The PARTITION BY clause sets the range of records that will be used for each "GROUP" within the OVER clause. In your example SQL, DEPT_COUNT will return the number of employees within that department for every employee record.
PARTITION BY gives aggregated columns with each record in the specified table. If we have 15 records in the table, the query output SQL PARTITION BY also gets 15 rows. On the other hand, GROUP BY gives one row per group in result set.
Thanks much. bhushan - we cannot use a where clause after the partition by is over.
Group By with not be always be faster than Partition by... its more important to understand the semantics of how the work. - Group BY with hashout the keys and then apply distinct on it.. so If you have nested queries or Views then its a never ending story.
The PARTITION BY
clause sets the range of records that will be used for each "GROUP" within the OVER
clause.
In your example SQL, DEPT_COUNT
will return the number of employees within that department for every employee record. (It is as if you're de-nomalising the emp
table; you still return every record in the emp
table.)
emp_no dept_no DEPT_COUNT
1 10 3
2 10 3
3 10 3 <- three because there are three "dept_no = 10" records
4 20 2
5 20 2 <- two because there are two "dept_no = 20" records
If there was another column (e.g., state
) then you could count how many departments in that State.
It is like getting the results of a GROUP BY
(SUM
, AVG
, etc.) without the aggregating the result set (i.e. removing matching records).
It is useful when you use the LAST OVER
or MIN OVER
functions to get, for example, the lowest and highest salary in the department and then use that in a calculation against this records salary without a sub select, which is much faster.
Read the linked AskTom article for further details.
The concept is very well explained by the accepted answer, but I find that the more example one sees, the better it sinks in. Here's an incremental example:
1) Boss says "get me number of items we have in stock grouped by brand"
You say: "no problem"
SELECT
BRAND
,COUNT(ITEM_ID)
FROM
ITEMS
GROUP BY
BRAND;
Result:
+--------------+---------------+
| Brand | Count |
+--------------+---------------+
| H&M | 50 |
+--------------+---------------+
| Hugo Boss | 100 |
+--------------+---------------+
| No brand | 22 |
+--------------+---------------+
2) The boss says "Now get me a list of all items, with their brand AND number of items that the respective brand has"
You may try:
SELECT
ITEM_NR
,BRAND
,COUNT(ITEM_ID)
FROM
ITEMS
GROUP BY
BRAND;
But you get:
ORA-00979: not a GROUP BY expression
This is where the OVER (PARTITION BY BRAND)
comes in:
SELECT
ITEM_NR
,BRAND
,COUNT(ITEM_ID) OVER (PARTITION BY BRAND)
FROM
ITEMS;
Whic means:
COUNT(ITEM_ID)
- get the number of itemsOVER
- Over the set of rows(PARTITION BY BRAND)
- that have the same brandAnd the result is:
+--------------+---------------+----------+
| Items | Brand | Count() |
+--------------+---------------+----------+
| Item 1 | Hugo Boss | 100 |
+--------------+---------------+----------+
| Item 2 | Hugo Boss | 100 |
+--------------+---------------+----------+
| Item 3 | No brand | 22 |
+--------------+---------------+----------+
| Item 4 | No brand | 22 |
+--------------+---------------+----------+
| Item 5 | H&M | 50 |
+--------------+---------------+----------+
etc...
It is the SQL extension called analytics. The "over" in the select statement tells oracle that the function is a analytical function, not a group by function. The advantage to using analytics is that you can collect sums, counts, and a lot more with just one pass through of the data instead of looping through the data with sub selects or worse, PL/SQL.
It does look confusing at first but this will be second nature quickly. No one explains it better then Tom Kyte. So the link above is great.
Of course, reading the documentation is a must.
EMPNO DEPTNO DEPT_COUNT
7839 10 4
5555 10 4
7934 10 4
7782 10 4 --- 4 records in table for dept 10
7902 20 4
7566 20 4
7876 20 4
7369 20 4 --- 4 records in table for dept 20
7900 30 6
7844 30 6
7654 30 6
7521 30 6
7499 30 6
7698 30 6 --- 6 records in table for dept 30
Here we are getting count for respective deptno. As for deptno 10 we have 4 records in table emp similar results for deptno 20 and 30 also.
the over partition keyword is as if we are partitioning the data by client_id creation a subset of each client id
select client_id, operation_date,
row_number() count(*) over (partition by client_id order by client_id ) as operationctrbyclient
from client_operations e
order by e.client_id;
this query will return the number of operations done by the client_id
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