![]() Very similar case on SO from just this week: It's crucial for performance that you back this up with a multicolumn index: CREATE INDEX balances_multi_idx ON balances (user_id, as_of_date DESC, balance) Generating time series between two dates in PostgreSQL.Rather use timestamp input for generate_series(): You did not define how to deal with the corner case. ![]() Users that are created already, but don't have any transactions, yet, are listed with a balance of 0. Returns your desired result - except that as_of_date is an actual date, not a timestamp like in your example. JOIN accounts a ON a.create_date <= d.as_of_date SELECT d::date AS as_of_date - cast to date right awayįROM generate_series(timestamp '', '', interval '1 day') d ![]() CROSS JOIN, LEFT JOIN LATERAL to subquery SELECT a.user_id, COALESCE(b.balance, 0) AS balance, d.as_of_date but I am struggling with LEFT JOINing that series with each set of rows grouped by user_id.ġ. To generate a series of dates in a date range, I know I can use: SELECT d.date FROM GENERATE_SERIES('', '', '1 day'::INTERVAL) d ![]() Note that rows have been added for user -01-01-03, carrying over the previous balance from and that no rows have been added for user 3, who was created on. My desired result looks like this: +-+-+-+ INSERT INTO accounts (user_id, create_date) VALUES I can reference an accounts table to get users' create_date: CREATE TABLE accounts ( If the user created their account after a given date in the range, I need to avoid creating a row for that user/date combination.If the user does not have a row for a given date in the range, I need to use their balance from the day before.I need it to contain a row for each user with their balance on each date in a given date range. It only contains balances for dates that a user has made a transaction. INSERT INTO balances (user_id, balance, as_of_date) VALUES If you want to learn more about Redshift's CROSS JOIN, you can check out the official documentation here.I have a balances table in PostgreSQL 9.3 that looks like this: CREATE TABLE balances ( Other databases, such as MySQL and PostgreSQL, have their own join operations. It's important to note that Redshift's CROSS JOIN is specific to Redshift. It allows you to quickly and easily combine data from multiple sources, making it a great tool for data analysis. Redshift's CROSS JOIN is a powerful tool for joining tables in a database. Additional info about using Redshift's CROSS JOIN The new table will have the same number of columns as the original tables, but the number of rows will be the product of the number of rows in each of the original tables. This query will join the two tables on the specified columns, creating a new table that contains all the data from the original tables. SELECT * FROM table1 CROSS JOIN table2 ON lumn1 = lumn2 AND lumn2 = lumn3 In the second example, we'll join two tables on multiple columns. This query will join the two tables on the specified column, creating a new table that contains all the data from the original tables. In the first example, we'll join two tables on a single column. To illustrate how Redshift's CROSS JOIN works, let's look at a few examples. SELECT * FROM table1 CROSS JOIN table2 ON lumn1 = lumn2 All you need to do is specify the tables you want to join and the columns you want to join them on. Using Redshift's CROSS JOIN is fairly straightforward. This creates a new table that contains all the data from the original tables. What is a CROSS JOIN?Ī CROSS JOIN is a type of join operation in which all the rows from one table are combined with all the rows from another table. This can be useful for data analysis, as it allows you to quickly and easily combine data from multiple sources. It allows you to join two or more tables together, creating a new table that contains all the data from the original tables.
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