How to use partition by instead of group by?

Question

Hi,
I am having trouble using partition by clause in following case,
column other_number with null values contains 10 records in 'some_table'
5 records with date 11-01-2009, item_code = 1
5 records with date 10-01-2009, item_code = 2
This query returns all 10 records, (which suppose to return 2)
SELECT count (a.anumber) over (partition by TO_char(a.some_date,'MM'), a.item_code) AS i_count, a.item_code,
TO_char(a.some_date,'MM')
     FROM some_table
     WHERE to_char(a.some_date,'yyyy') = 2009
     AND a.other_number IS NULL
Works fine if I wrote like this,
SELECT count (a.anumber) AS i_count, a.item_code,
TO_char(a.some_date,'MM')
     FROM some_table
     WHERE to_char(a.some_date,'yyyy') = 2009
     AND a.other_number IS NULL
group by TO_char(a.some_date,'MM'), a.item_code
How to use partition by in this case?

Answer 1

Hi,
Almost all of the aggregate functions (the ones you use in a GROUP BY query) have analytic counterparts.
You seem to have already discovered that whatever values are returned by
an aggregate funcition using "GROUP BY x, y, z" can also be found with
an analytic function using "PARTITION BY x, y. z".
Aggregate queries collapse the result set.
The aggregate COUNT function:
SELECT    deptno
,         COUNT (*)   AS cnt
FROM       scott.emp
GROUP BY  deptno
;tells how many of the 14 employees are in each of the 3 departments.
So does the analytic COUNT function:
SELECT    deptno
,         COUNT (*) OVER (PARTITION BY deptno)   AS cnt
FROM       scott.emp
;but the first query produces 3 rows of output, the second query produces 14.
You could get 3 rows of output using the analytic function and SELECT DISTINCT , but it's inefficient.
Which should you use? Like so many other things, the answer depends on what data you have, and what results you want from that data.
If you want collapsed results (one row per group), that's a striong indication that you'll want aggregate, not analytic functions.
If you want one row of output for every row in the table, that's a strong indication that you'll want analytic functions.
If you have a particular question, ask it. Post some sample data and the results you want from that data, as Rob said.
There is another important difference between aggreate and analytic functions: analytic functions can easily be restricted to a window , or subset, of the data set. This is something like a WHERE clause, but a WHERE clause applies to the whole query: a wondowing condition applies only to an individual row.
If you need to compute a SUM of rows with an earlier order_date than this row or an average of the last 5 rows, then you proabably want to use analytic function.