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Avoiding Data Loss in PIVOT Queries for Distinct Records
Problem:
PIVOT queries are useful for restructuring data to display information in a more organized manner. However, when dealing with distinct records, the MAX aggregation function can cause zero values to be omitted, leading to incomplete data.
Solution:
To preserve all distinct records, even those with zero values, one can incorporate the ROW_NUMBER() function into the PIVOT query. This approach assigns a row number to each record, maintaining the association between activities and percentages.
;with cte as ( select *, ROW_NUMBER() over (partition by name order by percentage desc) ROWNUM from A ), cte2 as ( SELECT Id,Code,ROWNUM,James,James_,Sam,Sam_,Lisa,Lisa_ FROM cte PIVOT(MAX(activity) FOR name IN (James,Sam,Lisa)) AS PVTTable PIVOT ( MAX(percentage) FOR name1 IN (James_,Sam_,Lisa_)) AS PVTTable1 ) select Id, Code, MAX(James) James, MAX(James_) James_, MAX(Sam) Sam, MAX(Sam_) Sam_, MAX(Lisa) Lisa, MAX(Lisa_) Lisa_ from cte2 group by Id, Code, ROWNUM
Example:
Consider the following table:
Id | Code | percentage | name | name1 | activity |
---|---|---|---|---|---|
1 | Prashant | 43.43 | James | James_ | Running |
1 | Prashant | 70.43 | Sam | Sam_ | Cooking |
1 | Prashant | 90.34 | Lisa | Lisa_ | Walking |
1 | Prashant | 0.00 | James | James_ | Stealing |
1 | Prashant | 0.00 | James | James_ | Lacking |
1 | Prashant | 73 | Sam | Sam_ | Cooking 1 |
Previously, a standard PIVOT query would have produced the following result:
Id | Code | James | James_ | Sam | Sam_ | Lisa | Lisa_ |
---|---|---|---|---|---|---|---|
1 | Prashant | Running | 43.43 | Cooking 1 | 73 | Walking | 90.34 |
1 | Prashant | Stealing | 0.0 | Cooking | 3.43 | NULL | NULL |
1 | Prashant | NULL | NULL | NULL | NULL | NULL | NULL |
However, by incorporating the ROW_NUMBER() function, the modified query retains all distinct records:
Id | Code | James | James_ | Sam | Sam_ | Lisa | Lisa_ |
---|---|---|---|---|---|---|---|
1 | Prashant | Running | 43.43 | Cooking 1 | 73 | Walking | 90.34 |
1 | Prashant | Stealing | 0.00 | Cooking | 3.43 | NULL | NULL |
1 | Prashant | Lacking | 0.00 | NULL | NULL | NULL | NULL |
This approach ensures that all distinct activities are displayed, even those with zero percentage values, providing a more accurate representation of the data.
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