, '20120105', 2
insert into #ph select 1, '20120106', 2
insert into #ph select 1, '20120107', 2
insert into #ph select 1, '20120108', 2
insert into #ph select 1, '20120109', 1
insert into #ph select 1, '20120110', 1
insert into #ph select 1, '20120111', 1
insert into #ph select 1, '20120112', 1

I would like to produce the following output:

product | date_from | date_to  | price
  1     | 20120101  | 20120105 |   1
  1     | 20120105  | 20120109 |   2
  1     | 20120109  | 20120112 |   1

If I group by price and show the max and min date then I will get the following which is not what I want (see the over lapping of dates).

product | date_from | date_to  | price
  1     | 20120101  | 20120112 |   1
  1     | 20120105  | 20120108 |   2

So essentially what I'm looking to do is group by the step change in data based on group columns product and price.

What is the cleanest way to achieve this?

Answer 1

There's a (more or less) known technique of solving this kind of problem, involving two ROW_NUMBER() calls, like this:

WITH marked AS (
  SELECT
    *,
    grp = ROW_NUMBER() OVER (PARTITION BY product        ORDER BY date)
        - ROW_NUMBER() OVER (PARTITION BY product, price ORDER BY date)
  FROM #ph
)
SELECT
  product,
  date_from = MIN(date),
  date_to   = MAX(date),
  price
FROM marked
GROUP BY
  product,
  price,
  grp
ORDER BY
  product,
  MIN(date)

Output:

product  date_from   date_to        price 
-------  ----------  -------------  ----- 
1        2012-01-01  2012-01-04     1     
1        2012-01-05  2012-01-08     2     
1        2012-01-09  2012-01-12     1     

Answer 2

I'm new to this forum so hope my contribution is helpful.

If you really don't want to use a CTE (although I think thats probably the best approach) you can get a solution using set based code. You will need to test the performance of this code!.

I have added in an extra temp table so that I can use a unique identifier for each record but I suspect you will already have this column in you source table. So heres the temp table.

    If Exists (SELECT Name FROM tempdb.sys.tables WHERE name LIKE '#phwithId%')
        DROP TABLE #phwithId    

    CREATE TABLE #phwithId
    (
        SaleId INT
        , ProductID INT
        , Price Money
        , SaleDate Date 
    )
    INSERT INTO #phwithId SELECT row_number() over(partition by product order by [date] asc) as SalesId, Product, Price, Date FROM ph 

Now the main body of the Select statement

    SELECT 
        productId 
        , date_from
        , date_to
        , Price
    FROM
        (   
            SELECT 
                dfr.ProductId
                , ROW_NUMBER() OVER (PARTITION BY ProductId ORDER BY ChangeDate) AS rowno1          
                , ChangeDate AS date_from
                , dfr.Price
            FROM
                (       
                    SELECT
                        sl1.ProductId AS ProductId
                        , sl1.SaleDate AS ChangeDate
                        , sl1.price
                    FROM
                        #phwithId sl1
                    LEFT JOIN
                        #phwithId sl2
                        ON sl1.SaleId = sl2.SaleId + 1
                    WHERE
                        sl1.Price <> sl2.Price OR sl2.Price IS NULL
                ) dfr
        ) da1
    LEFT JOIN
        (   
            SELECT 
                ROW_NUMBER() OVER (PARTITION BY ProductId ORDER BY ChangeDate) AS rowno2
                , ChangeDate AS date_to     
            FROM
                (   
                    SELECT 
                        sl1.ProductId
                        , sl1.SaleDate AS ChangeDate
                    FROM
                        #phwithId sl1
                    LEFT JOIN
                        #phwithId sl3
                        ON sl1.SaleId = sl3.SaleId - 1  
                    WHERE
                        sl1.Price <> sl3.Price OR sl3.Price IS NULL         
                ) dto

        ) da2 
        ON da1.rowno1 = da2.rowno2  

By binding the data source offset by 1 record (+or-) we can identify when the price buckets change and then its just a matter of getting the start and end dates for the buckets back into a single record.

All a bit fiddly and I'm not sure its going to give better performance but I enjoyed the challenge.