Getting Distinct Rows on SQL Query with Multiple IIF Columns

As a developer, it’s not uncommon to encounter complex queries that require creative solutions. In this article, we’ll delve into a specific problem where we need to get distinct rows from an SQL query using multiple IIF columns.

Problem Statement

Suppose we have two tables: CONTACTS and TAGS. We want to create a view that shows if a record in the CONTACTS table has certain tags in the TAGS table. The query is as follows:

SELECT DISTINCT
    contacts.ID, contacts.NAME,
    IIF(tags.tag = 'A', 1, 0) as A,
    IIF(tags.tag = 'B', 1, 0) as B,
    IIF(tags.tag = 'C', 1, 0) as C,
    IIF(tags.tag = 'D', 1, 0) as D
FROM
    contacts 
LEFT JOIN
    TAGS ON contacts.ID = TAGS.CONTACT_ID

The expected output is:

ID     NAME     A     B     C     D
------------------------------------
1      BOB      1     0     0     1
1      Charlie  1     0     1     0

However, the actual output is:

ID     NAME     A     B     C     D
------------------------------------
1      BOB      1     0     0     0
1      BOB      0     0     0     1
1      Charlie  1     0     0     0
1      Charlie  0     0     1     0

As we can see, the results are not distinct as expected.

Solution

To fix this issue, we need to use a different approach. The problem lies in using DISTINCT on columns that contain non-numeric values (in this case, IIF columns). We can achieve this by grouping the rows based on the unique combinations of these columns and then selecting the maximum value for each group.

Here’s an updated query:

SELECT contacts.ID, contacts.NAME
    , MAX(IIF(tags.tag = 'A', 1, 0)) as A
    , MAX(IIF(tags.tag = 'B', 1, 0)) as B
    , MAX(IIF(tags.tag = 'C', 1, 0)) as C
    , MAX(IIF(tags.tag = 'D', 1, 0)) as D
FROM            contacts LEFT  JOIN
                     TAGS ON contacts.ID = TAGS.CONTACT_ID
group by
    contacts.ID, contacts.NAME

This query uses the MAX aggregation function to select the maximum value for each group of rows with the same ID and NAME. This effectively groups the results based on the unique combinations of these columns.

Alternative Approach using Standard SQL Case When

Another approach is to use standard SQL’s CASE WHEN statement instead of IIF. Here’s an updated query:

SELECT contacts.ID, contacts.NAME
    , SUM(CASE WHEN tags.tag = 'A' THEN 1 ELSE 0 END) as A
    , SUM(CASE WHEN tags.tag = 'B' THEN 1 ELSE 0 END) as B
    , SUM(CASE WHEN tags.tag = 'C' THEN 1 ELSE 0 END) as C
    , SUM(CASE WHEN tags.tag = 'D' THEN 1 ELSE 0 END) as D
FROM            contacts LEFT  JOIN
                     TAGS ON contacts.ID = TAGS.CONTACT_ID
group by
    contacts.ID, contacts.NAME

This query uses the CASE WHEN statement to evaluate a condition and return either 1 or 0. The SUM aggregation function is then used to calculate the total value for each group of rows.

Comparison

Both approaches achieve the same result: grouping the results based on unique combinations of columns and selecting the maximum value for each group. However, using standard SQL’s CASE WHEN statement provides more flexibility and compatibility across different databases.

In addition, using CASE WHEN allows us to avoid issues with non-numeric values in columns that contain IIF. For example, if we had another column that contains string values, we could use a similar approach to evaluate the condition without encountering errors.

Conclusion

In conclusion, getting distinct rows on SQL queries with multiple IIF columns requires careful consideration of how to group and aggregate the results. By using either the MAX aggregation function or standard SQL’s CASE WHEN statement, we can effectively address this issue and achieve the desired output.

When working with complex queries, it’s essential to consider various approaches and evaluate their pros and cons before choosing a solution. In this case, both methods provide a viable alternative to the original query and help us achieve our goal of getting distinct rows from the SQL query.

Last modified on 2023-07-06