window-functions

I'm new to PostgreSQL and writing functions here is tough as nails. So I'm hoping someone can help let me know how to do what I'm trying to do. I have a table of stock prices and dates. I want to calculate the percent change from the previous day for each entry. For the earliest day of data, there won't be a previous day, so that entry can simply be Nil. Can someone look over my function and help me with a) how to reference data from the next row and b) help me clean it up? I'm aware that the WITH statement is probably not supposed to be above the IF statement. However logically, this is how I

The documentation for PostgreSQL window functions seems to imply you can use the same named window in multiple places in your query. However, I can't figure out how do I create a named window? SELECT first_value(vin) OVER( PARTITION BY vin ) AS w, first_value(make) OVER w FROM inventory.vehicles WHERE lot_Id = 9999 AND make is not null; This is a joke query I'm trying to get the syntax to take, but I'm getting error: ERROR: window "w" does not exist The answer was actually in the SELECT doc: WINDOW Clause The optional WINDOW clause has the general form WINDOW window_name AS ( window_definition

From every references that I search how to do cumulative sum / running total. they said it's better using windows function, so I did select grandtotal,sum(grandtotal)over(order by agentname) from call but I realize that the results are okay as long as the value of each rows are different. Here is the result : Is There anyway to fix this? You might want to review the documentation on window specifications (which is here ). The default is "range between" which defines the range by the values in the row. You want "rows between": select grandtotal, sum(grandtotal) over (order by agentname rows

Backstory: I have a database that has data points of drivers in trucks which also contain the. While in a truck, the driver can have a 'driverstatus'. What I'd like to do is group these statuses by driver, truck. As of now, I've tried using LAG/LEAD to help. The reason for this is so I can tell when a driverstatus change occurs, and then I can mark that row as having the last datetime of that status. That in itself is insufficient, because I need to group the statuses by their status and date. For this, I've got something such as DENSE_RANK, but I can't manage to get that right concerning the

SELECT invoice.id, COUNT(slip.id), SUM(projected_minutes) OVER (PARTITION BY task.id) AS projected_minutes FROM invoice INNER JOIN task ON task.invoice_id = invoice.id LEFT JOIN slip ON slip.task_id = task.id The query above is in postgresql, and I want to convert it to DQL, but I cant find any documentation for window functions in DQL, is this natively supported in doctrine or would i have to create a custom dql function for this? There is no support for this vendor specific function in Doctrine. Either create a custom DQL function or use Native SQL. As asked in one of the comments, I attach

I have this data table and I'm wondering if is possible create a query that get a cumulative sum by month considering all months until the current month . date_added | qty ------------------------------------ 2015-08-04 22:28:24.633784-03 | 1 2015-05-20 20:22:29.458541-03 | 1 2015-04-08 14:16:09.844229-03 | 1 2015-04-07 23:10:42.325081-03 | 1 2015-07-06 18:50:30.164932-03 | 1 2015-08-22 15:01:54.03697-03 | 1 2015-08-06 18:25:07.57763-03 | 1 2015-04-07 23:12:20.850783-03 | 1 2015-07-23 17:45:29.456034-03 | 1 2015-04-28 20:12:48.110922-03 | 1 2015-04-28 13:26:04.770365-03 | 1 2015-05-19 13:30:08

I have written this and successfully executed in Oracle COUNT (DISTINCT APEC.COURSE_CODE) OVER ( PARTITION BY s.REGISTRATION_NUMBER ,APEC.APE_ID ,COV.ACADEMIC_SESSION ) APE_COURSES_PER_ACADEMIC_YEAR I'm trying to achieve the same result in SQL Server (our source database uses Oracle but our warehouse uses SQL Server). I know the distinct isn't supported with window functions in SQL Server 2008 - can anyone suggest an alternative? Here's what I recently came across. I got it from this post . So far it works really well for me. DENSE_RANK() OVER (PARTITION BY PartitionByFields ORDER BY

The docs for Pg's Window function say : The rows considered by a window function are those of the "virtual table" produced by the query's FROM clause as filtered by its WHERE, GROUP BY, and HAVING clauses if any. For example, a row removed because it does not meet the WHERE condition is not seen by any window function. A query can contain multiple window functions that slice up the data in different ways by means of different OVER clauses, but they all act on the same collection of rows defined by this virtual table. However, I'm not seeing this. It seems to me like the Select Filter is very