join

问题 If I have a use case where I need to join two streams or aggregate some kind of metrics from a single stream, and I use keyed streams to partition the events, how does Flink handle the operations for hot partitions where the data might not fit into memory and needs to be split across partitions? 来源： https://stackoverflow.com/questions/66273158/how-does-flink-scale-for-hot-partitions

问题 I'd like to count the number of purchases of each item while also, depending on who's viewing the content, show whether the user has purchased the content. Because the number of items and purchases could become large I'm reluctant to throw in more JOINs to accomplish this because that would seem not performant. Basically, I'd like to have a did_i_buy field somewhere in the following query without adding another JOIN . Is this possible? Let's say for user_name=tom : SELECT Items.item_id, item

问题 I apologize ahead of time because this question is in various forms many times on this site, but none of the solutions I have tried implementing seem to work properly, and I cannot find an answered question that gets me the right answer. I am working in access for a co-worker, though it will probably be in SQL in the future once he can get a server set up. I am trying to join two tables using Like, which is easy enough, except that it just is not working properly. First, an example from each

问题 In other words, for a nested/multiple JOIN SQL statement, is it safe to say that one should always use INNER JOIN first (either put it at the top line or by using parentheses to first INNER JOIN two tables) and make sure it precedes any OUTER JOIN ( LEFT , RIGHT , FULL )? My understanding is that matching columns (e.g., Primary Key column and Foreign Key column) usually don't have NULL values. And any non-matching rows including NULL from an OUTER JOIN result would be removed when being INNER

问题 In SQL, you can join two tables without a key so that all records of both tables merge with each other. If pandas.concat() or pandas.merge() or some other pandas syntax supported this, it could help me with one step of a problem I am trying to solve. I found an outer join option on the help documentation, but I could not find an exact syntax to do what I wanted (join all records without a key). To explain this a little better: import pandas as pd lunchmenupairs2 = [["pizza", "italian"],[

问题 In SQL, you can join two tables without a key so that all records of both tables merge with each other. If pandas.concat() or pandas.merge() or some other pandas syntax supported this, it could help me with one step of a problem I am trying to solve. I found an outer join option on the help documentation, but I could not find an exact syntax to do what I wanted (join all records without a key). To explain this a little better: import pandas as pd lunchmenupairs2 = [["pizza", "italian"],[

问题 I have two tables that I join on the id-column, they look like: +-------+ | users | +----+--+---+ | id | name | +----+------+ +-------+ | posts | +-------+------+---------+ | id | user_id | message | +----+---------+---------+ And now I want to select all posts and include the username, with: SELECT * FROM posts, users WHERE user_id = users.id And then I try to get the values with: ResultSet rs = // SQL if(rs.next()) { rs.getInt("posts.id"); ... } But I get SQLException when executing rs

问题 I have two tables that I join on the id-column, they look like: +-------+ | users | +----+--+---+ | id | name | +----+------+ +-------+ | posts | +-------+------+---------+ | id | user_id | message | +----+---------+---------+ And now I want to select all posts and include the username, with: SELECT * FROM posts, users WHERE user_id = users.id And then I try to get the values with: ResultSet rs = // SQL if(rs.next()) { rs.getInt("posts.id"); ... } But I get SQLException when executing rs

问题 Being rather new to LINQ, I am probably not looking for the correct search terms, that's why I am asking here. I have a data transfer object (DTO) for the current timestep and a DTO for the previous timestep. I am intending to JOIN this information into a single (nested) list and display procentual changes (for all entries of the list). The nested contains nodes of type myObject . In other words, the list consists of a couple of parent entries and (different levels of) child elements of the

问题 I have to dataset, one with some location (lat,lon), that's test, and one with the lat/lon information of all zip codes in NYC, that's test2. test <- structure(list(trip_count = 1:10, dropoff_longitude = c(-73.959862, -73.882202, -73.934113, -73.992203, -74.00563, -73.975189, -73.97448, -73.974838, -73.981377, -73.955093), dropoff_latitude = c(40.773617, 40.744175, 40.715923, 40.749203, 40.726158, 40.729824, 40.763599, 40.754135, 40.759987, 40.765224)), row.names = c(NA, -10L), class = c("tbl