GROUP BY vs. PARTITION BY: What's the Key Difference in Aggregate Queries?

Distinguishing PARTITION BY from GROUP BY

When working with aggregate queries, GROUP BY has long been a familiar option for collating data. However, the emergence of PARTITION BY has introduced a similar concept that raises questions about its relationship to GROUP BY.

Understanding the Role of GROUP BY

GROUP BY operates at the query level, transforming the entire query result. By grouping rows based on specific columns, it condenses the data, calculating aggregate values (e.g., count, average, sum) for each group. For instance:

select customerId, count(*) as orderCount
from Orders
group by customerId

PARTITION BY: A Different Perspective

Unlike GROUP BY, PARTITION BY is associated with window functions, such as ROW_NUMBER(). It operates within the scope of window computations, modifying how these functions calculate their results. Consider the following example:

select row_number() over (partition by customerId order by orderId)
    as OrderNumberForThisCustomer
from Orders

Key Differences to Note

• Scope of Impact: GROUP BY affects the entire query result, reducing the number of rows by consolidating data, while PARTITION BY operates only within a window function, without altering the number of output rows.
• Aggregate vs. Non-Aggregate: GROUP BY facilitates aggregate calculations for grouped data, whereas PARTITION BY does not perform any aggregate operations.
• Window Function Modification: PARTITION BY modifies the behavior of window functions by indicating how calculations should be performed within each partition.

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