“Combining Data with SQL: Using CTEs vs. Temporary Tables for UNION Queries”

you can use both CTEs (Common Table Expressions) and Temporary Tables to perform a UNION operation in SQL. Here’s how each option can be used:

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1. Using CTE for a UNION Query

You can define multiple CTEs and then use a UNION or UNION ALL to combine the results. This approach is clean and keeps the code organized, especially if you need to combine more than two result sets.

Example:

sqlCopy codeWITH CTE1 AS (
    SELECT column1, column2
    FROM table1
),
CTE2 AS (
    SELECT column1, column2
    FROM table2
)
SELECT * FROM CTE1
UNION
SELECT * FROM CTE2;

• Note: Using UNION removes duplicates, while UNION ALL includes all rows, including duplicates.
• This is useful for combining related datasets that you won’t need to store or index separately, and for keeping queries concise when working with multiple sources.

2. Using a Temporary Table for a UNION Query

Temporary tables are also effective for UNION operations, especially if you need to perform further operations on the combined data (e.g., adding indexes, sorting, or filtering across multiple statements).

With a temporary table, you can insert data from multiple tables into the temp table with UNION:

Example:

sqlCopy codeCREATE TABLE #TempTable (column1 datatype, column2 datatype);

INSERT INTO #TempTable
SELECT column1, column2 FROM table1
UNION
SELECT column1, column2 FROM table2;

-- Now you can work with #TempTable for further analysis
SELECT * FROM #TempTable;

-- Drop the temporary table when done
DROP TABLE #TempTable;

• This approach allows more complex operations on the resulting dataset, and the data will persist across multiple statements in your session.

When to Use Each Approach

• CTE: Ideal for simple, one-time UNION operations, particularly when organizing data for readability and using the combined results within a single query.
• Temporary Table: Best for cases where the unioned dataset needs to be reused across multiple statements, when indexing might improve performance, or when working with large result sets.

Both methods are viable, so the choice depends on the query’s complexity, performance needs, and whether you need to store or manipulate the unioned data further.