Pivot using Multiple columns in SQL - sql

Question

I need to pivot a table as show below using column "channel" and grouping it based on Units.
Actual table:
The result I need is shown below
I'm not an expert with pivotting and unpivoting concepts, I'm trying the below query to achieve the above result
SELECT [service_point_ID]
,isnull([1],0) - isnull([2],0) as net_usage_value
,[units]
,[1]
,[2]
,[channel_ID]
,[date]
,[time]
,[is_estimate]
,[UTC_offset]
,[import_history_id]
FROM #temp1
AS SourceTable PIVOT(sum(usage_value) FOR channel IN([1],[2])) AS PivotTable
If I execute this query I'm getting the below result
The same logic is achieved in r -Refernce link Pivot using Mutiple columns
Here is the SQL fiddle for this one
CREATE TABLE #temp1
(
Service_point_ID varchar(10) NUll,
usage_value decimal(18,6) NULL,
units varchar(10) NUll,
[date] Date NULL,
[time] time NULL,
channel varchar(2) NULL,
[Channel_ID] varchar(2) NULL,
is_estimate varchar(2) NULL,
UTC_Offset varchar(20) NULL
)
INSERT INTO #temp1 VALUES ('123',1.000000,'kvarh','2017-01-01','0015','1','11','A','-500')
INSERT INTO #temp1 VALUES ('123',0.200000,'kvarh','2017-01-01','0015','2','11','A','-500')
INSERT INTO #temp1 VALUES ('123',0.200000,'kwh','2017-01-01','0015','1','11','A','-500')
INSERT INTO #temp1 VALUES ('123',0.400000,'kwh','2017-01-01','0015','2','11','A','-500')
Any help is much appreciated.

Answer 1

This is solution using pivot function:
declare #table table(
service_point_id int,
usage_value float,
units varchar(10),
[date] date,
[time] char(4),
channel int,
channel_id int,
is_estimate char(1),
utc_offset int,
import_history int,
datecreated datetime
)
--example data you provided
insert into #table values
(123, 1, 'kvarh', '2017-01-01', '0015', 1, 11, 'A', -500, 317, '2018-03-20 10:32:42.817'),
(123, 0.2, 'kwh', '2017-01-01', '0015', 1, 33, 'A', -500, 317, '2018-03-20 10:32:42.817'),
(123, 0.3, 'kvarh', '2017-01-01', '0015', 2, 11, 'A', -500, 317, '2018-03-20 10:32:42.817'),
(123, 0.4, 'kwh', '2017-01-01', '0015', 2, 33, 'A', -500, 317, '2018-03-20 10:32:42.817')
--pivot query that does the work, it's only matter of aggregation one column, as mentioned already, so pivot query is really simple and concise
select *, [1]-[2] [net_usage_value] from
(select * from #table) [t]
pivot (
max(usage_value)
for channel in ([1],[2])
) [a]

Answer 2

SELECT [service_point_ID]
sum(,isnull([1],0) - isnull([2],0)) as net_usage_value
,[units]
,sum(isnull([1],0))[1]
,sum(isnull([2],0))[2]
,[channel_ID]
,[date]
,[time]
,[is_estimate]
,[UTC_offset]
,[import_history_id]
FROM #temp1
AS SourceTable PIVOT(sum(usage_value) FOR channel IN([1],[2])) AS PivotTable
group by [service_point_ID], [units],[channel_ID]
,[date]
,[time]
,[is_estimate]
,[UTC_offset]
,[import_history_id]

Answer 3

Inner join will out perform the pivot syntax. SQL Server pivot vs. multiple join
select a.usage_value - b.usage_value as net_usage_value , other columns
from #temp1 a inner join #temp1 b on a.service_point_id = b.service_point_id
and a.units = b.units
and a.channel = 1
and b.channel = 2
gets around the group by as well.