window-functions

问题 I'm using a query where a part of it gets the top 3 of a certain column. It creates a distinct subquery of the column, limited by 3 number of rows, and then filters those rows to the main query to do the top 3. WITH subquery AS ( SELECT col FROM ( SELECT DISTINCT col FROM tbl ) WHERE ROWNUM <= 3 ) SELECT col FROM tbl WHERE tbl.col = subquery.col So the original table is like this: col ----- a a a b b b c d d e f f f f And the query returns the top 3 of the column (not the top 3 rows which

问题 I have a table like this ID ATTRIBUTE 1 A 1 A 1 B 1 C 2 B 2 C 2 C 3 A 3 B 3 C I'd like to select just one random attribute for each ID. The result therefore could look like this (although this is just one of many options ATTRIBUTE B C C This is my attempt on this problem SELECT "ATTRIBUTE" FROM ( SELECT "ID", "ATTRIBUTE", row_number() OVER (PARTITION BY "ID" ORDER BY random()) rownum FROM table ) shuffled WHERE rownum = 1 however, I don't know if this is a good solution, as I need to

问题 My question is triggered by the use case of calculating the differences between consecutive rows in a spark dataframe. For example, I have: >>> df.show() +-----+----------+ |index| col1| +-----+----------+ | 0.0|0.58734024| | 1.0|0.67304325| | 2.0|0.85154736| | 3.0| 0.5449719| +-----+----------+ If I choose to calculate these using "Window" functions, then I can do that like so: >>> winSpec = Window.partitionBy(df.index >= 0).orderBy(df.index.asc()) >>> import pyspark.sql.functions as f >>>

问题 This is my table: Using this query, I am getting most sold items: SELECT [Purchased Item], SUM([Overall Quantity purchased] ) FROM ReportDraft GROUP BY [Purchased Item] ORDER BY SUM([Overall Quantity purchased] ) This returns items and total quantity purchased by customer. Can I somehow create a table like ItemName | Total quantity purchased | Customer who purchased most | Customer quantity bought Pie--------|---------11------------|---------------ALEX----------|--------3------------| Thank

问题 I have a table full of prices, items, and dates. An example of this is: AA, 1/2/3024, 1.22 AA, 1/3/3024, 1.23 BB, 1/2/3024, 4.22 BB, 1/3/3024, 4.23 Within the data there are only two rows per price, and they are ordered by date. How would I condense this data set into a single product row showing the difference from the last price to the previous? [Also this applies to a ratio, so AA would produce 1.23/1.22]. The result should look like AA, todays price-yesterdays price Despite being a sum

问题 I am selecting list of periods from database. If current row is first row then the period starts with date and I can find the interval between period start like this: SELECT ... CASE WHEN row_number() OVER(ORDER BY r.created_at ASC) = 1 THEN r.created_at - r.created_at::date ELSE NULL END AS period ... FROM mytable r How can I do the same to last row? To find the time between the r.created_at of last row and midnight of its date. I am aware of first and last functions in PostgreSQL (https:/

问题 I am working on Sybase Adaptive Server Enterprise (version 12.5.0.3). Trying to use Row_number() OVER (Partition by columnname order by columnname) . When I execute the query it is throwing an exception saying that the syntax near OVER is incorrect. I have searched for proper row_number() syntax for sybase database, but there is nothing wrong in the syntax. I guess that the Sybase version that am using does not support row_number() OVER . I even tried dense_rank() OVER , but am getting the

问题 I have sql query below but i face a problem when execute it. SELECT * from (Select row_number() OVER(Order By FloorUserId) as 'row_number', FloorUserId, max(CASE WHEN AreaId='[G]' or AreaId=N'L01' THEN 'X' ELSE ' ' END) as 'L01', max(CASE WHEN AreaId='[G]' or AreaId=N'L02' THEN 'X' ELSE ' ' END) as 'L02' from floor, tbuser where FloorUserId= tbuser.userID ) as derivedTable where row_number BETWEEN 1 AND 20 But I keep getting the following error: Column 'FloorId' is invalid in the select list

问题 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? 回答1: You might want to review the documentation on window specifications (which is here). The default is "range between" which defines the range by the

问题 Comming from SQL i would expect i was able to do something like the following in dplyr, is this possible? # R tbl %>% mutate(n = dense_rank(Name, Email)) -- SQL SELECT Name, Email, DENSE_RANK() OVER (ORDER BY Name, Email) AS n FROM tbl Also is there an equivilant for PARTITION BY ? 回答1: I did struggle with this problem and here is my solution: In case you can't find any function which supports ordering by multiple variables, I suggest that you concatenate them by their priority level from