Displaying the difference between rows in the same table - sql

Question

I have a table named Employee_audit with following schema,
emp_audit_id
eid
name
salary
1
1
Daniel
1000
2
1
Dani
1000
3
1
Danny
3000
My goal is to write a SQL query which will return in following format, considering the first row also as changed value from null.
columnName
oldValue
newValue
name
null
Daniel
salary
null
1000
name
Daniel
Dani
name
Dani
Danny
salary
1000
3000
I have written the below SQL query,
WITH cte AS
(
SELECT empid,
name,
salary,
rn=ROW_NUMBER()OVER(PARTITION BY empid ORDER BY emp_audit_id)
FROM Employee_audit
)
SELECT oldname=CASE WHEN c1.Name=c2.Name THEN '' ELSE C1.Name END,
newname=CASE WHEN c1.Name=c2.Name THEN '' ELSE C2.Name END,
oldsalary=CASE WHEN c1.salary=c2.salary THEN NULL ELSE C1.salary END,
newsalary=CASE WHEN c1.salary=c2.salary THEN NULL ELSE C2.salary END
FROM cte c1 INNER JOIN cte c2
ON c1.empid=c2.empid AND c2.RN=c1.RN + 1
But it gives the result in following format
oldname
newname
oldsalary
newsalary
Daniel
Dani
null
null
Dani
Danny
1000
3000
Could you please answer me, how can I get the required result.

Answer 1

The lead and lag functions are to help you out.
The "diffs" calculates differences for each column you need to find diff to
with diffs as (
select 'name' colName, emp_audit_id, eid, lag(name, 1, null) over (partition by eid order by emp_audit_id) oldValue, name newValue
from some_table
union all
select 'salary', emp_audit_id, eid, cast(lag(salary, 1, null) over (partition by eid order by emp_audit_id) as varchar), cast(salary as varchar) newValue
from some_table
)
select *
from diffs
where oldValue <> newValue or oldValue is null
order by emp_audit_id, eid

Answer 2

If you give each row a row number in a CTE then join on yourself to the next row you can compare the old and the new values. Unioning the 2 different column names is a bit clunky however, if you needed a more robust solution you might look at pivoting the data.
You also obviously have to convert all values to a common datatype e.g. a string.
declare #Test table (emp_audit_id int, eid int, [name] varchar(32), salary money);
insert into #Test (emp_audit_id, eid, [name], salary)
values
(1, 1, 'Daniel', 1000),
(2, 1, 'Dani', 1000),
(3, 1, 'Danny', 3000);
with cte as (
select emp_audit_id, eid, [name], salary
, row_number() over (partition by eid order by emp_audit_id) rn
from #Test
)
select C.emp_audit_id, 'name' columnName, P.[Name] oldValue, C.[name] newValue
from cte C
left join cte P on P.eid = C.eid and P.rn + 1 = C.rn
where coalesce(C.[name],'') != coalesce(P.[Name],'')
union all
select C.emp_audit_id, 'salary' columnName, convert(varchar(21),P.salary), convert(varchar(21),C.salary)
from cte C
left join cte P on P.eid = C.eid and P.rn + 1 = C.rn
where coalesce(C.salary,0) != coalesce(P.salary,0)
order by C.emp_audit_id, columnName;
Returns:
emp_audit_id
columnName
oldValue
newValue
1
name
NULL
Daniel
1
salary
NULL
1000.00
2
name
Daniel
Dani
3
name
Dani
Danny
3
salary
1000.00
3000.00
I highly encourage you to add DDL+DML (as show above) to all your future questions as it makes it much easier for people to assist.