Question

I have audit for records in a table. There multiple columns and each records states for a change of 1 or more columns.
I need to return an audit result where the return pattern will be: column (id, alias or name), previous value, new value, etc.
The problem is in that there can be multiple columns with changed data per each new record. At the same time the quantity of auditable columns is 5 so it’s possible to “hardcode” there names and changes verifications.

So is it possible to compose such a query in a shortened manner not just using UNIONS and make a SELECT query for each column and check for change?

Let’s say there is the table with the columns:

id, datetime value, int value, varchar value.

And if I have 2 records with such a data change as like:

id1, value1, value1, value1
id1, value2, value1, value2

Then I expect such audit results:

id1, value1 as oldvalue, value2 as newvalue, column2name as columnname
id1, value1 as oldvalue, value2 as newvalue, column4name as columnname

Answer 1

If I haven’t missed anything:

WITH ranked AS (
  SELECT
    ChangeDate,
    ColPK,
    Col1,
    Col2,
    Col3,
    Col4,
    Col5,
    OverallRank = ROW_NUMBER() OVER (PARTITION BY ColPK       ORDER BY ChangeDate),
    Col1Rank    = ROW_NUMBER() OVER (PARTITION BY ColPK, Col1 ORDER BY ChangeDate),
    Col2Rank    = ROW_NUMBER() OVER (PARTITION BY ColPK, Col2 ORDER BY ChangeDate),
    Col3Rank    = ROW_NUMBER() OVER (PARTITION BY ColPK, Col3 ORDER BY ChangeDate),
    Col4Rank    = ROW_NUMBER() OVER (PARTITION BY ColPK, Col4 ORDER BY ChangeDate),
    Col5Rank    = ROW_NUMBER() OVER (PARTITION BY ColPK, Col5 ORDER BY ChangeDate)
  FROM AuditTable
)
, ranked2 AS (
  SELECT
    ChangeDate,
    ColPK,
    Col1,
    Col2,
    Col3,
    Col4,
    Col5,
    Col1Group = RANK() OVER (PARTITION BY ColPK, Col1 ORDER BY OverallRank - Col1Rank),
    Col2Group = RANK() OVER (PARTITION BY ColPK, Col2 ORDER BY OverallRank - Col2Rank),
    Col3Group = RANK() OVER (PARTITION BY ColPK, Col3 ORDER BY OverallRank - Col3Rank),
    Col4Group = RANK() OVER (PARTITION BY ColPK, Col4 ORDER BY OverallRank - Col4Rank),
    Col5Group = RANK() OVER (PARTITION BY ColPK, Col5 ORDER BY OverallRank - Col5Rank),
    Col1Rank = ROW_NUMBER() OVER (PARTITION BY ColPK, Col1, OverallRank - Col1Rank ORDER BY ChangeDate),
    Col2Rank = ROW_NUMBER() OVER (PARTITION BY ColPK, Col2, OverallRank - Col2Rank ORDER BY ChangeDate),
    Col3Rank = ROW_NUMBER() OVER (PARTITION BY ColPK, Col3, OverallRank - Col3Rank ORDER BY ChangeDate),
    Col4Rank = ROW_NUMBER() OVER (PARTITION BY ColPK, Col4, OverallRank - Col4Rank ORDER BY ChangeDate),
    Col5Rank = ROW_NUMBER() OVER (PARTITION BY ColPK, Col5, OverallRank - Col5Rank ORDER BY ChangeDate)
  FROM ranked
),
unpivoted AS (
  SELECT
    r.ChangeTime,
    r.ColPK,
    x.ColName,
    ColRank = CASE x.Colname
      WHEN 'Col1' THEN Col1Group
      WHEN 'Col2' THEN Col2Group
      WHEN 'Col3' THEN Col3Group
      WHEN 'Col4' THEN Col4Group
      WHEN 'Col5' THEN Col5Group
    END,
    Value = CASE x.Colname
      WHEN 'Col1' THEN CONVERT(nvarchar(100), r.Col1)
      WHEN 'Col2' THEN CONVERT(nvarchar(100), r.Col2)
      WHEN 'Col3' THEN CONVERT(nvarchar(100), r.Col3)
      WHEN 'Col4' THEN CONVERT(nvarchar(100), r.Col4)
      WHEN 'Col5' THEN CONVERT(nvarchar(100), r.Col5)
    END
  FROM ranked2 r
    INNER JOIN (VALUES ('Col1'), ('Col2'), ('Col3'), ('Col4'), ('Col5')) x (ColName)
      ON x.ColName = 'Col1' AND Col1Rank = 1
      OR x.ColName = 'Col2' AND Col2Rank = 1
      OR x.ColName = 'Col3' AND Col3Rank = 1
      OR x.ColName = 'Col4' AND Col4Rank = 1
      OR x.ColName = 'Col5' AND Col5Rank = 1
)
SELECT
  new.ChangeTime,
  new.ColPK,
  new.ColName,
  old.Value AS OldValue,
  new.Value AS NewValue
FROM unpivoted new
  LEFT JOIN unpivoted old
    ON new.ColPK   = old.ColPK
   AND new.ColName = old.ColName
   AND new.ColRank = old.ColRank + 1

Basically, the idea is to rank contiguous groups of identical values and pick first occurrences of every value. That is done for every column whose values are being audited, and the columns are unpivoted in the process. Afterwards, the unpivoted row set is joined to itself, i.e. for every PK and column name, every row is matched to its predecessor (based on the ranking) to obtain the old value in the same row for the final result set.