SQL Server: Difference between PARTITION BY and GROUP BY

I've been using GROUP BY for all types of aggregate queries over the years. Recently, I've been reverse-engineering some code that uses PARTITION BY to perform aggregations. In reading through all the documentation I can find about PARTITION BY, it sounds a lot like GROUP BY, maybe with a little extra functionality added in? Are they two versions of the same general functionality, or are they something different entirely?

They're used in different places. group by modifies the entire query, like:

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

But partition by just works on a window function, like row_number:

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

A group by normally reduces the number of rows returned by rolling them up and calculating averages or sums for each row. partition by does not affect the number of rows returned, but it changes how a window function's result is calculated.

We can take a simple example.

Consider a table named TableA with the following values:

id  firstname                   lastname                    Mark
-------------------------------------------------------------------
1   arun                        prasanth                    40
2   ann                         antony                      45
3   sruthy                      abc                         41
6   new                         abc                         47
1   arun                        prasanth                    45
1   arun                        prasanth                    49
2   ann                         antony                      49

GROUP BY

The SQL GROUP BY clause can be used in a SELECT statement to collect data across multiple records and group the results by one or more columns.

In more simple words GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns.

Syntax:

SELECT expression1, expression2, ... expression_n, 
       aggregate_function (aggregate_expression)
FROM tables
WHERE conditions
GROUP BY expression1, expression2, ... expression_n;

We can apply GROUP BY in our table:

select SUM(Mark)marksum,firstname from TableA
group by id,firstName

Results:

marksum  firstname
----------------
94      ann                      
134     arun                     
47      new                      
41      sruthy   

In our real table we have 7 rows and when we apply GROUP BY id, the server group the results based on id:

In simple words:

here GROUP BY normally reduces the number of rows returned by rolling them up and calculating Sum() for each row.

PARTITION BY

Before going to PARTITION BY, let us look at the OVER clause:

According to the MSDN definition:

OVER clause defines a window or user-specified set of rows within a query result set. A window function then computes a value for each row in the window. You can use the OVER clause with functions to compute aggregated values such as moving averages, cumulative aggregates, running totals, or a top N per group results.

PARTITION BY will not reduce the number of rows returned.

We can apply PARTITION BY in our example table:

SELECT SUM(Mark) OVER (PARTITION BY id) AS marksum, firstname FROM TableA

Result:

marksum firstname 
-------------------
134     arun                     
134     arun                     
134     arun                     
94      ann                      
94      ann                      
41      sruthy                   
47      new  

Look at the results - it will partition the rows and returns all rows, unlike GROUP BY.

partition by doesn't actually roll up the data. It allows you to reset something on a per group basis. For example, you can get an ordinal column within a group by partitioning on the grouping field and using rownum() over the rows within that group. This gives you something that behaves a bit like an identity column that resets at the beginning of each group.