How to use the partition instead of group by?

Hello

I'm unable to use the partition by clause in the following cases,

the column with null values other_number contains 10 records in 'une_table '.
5 records where the date 01/11/2009, item_code = 1
5 records where the date 01/10/2009, item_code = 2

This query returns all of the records of 10, (which assume back 2)
SELECT count (a.anumber) on (partition TO_char(a.some_date,'MM'), a.item_code) AS i_count, a.item_code,.
TO_char (a.some_date, 'MM')
Of une_table
WHERE to_char (a.some_date, 'yyyy') = 2009
AND a.other_number IS NULL


Works great if I wrote like this,
SELECT count (a.anumber) AS i_count, a.item_code,.
TO_char (a.some_date, 'MM')
Of une_table
WHERE to_char (a.some_date, 'yyyy') = 2009
AND a.other_number IS NULL
TO_char(a.some_date,'MM') group, a.item_code

How to use partition of in this case?

Hello

Almost all of the aggregate functions (the ones you use in a GROUP BY query) have analytical equivalents.
You seem to have already discovered that, regardless of the values returned by
a comprehensive funcition using ' GROUP BY x, y, z "can also be found
an analytical function by using "PARTITION BY x, y, z".

Aggregate queries to collapse the result set.
The COUNT aggregate function:

SELECT    deptno
,         COUNT (*)   AS cnt
FROM       scott.emp
GROUP BY  deptno
;

indicates how many 14 employees are in each of 3 departments.
The fact the analytical COUNT function:

SELECT    deptno
,         COUNT (*) OVER (PARTITION BY deptno)   AS cnt
FROM       scott.emp
;

but the first query produces 3 production lines, the second query produced 14.
You could get 3 rows of output using the analytical function and SELECT SEPARATE , but it is inefficient.

Which should you use? As with many other things, the answer depends on what data you have and what results you want from this data.
If you want has collapsed of results (one line per group), it is an indication of striong you'll want features global, not analytical.
If you want a row of output for each row in the table, it is a strong indication that you'll want to analytical functions.

If you have a specific question, ask. Post some sample data and the results desired from this data, as Rob has said.

There is another important difference between the aggreate and analytical functions: analytic functions can easily be restricted to a window , or a subset DataSet. It's something like a WHERE clause and a WHERE clause applies to the entire request: a condition of wondowing applies only to a single line.
If you need calculate a SUM of lines with a previous of this line order_date , or an average of last 5 lines, then proabably you want to use the analytical function.

Tags: Database

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