window-functions

Title says it all, why can't I use a windowed function in a where clause in SQL Server? This query makes perfect sense: select id, sales_person_id, product_type, product_id, sale_amount from Sales_Log where 1 = row_number() over(partition by sales_person_id, product_type, product_id order by sale_amount desc) But it doesn't work. Is there a better way than a CTE/Subquery? EDIT For what its worth this is the query with a CTE: with Best_Sales as ( select id, sales_person_id, product_type, product_id, sale_amount, row_number() over (partition by sales_person_id, product_type, product_id order by

I want to find the cumulative or running amount of field and insert it from staging to table. My staging structure is something like this: ea_month id amount ea_year circle_id April 92570 1000 2014 1 April 92571 3000 2014 2 April 92572 2000 2014 3 March 92573 3000 2014 1 March 92574 2500 2014 2 March 92575 3750 2014 3 February 92576 2000 2014 1 February 92577 2500 2014 2 February 92578 1450 2014 3 I want my target table to look something like this: ea_month id amount ea_year circle_id cum_amt February 92576 1000 2014 1 1000 March 92573 3000 2014 1 4000 April 92570 2000 2014 1 6000 February

What's the difference between RANK() and DENSE_RANK() functions? How to find out nth salary in the following emptbl table? DEPTNO EMPNAME SAL ------------------------------ 10 rrr 10000.00 11 nnn 20000.00 11 mmm 5000.00 12 kkk 30000.00 10 fff 40000.00 10 ddd 40000.00 10 bbb 50000.00 10 ccc 50000.00 If in the table data having nulls , what will happen if I want to find out nth salary? RANK gives you the ranking within your ordered partition. Ties are assigned the same rank, with the next ranking(s) skipped. So, if you have 3 items at rank 2, the next rank listed would be ranked 5. DENSE_RANK

Using PostgreSQL 9.0. Let's say I have a table containing the fields: company , profession and year . I want to return a result which contains unique companies and professions, but aggregates (into an array is fine) years based on numeric sequence: Example Table: +-----------------------------+ | company | profession | year | +---------+------------+------+ | Google | Programmer | 2000 | | Google | Sales | 2000 | | Google | Sales | 2001 | | Google | Sales | 2002 | | Google | Sales | 2004 | | Mozilla | Sales | 2002 | +-----------------------------+ I'm interested in a query which would output

I'm trying to put together a query that will retrieve the statistics of a user (profit/loss) as a cumulative result, over a period of time. Here's the query I have so far: SELECT p.name, e.date, sum(sp.payout) OVER (ORDER BY e.date) - sum(s.buyin) OVER (ORDER BY e.date) AS "Profit/Loss" FROM result r JOIN game g ON r.game_id = g.game_id JOIN event e ON g.event_id = e.event_id JOIN structure s ON g.structure_id = s.structure_id JOIN structure_payout sp ON g.structure_id = sp.structure_id AND r.position = sp.position JOIN player p ON r.player_id = p.player_id WHERE p.player_id = 17 GROUP BY p

I am having a Spark SQL DataFrame with data and what I'm trying to get is all the rows preceding current row in a given date range. So for example I want to have all the rows from 7 days back preceding given row. I figured out I need to use a Window Function like: Window \ .partitionBy('id') \ .orderBy('start') and here comes the problem. I want to have a rangeBetween 7 days, but there is nothing in the Spark docs I could find on this. Does Spark even provide such option? For now I'm just getting all the preceding rows with: .rowsBetween(-sys.maxsize, 0) but would like to achieve something