Reputation: 2628
I'm needing to verify a source system with a destination system and ensure the values are matching between them. The problem is the source system is a total mess and is proving hard to validate.
I've got the following sample data where they should all be OK, but they're showing as ERROR. Does anyone know a way of doing a comparison that would result as an OK for all for the below?
CREATE TABLE #testdata (
ID INT
,ValueSource VARCHAR(800)
,ValueDestination VARCHAR(800)
,Value_Varchar_Check AS (
CASE
WHEN coalesce(ValueSource, '0') = coalesce(ValueDestination, '0')
THEN 'OK'
ELSE 'ERROR'
END
)
)
INSERT INTO #testdata (
ID
,ValueSource
,ValueDestination
)
SELECT 1
,'hepatitis c,other (specify)' 'hepatitis c, other (specify)'
UNION ALL
SELECT 2
,'lung problems / asthma,lung problems / asthma'
,'lung problems / asthma'
UNION ALL
SELECT 3
,'lung problems / asthma,diabetes'
,'diabetes, lung problems / asthma'
UNION ALL
SELECT 4
,'seizures/epilepsy,hepatitis c,seizures/epilepsy'
,'hepatitis c, seizures/epilepsy'
Upvotes: 0
Views: 40
Reputation: 147206
I don't think you can write this as a generated column as it is quite a tricky thing to compute. If you are using SQL Server 2016 or later, you can use STRING_SPLIT
to convert the ValueSource
and ValueDestination
values into tables and then sort them alphabetically using a query like this:
SELECT DISTINCT ID, TRIM(value) AS value,
DENSE_RANK() OVER (PARTITION BY ID ORDER BY TRIM(value)) AS rn
FROM testdata
CROSS APPLY STRING_SPLIT(ValueSource, ',')
For ValueSource
, this produces:
ID value rn
1 hepatitis c 1
1 other (specify) 2
2 lung problems / asthma 1
3 diabetes 1
3 lung problems / asthma 2
4 hepatitis c 1
4 seizures/epilepsy 2
You can then FULL OUTER JOIN
those two tables on ID
, value
and rn
, and detect an error when there are null values from either side (since that implies that the values for a given ID
and rn
don't match):
WITH t1 AS (
SELECT DISTINCT ID, TRIM(value) AS value,
DENSE_RANK() OVER (PARTITION BY ID ORDER BY TRIM(value)) AS rn
FROM testdata
CROSS APPLY STRING_SPLIT(ValueSource, ',')
),
t2 AS (
SELECT DISTINCT ID, TRIM(value) AS value,
DENSE_RANK() OVER (PARTITION BY ID ORDER BY TRIM(value)) AS rn
FROM testdata
CROSS APPLY STRING_SPLIT(ValueDestination, ',')
)
SELECT COALESCE(t1.ID, t2.ID) AS ID,
CASE WHEN COUNT(CASE WHEN t1.value IS NULL OR t2.value IS NULL THEN 1 END) > 0 THEN 'Error'
ELSE 'OK'
END AS Status
FROM t1
FULL OUTER JOIN t2 ON t2.ID = t1.ID AND t2.rn = t1.rn AND t2.value = t1.value
GROUP BY COALESCE(t1.ID, t2.ID)
Output (for your sample data):
ID Status
1 OK
2 OK
3 OK
4 OK
You can then use the entire query above as a CTE
(call it t3
) to update your original table:
UPDATE t
SET t.Value_Varchar_Check = t3.Status
FROM testdata t
JOIN t3 ON t.ID = t3.ID
Output:
ID ValueSource ValueDestination Value_Varchar_Check
1 hepatitis c,other (specify) hepatitis c, other (specify) OK
2 lung problems / asthma,lung problems / asthma lung problems / asthma OK
3 lung problems / asthma,diabetes diabetes, lung problems / asthma OK
4 seizures/epilepsy,hepatitis c,seizures/epilepsy hepatitis c, seizures/epilepsy OK
Upvotes: 2