Question

I have the following two tables

activity(activity_id, title, description, group_id)
statistic(statistic_id, activity_id, date, user_id, result)

group_id and user_id come from active directory. Result is an integer.

Given a user_id and a date range of 6 days (Mon – Sat) which I’ve calculated on the business logic side, and the fact that some of the dates in the date range may not have a statistic result for the particular date (ie. day1 and day 4 may have entered statistic rows for a particular activity, but there may not be any entries for days 2, 3, 5 and 6) how can I get a SQL result with the following format? Keep in mind that if a particular activity doesn’t have a record for the particular date in the statistics table, then that day should return 0 in the SQL result.

activity_id    group_id    day1result    day2result    day3result    day4result    day5result    day6 result
-----------    --------    ----------    ----------    ----------    ----------    ----------    -----------
sample1        Secured     0             5             1             0             2             1
sample2        Unsecured   1             0             0             4             3             2

Note: Currently I am planning on handling this in the business logic, but that would require multiple queries (one to create a list of distinct activities for that user for the date range, and one for each activity looping through each date for a result or lack of result, to populate the 2nd dimension of the array with date-related results). That could end up with 50+ queries for each user per date range, which seems like overkill to me.

I got this working for 4 days and I can get it working for all 6 days, but it seems like overkill. Is there a way to simplify this?:

SELECT d1d2.activity_id, ISNULL(d1d2.result1,0) AS day1, ISNULL(d1d2.result2,0) AS day2, ISNULL(d3d4.result3,0) AS day3, ISNULL(d3d4.result4,0) AS day4
FROM
    (SELECT ISNULL(d1.activity_id,0) AS activity_id, ISNULL(result1,0) AS result1, ISNULL(result2,0) AS result2
     FROM
         (SELECT ISNULL(statistic_result,0) AS result1, ISNULL(activity_id,0) AS activity_id
          FROM statistic 
              WHERE user_id='jeremiah' AND statistic_date='11/22/2011'
          ) d1
          FROM JOIN
          (SELECT ISNULL(statistic_result,0) AS result2, ISNULL(activity_id,0) AS activity_id
           FROM statistic WHERE user_id='jeremiah' AND statistic_date='11/23/2011'
          ) d2
          ON d1.activity_id=d2.activity_id
     ) d1d2
     FULL JOIN
     (SELECT d3.activity_id AS activity_id, ISNULL(d3.result3,0) AS result3, ISNULL(d4.result4,0) AS result4
      FROM
          (SELECT ISNULL(statistic_result,0) AS result3, ISNULL(activity_id,0) AS activity_id
           FROM statistic WHERE user_id='jeremiah' AND statistic_date='11/24/2011'
          ) d3
          FULL JOIN
          (SELECT ISNULL(statistic_result,0) AS result4, ISNULL(activity_id,0) AS activity_id
           FROM statistic WHERE user_id='jeremiah' AND statistic_date='11/25/2011'
          ) d4
          ON d3.activity_id=d4.activity_id
     ) d3d4
     ON d1d2.activity_id=d3d4.activity_id
ORDER BY d1d2.activity_id

Answer 1

Here is a typical approach for this kind of thing:

DECLARE @minDate DATETIME,
        @maxdate DATETIME,
        @userID VARCHAR(200)

SELECT  @minDate = '2011-11-15 00:00:00',
        @maxDate = '2011-11-22 23:59:59',
        @userID = 'jeremiah'

SELECT A.activity_id, A.group_id, 
        SUM(CASE WHEN DATEDIFF(day, @minDate, S.date) = 0 THEN S.Result ELSE 0 END) AS Day1Result,
        SUM(CASE WHEN DATEDIFF(day, @minDate, S.date) = 1 THEN S.Result ELSE 0 END) AS Day2Result,
        SUM(CASE WHEN DATEDIFF(day, @minDate, S.date) = 2 THEN S.Result ELSE 0 END) AS Day3Result,
        SUM(CASE WHEN DATEDIFF(day, @minDate, S.date) = 3 THEN S.Result ELSE 0 END) AS Day4Result,
        SUM(CASE WHEN DATEDIFF(day, @minDate, S.date) = 4 THEN S.Result ELSE 0 END) AS Day5Result,
        SUM(CASE WHEN DATEDIFF(day, @minDate, S.date) = 5 THEN S.Result ELSE 0 END) AS Day6Result
FROM activity A 
    LEFT OUTER JOIN statistic S 
        ON A.activity_id = S.activity_ID
            AND S.user_id = @userID
WHERE S.date between @minDate AND @maxDate 
GROUP BY A.activity_id, A.group_id 

First, I’m using group by to reduce the resultset to one row per activity_id/group_id, then I’m using CASE to separate values for each individual column. In this case I’m looking at which day in the last seven, but you can use whatever logic there to determine what date. The case statements will return the value of S.result if the row is for that particular day, or 0 if it’s not. SUM will add up the individual values (or just the one, if there is only one) and consolidate that into a single row.

You’ll also note my date range is based on midnight on the first day in the range and 11:59PM on the last day of the range to ensure all times are included in the range.

Finally, I’m performing a left join so you will always have a 0 in your columns, even if there are no statistics.