Combining multiple aggregate functions in a single query can be a powerful tool in SQL, but it's important to follow best practices to ensure your query is efficient and accurate. Here are some steps to follow:

1. **Use DISTINCT Clause Carefully**: When using aggregate functions like COUNT, SUM, AVG, etc., be careful with the DISTINCT clause. It can significantly slow down your query if used with large datasets. Use it only when necessary.

2. **Group By Clause**: When using multiple aggregate functions in a single query, it's often necessary to use the GROUP BY clause. This allows you to aggregate data in different groups, based on one or more columns.

3. **Having Clause**: If you want to filter the results of your aggregate functions, use the HAVING clause. This works similarly to the WHERE clause but is used after the GROUP BY clause.

4. **Order of Execution**: Remember the order of execution in SQL. FROM clause is executed first, then WHERE, GROUP BY, HAVING, SELECT, ORDER BY. Knowing this order can help you write more efficient queries.

5. **Subqueries**: Sometimes, it might be more efficient to use subqueries instead of trying to do everything in a single query. This can make your query easier to read and understand, and also improve performance in some cases.

6. **Indexes**: If you're working with large datasets, consider using indexes on the columns that you're using in your aggregate functions. This can significantly speed up your query.

7. **Test Your Query**: Always test your query with different datasets to ensure it's returning the expected results. This is especially important when using multiple aggregate functions in a single query.

8. **Comment Your Code**: If your query is complex, consider adding comments to explain what each part of the query does. This can make it easier for others (or future you) to understand what the query does.

Question

Combining multiple aggregate functions in a single query can be a powerful tool in SQL, but it's important to follow best practices to ensure your query is efficient and accurate. Here are some steps to follow:

1. **Use DISTINCT Clause Carefully**: When using aggregate functions like COUNT, SUM, AVG, etc., be careful with the DISTINCT clause. It can significantly slow down your query if used with large datasets. Use it only when necessary.

2. **Group By Clause**: When using multiple aggregate functions in a single query, it's often necessary to use the GROUP BY clause. This allows you to aggregate data in different groups, based on one or more columns.

3. **Having Clause**: If you want to filter the results of your aggregate functions, use the HAVING clause. This works similarly to the WHERE clause but is used after the GROUP BY clause.

4. **Order of Execution**: Remember the order of execution in SQL. FROM clause is executed first, then WHERE, GROUP BY, HAVING, SELECT, ORDER BY. Knowing this order can help you write more efficient queries.

5. **Subqueries**: Sometimes, it might be more efficient to use subqueries instead of trying to do everything in a single query. This can make your query easier to read and understand, and also improve performance in some cases.

6. **Indexes**: If you're working with large datasets, consider using indexes on the columns that you're using in your aggregate functions. This can significantly speed up your query.

7. **Test Your Query**: Always test your query with different datasets to ensure it's returning the expected results. This is especially important when using multiple aggregate functions in a single query.

8. **Comment Your Code**: If your query is complex, consider adding comments to explain what each part of the query does. This can make it easier for others (or future you) to understand what the query does.

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