SQL Server: Difference between PARTITION BY and GROUP BY
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 calculatingSum()
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.