Question

The question is how long have these customers been jerks on any given date.

I’m working against Sybase

For this simplified table structure of table history_data

 table: history_of_jerkiness processing_date  name  is_jerk ---------------  ----- ------- 20090101         Matt  true 20090101         Bob   false         20090101         Alex  true         20090101         Carol true         20090102         Matt  true         20090102         Bob   true         20090102         Alex  false         20090102         Carol true         20090103         Matt  true         20090103         Bob   true         20090103         Alex  true         20090103         Carol false          

The report for the 3rd should show that Matt has always been a jerk, Alex has just become a jerk, and Bob has been a jerk for 2 days.

 name    days jerky -----   ---------- Matt    3 Bob     2 Alex    1 

I’d like to find these spans of time dynamically, so if I run the report for the 2nd, I should get different results:

 name    days_jerky -----   ---------- Matt    2 Bob     1 Carol   2 

The key here is trying to find only continuous spans older than a certain date. I’ve found a few leads, but it seems like a problem where there would be very smart tricky solutions.

Answer 1

My solution from SQL Server – same as Dems but I put in a min baseline myself. It assumes there are no gaps – that is there is an entry for each day for each person. If that isn’t true then I’d have to loop.

DECLARE @run_date datetime DECLARE @min_date datetime  SET @run_date = {d '2009-01-03'}  -- get day before any entries in the table to use as a false baseline date SELECT @min_date = DATEADD(day, -1, MIN(processing_date)) FROM history_of_jerkiness  -- get last not a jerk date for each name that is before or on the run date -- the difference in days between the run date and the last not a jerk date is the number of days as a jerk SELECT [name], DATEDIFF(day, MAX(processing_date), @run_date) FROM (      SELECT processing_date, [name], is_jerk      FROM history_of_jerkiness      UNION ALL      SELECT DISTINCT @min_date, [name], 0      FROM history_of_jerkiness ) as data WHERE is_jerk = 0   AND processing_date <= @run_date GROUP BY [name] HAVING DATEDIFF(day, MAX(processing_date), @run_date) > 0 

I created the test table with the following:

CREATE TABLE history_of_jerkiness (processing_date datetime, [name] varchar(20), is_jerk bit)  INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-01'}, 'Matt', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-01'}, 'Bob', 0) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-01'}, 'Alex', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-01'}, 'Carol', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-02'}, 'Matt', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-02'}, 'Bob', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-02'}, 'Alex', 0) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-02'}, 'Carol', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-03'}, 'Matt', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-03'}, 'Bob', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-03'}, 'Alex', 1) INSERT INTO history_of_jerkiness (processing_date, [name], is_jerk) VALUES ({d '2009-01-03'}, 'Carol', 0)