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SQL Query

Posted on 2015-01-23
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Last Modified: 2015-01-27
I have a view I'm trying to query - it has a today column, yesterday column, thismonth column, and a lastmonth column as well as price info.

I want a summary of results - total price for today, total price for yesterday, total price this month (including today and yesterday), total price for last month (including yesterday if that is applicable.

I have attached the script to create a temp table which looks like the view.

My end result should look like

period records   Total                                   $/record
--------- ----------- --------------------------------------- ---------------------
lastmonth         1447        1949.49                                 1.3473
this month         1321        1674.32                                 1.2675
today         28          35.40                                   1.2643
yesterday         50          75.00                                   1.50

How can i query ?
table-contents.sql
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Question by:enjama
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LVL 35

Accepted Solution

by:
David Todd earned 500 total points
ID: 40567171
Hi,

Given your data and requirements, I've got the following which appears to work - fairly ugly though
select 
	'Today' as period
	, count( * ) as records
	, sum( convert( money, t.price_sum )) as total
	, sum( convert( money, t.price_sum )) / count( * ) as [$/record]
from #tmp_GridResults_1 t
where 
	t.today = 1

union all

select 
	'Yesterday' as period
	, count( * ) as records
	, sum( convert( money, t.price_sum )) as total
	, sum( convert( money, t.price_sum )) / count( * ) as [$/record]
from #tmp_GridResults_1 t
where 
	t.yesterday = 1

union all

select 
	'This month' as period
	, count( * ) as records
	, sum( convert( money, t.price_sum )) as total
	, sum( convert( money, t.price_sum )) / count( * ) as [$/record]
from #tmp_GridResults_1 t
where 
	t.thismonth = 1

union all

select 
	'Last month' as period
	, count( * ) as records
	, sum( convert( money, t.price_sum )) as total
	, sum( convert( money, t.price_sum )) / count( * ) as [$/record]
from #tmp_GridResults_1 t
where 
	t.lastmonth = 1
;

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Now if the periods were a little more even and had a datetime field, then you could do something like

select
	dateadd( month, datediff( month, 0, t.TransactionDate ), 0 ) as StartOfPeriod
	, count( * ) as Records
	, sum( t.TransactionValue ) as Total
	, sum( t.TransactionValue ) / count( * ) as AverageTransaction
from dbo.TransactionTable t
where
	somewhereclause
group by
	dateadd( month, datediff( month, 0, t.TransactionDate ), 0 )
order by
	dateadd( month, datediff( month, 0, t.TransactionDate ), 0 )
;

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HTH
  David
0
 

Author Comment

by:enjama
ID: 40570487
I did the union all before I posted this question.  The execution plan is slow - any way to speed it up?  I'm thinking grouping sets?
0
 
LVL 48

Expert Comment

by:PortletPaul
ID: 40571586
It would help performance if your data wasn't stored as nvarchar columns. Instead make them integers or money as fits the data. Not sure why that temp table was all nvarchar.

This approach avoids unions. Instead it does a simple group by (as a subquery) then "unpivots" that result using cross apply with values (for more on that technique see this blog and this EE article )

select
       ca.period
     , ca.records
     , ca.total
     , ca.total / ca.records as "$/record"
from (
      select
            [period]
          , sum([price_sum]) as [price_sum]
          , count(*) as [records]
      from (
            select
                  case when [today]     = 1 then 'Today'
                       when [yesterday] = 1 then 'Yesterday'
                       when [thismonth] = 1 then 'This Month'
                       when [lastmonth] = 1 then 'Last Month'
                       end as [period]
                , convert( money, t.price_sum ) as [price_sum]
            from tmp_GridResults_1 t
          ) as u
      group by
            [period]
     ) as v
cross apply (
      values
             (case when v.period = 'Today'      then [period] end, case when v.period = 'Today'      then v.[records] end, case when v.period = 'Today'      then v.[price_sum] end )
           , (case when v.period = 'Yesterday'  then [period] end, case when v.period = 'Yesterday'  then v.[records] end, case when v.period = 'Yesterday'  then v.[price_sum] end )
           , (case when v.period = 'This Month' then [period] end, case when v.period = 'This Month' then v.[records] end, case when v.period = 'This Month' then v.[price_sum] end )
           , (case when v.period = 'Last Month' then [period] end, case when v.period = 'Last Month' then v.[records] end, case when v.period = 'Last Month' then v.[price_sum] end )
       ) as ca ([period],[records],[total])
where ca.period is not null
;

Open in new window


Details:
**MS SQL Server 2008 Schema Setup**:

    
    
    CREATE TABLE tmp_GridResults_1
    	([TODAY] int, [YESTERDAY] int, [THISMONTH] int, [LASTMONTH] int, [RECORD_ID] int, [PRICE] int, [RECORD_COUNT] int, [PRICE_SUM] int)
    ;
    	
    INSERT INTO tmp_GridResults_1
    	([TODAY], [YESTERDAY], [THISMONTH], [LASTMONTH], [RECORD_ID], [PRICE], [RECORD_COUNT], [PRICE_SUM])
    VALUES
    	(1, 0, 0, 0, 8108364, 0.60, 1, 0.60),
    	(1, 0, 0, 0, 8139339, 1.00, 1, 1.00),
    	(1, 0, 0, 0, 8150460, 4.00, 1, 4.00),
    	(1, 0, 0, 0, 8155862, 4.00, 1, 4.00),
    	(1, 0, 0, 0, 8157908, 1.00, 1, 1.00),
    	(1, 0, 0, 0, 8158261, 1.00, 1, 1.00),
    	(1, 0, 0, 0, 8158277, 4.00, 1, 4.00),
    
    	(0, 1, 0, 0, 8108364, 0.60, 1, 0.60),
    	(0, 1, 0, 0, 8139339, 1.00, 1, 1.00),
    	(0, 1, 0, 0, 8150460, 4.00, 1, 4.00),
    	(0, 1, 0, 0, 8155862, 4.00, 1, 4.00),
    	(0, 1, 0, 0, 8157908, 1.00, 1, 1.00),
    	(0, 1, 0, 0, 8158261, 1.00, 1, 1.00),
    	(0, 1, 0, 0, 8158277, 4.00, 1, 4.00),
    
    
    	(0, 0, 1, 0, 8108364, 0.60, 1, 0.60),
    	(0, 0, 1, 0, 8139339, 1.00, 1, 1.00),
    	(0, 0, 1, 0, 8150460, 4.00, 1, 4.00),
    	(0, 0, 1, 0, 8155862, 4.00, 1, 4.00),
    	(0, 0, 1, 0, 8157908, 1.00, 1, 1.00),
    	(0, 0, 1, 0, 8158261, 1.00, 1, 1.00),
    	(0, 0, 1, 0, 8158277, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8108364, 0.60, 1, 0.60),
    	(0, 0, 0, 1, 8139339, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8150460, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8155862, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8157908, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8158261, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8158277, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8158370, 0.40, 1, 0.40),
    	(0, 0, 0, 1, 8158468, 0.10, 1, 0.10),
    	(0, 0, 0, 1, 8162133, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8185991, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8198302, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8198587, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8205676, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8219799, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8223108, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8223391, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8224794, 0.10, 1, 0.10),
    	(0, 0, 0, 1, 8225338, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8225440, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8226264, 0.20, 1, 0.20),
    	(0, 0, 0, 1, 8226765, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8227505, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8227628, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8228380, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8228787, 0.20, 1, 0.20),
    	(0, 0, 0, 1, 8228975, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8228989, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8229130, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8229370, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8230594, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8230677, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8230691, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8230900, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8230921, 0.80, 1, 0.80),
    	(0, 0, 0, 1, 8230927, 0.40, 1, 0.40),
    	(0, 0, 0, 1, 8231002, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231101, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231110, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231120, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231164, 0.20, 1, 0.20),
    	(0, 0, 0, 1, 8231267, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8231390, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231444, 0.20, 1, 0.20),
    	(0, 0, 0, 1, 8231559, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231681, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8231760, 0.90, 1, 0.90),
    	(0, 0, 0, 1, 8231793, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231807, 0.80, 1, 0.80),
    	(0, 0, 0, 1, 8231817, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8231856, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8231891, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231938, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8231973, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8231981, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8232014, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232094, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232128, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232160, 0.50, 1, 0.50),
    	(0, 0, 0, 1, 8232175, 0.10, 1, 0.10),
    	(0, 0, 0, 1, 8232210, 0.10, 1, 0.10),
    	(0, 0, 0, 1, 8232267, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232318, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232334, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232346, 1.00, 1, 1.00),
    	(0, 0, 0, 1, 8232387, 4.00, 1, 4.00),
    	(0, 0, 0, 1, 8232444, 1.00, 1, 1.00)
    ;

**Query 1**:

    select
           ca.period
         , ca.records
         , ca.total
         , ca.total / ca.records as "$/record"
    from (
          select
                [period]
              , sum([price_sum]) as [price_sum]
              , count(*) as [records]
          from (
                select
                      case when [today]     = 1 then 'Today'
                           when [yesterday] = 1 then 'Yesterday'
                           when [thismonth] = 1 then 'This Month'
                           when [lastmonth] = 1 then 'Last Month'
                           end as [period]
                    , convert( money, t.price_sum ) as [price_sum]
                from tmp_GridResults_1 t
              ) as u
          group by
                [period]
         ) as v
    cross apply (
          values
                 (case when v.period = 'Today'      then [period] end, case when v.period = 'Today'      then v.[records] end, case when v.period = 'Today'      then v.[price_sum] end )
               , (case when v.period = 'Yesterday'  then [period] end, case when v.period = 'Yesterday'  then v.[records] end, case when v.period = 'Yesterday'  then v.[price_sum] end )
               , (case when v.period = 'This Month' then [period] end, case when v.period = 'This Month' then v.[records] end, case when v.period = 'This Month' then v.[price_sum] end )
               , (case when v.period = 'Last Month' then [period] end, case when v.period = 'Last Month' then v.[records] end, case when v.period = 'Last Month' then v.[price_sum] end )
           ) as ca ([period],[records],[total])
    where ca.period is not null
    

**[Results][2]**:
    
    |     PERIOD | RECORDS | TOTAL | $/RECORD |
    |------------|---------|-------|----------|
    | Last Month |      67 |    77 |   1.1492 |
    | This Month |       7 |    15 |   2.1428 |
    |      Today |       7 |    15 |   2.1428 |
    |  Yesterday |       7 |    15 |   2.1428 |



  [1]: http://sqlfiddle.com/#!3/f25471/9

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0
 

Author Comment

by:enjama
ID: 40572719
This was very much like my original query, and it does the same thing, yesterday and today need to be included in this month - with this they are not.
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LVL 35

Expert Comment

by:David Todd
ID: 40574263
Hi,

I suggest then that you look at the group I did.

Write two queries: Group one by months, and one by days, and union the results together.

HTH
  David

PS With the dates as datetimes you'll find that performance is fairly good.
0
 
LVL 48

Expert Comment

by:PortletPaul
ID: 40574335
select
        [period]
      , sum([price_sum]) as [price_sum]
      , count(*) as [records]
      , sum([price_sum]) /  count(*) as "$/record"
from (
      select
            ca.*
      from tmp_GridResults_1 t
      cross apply (
            values 
                    (case when [today]=1     then 'today'     end, case when [today]=1     then record_id end, case when [today]=1     then convert(money,price_sum) end)
                  , (case when [yesterday]=1 then 'yesterday' end, case when [yesterday]=1 then record_id end, case when [yesterday]=1 then convert(money,price_sum) end)
                  , (case when [lastmonth]=1 then 'lastmonth' end, case when [lastmonth]=1 then record_id end, case when [lastmonth]=1 then convert(money,price_sum) end)
                  , (
                      case when [today]=1 or [yesterday]=1 or [thismonth]=1 then 'thismonth' end
                    , case when [today]=1 or [yesterday]=1 or [thismonth]=1 then record_id end
                    , case when [today]=1 or [yesterday]=1 or [thismonth]=1 then convert(money,price_sum) end
                  )
            ) ca (period,record_id, price_sum)
      where ca.period is not null
    ) as u
group by
      [period]
;

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0
 

Author Closing Comment

by:enjama
ID: 40574381
Thanks David!  I'm accepting your solution, although I ended up grouping by grouping sets.
0
 
LVL 48

Expert Comment

by:PortletPaul
ID: 40574429
did you not try my last suggestion? oh well, just seems odd as you specifically asked not to union.
0
 
LVL 35

Expert Comment

by:David Todd
ID: 40574512
Hi,

There's a couple of points implied in my answer that often have to spelt out to the business.
1. Sometimes the requirements should be changed a little to simplify the reporting.
2. Sometimes the data needs to be shaped for said reporting.

What do I mean? For instance, in the above scenario, mixing days and months in the grouping meant that there was no one measure to group on.

Shaping the data - I find it relatively easy to group on datetime fields by the datepart interval. I've seen a post where the datetime dimension for a datamart had almost every conceivable derivation of the datetime. The logic behind it was that the reporting was easier.

HTH
  David
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