window-functions

I'm trying to correlate two types of events for users. I want to see all event "B"s along with the most recent event "A" for that user prior to the "A" event. How would one accomplish this? In particular, I'm trying to do this in Postgres. I was hoping it was possible to use a "where" clause in a window function, in which case I could essentially do a LAG() with a "where event='A'", but that doesn't seem to be possible. Any recommendations? Data example: |user |time|event| |-----|----|-----| |Alice|1 |A | |Bob |2 |A | |Alice|3 |A | |Alice|4 |B | |Bob |5 |B | |Alice|6 |B | Desired result: |user

Using the following table: A | B | C | ts --+------+------+------------------ 1 | null | null | 2016-06-15 10:00 4 | null | null | 2016-06-15 11:00 4 | 9 | null | 2016-06-15 12:00 5 | 1 | 7 | 2016-06-15 13:00 How do I select the first non-null value of each column in a running window of N rows? "First" as defined by the order of timestamps in columns ts . Querying the above table would result in: A | B | C --+---+--- 1 | 9 | 7 The window function first_value() allows for a rather short and elegant solution: SELECT first_value(a) OVER (ORDER BY a IS NULL, ts) AS a , first_value(b) OVER (ORDER

From the PySpark docs rangeBetween : rangeBetween(start, end) Defines the frame boundaries, from start (inclusive) to end (inclusive). Both start and end are relative from the current row. For example, “0” means “current row”, while “-1” means one off before the current row, and “5” means the five off after the current row. Parameters: start – boundary start, inclusive. The frame is unbounded if this is -sys.maxsize (or lower). end – boundary end, inclusive. The frame is unbounded if this is sys.maxsize (or higher). New in version 1.4. while rowsBetween rowsBetween(start, end) Defines the

What is the proper way of specifying window interval in Spark SQL, using two predefined boundaries? I am trying to sum up values from my table over a window of "between 3 hours ago and 2 hours ago". When I run this query: select *, sum(value) over ( partition by a, b order by cast(time_value as timestamp) range between interval 2 hours preceding and current row ) as sum_value from my_temp_table; That works. I get results that I expect, i.e. sums of values that fall into 2 hours rolling window. Now, what I need is to have that rolling window not being bound to the current row but to take into

I'm looking to aggregate data by the end date of a dataset with some leading period rather than the start. For example, I want to query a table and return the count of matching results 30 days PRIOR to the end date of the date shown in the results. The original table would contain ONLY the date a sale was made (timestamp). Example: sales_timestamp ------------------ 2015-08-05 12:00:00 2015-08-06 13:00:00 2015-08-25 12:31:00 2015-08-26 01:02:00 2015-08-27 02:03:00 2015-08-29 04:23:00 2015-09-01 12:00:00 2015-09-02 12:00:00 2015-09-08 00:00:00 An example of the resulting query output would be:

Is there a way to use window functions in MySQL queries dynamically within a SELECT query itself? (I know for a fact that it is possible in PostgreSQL). For example, here is the equivalent query in PostgreSQL: SELECT c_server_ip, c_client_ip, sum(a_num_bytes_sent) OVER (PARTITION BY c_server_ip) FROM network_table; However, what would be the corresponding query in MySQL? Hope this might work: select A.c_server_ip, A.c_client_ip, B.mySum from network_table A, ( select c_server_ip, sum(a_num_bytes_sent) as mySum from network_table group by c_server_ip ) as B where A.c_server_ip=B.c_server_ip;