A lot of charts and tables are time series, and the queries behind them are often easier when you can join and aggregate against a list of dates. Not having a complete list of dates causes gaps in the results, changing them in a misleading way:
select now()::date - generate_series(0, 59)
Accomplishing the same thing in Redshift and MySQL requires a little more work.
Date Series from a Numbers Table
The simplest alternative to generate_series is to create a table containing a continuous list of numbers, starting at 0, and select from that table. (If you have a table with a sequential id column and never delete rows from it, you can just select the id column from that table instead of creating a new numbers table).
select n from numbers;
Returns this list of rows: 0, 1, 2, 3…
Now that you have a numbers table, convert each number into a date:
select (getdate()::date - n)::date from numbers
select date_sub(date(now()), interval n day) from numbers
A numbers table is more convenient than a dates table since it never needs to be refreshed with new dates.
Redshift: Date Series using Window Functions
If you don’t have the option to create a numbers table, you can build one on the fly using a window function. All you need is a table that has at least as many rows as the number of dates desired. Using a window function, number the rows in any table to get a list of numbers, and then convert that to a list of dates:
select row_number() over (order by true) as n from users limit 60
And now creating the list of dates directly:
select ( getdate()::date - row_number() over (order by true) )::date as n from users limit 60
MySQL: Date Series using Variables
With variables in MySQL, we can generate a numbers table by treating a select statement as a for loop:
set @n:=-1; select (select @n:= @n+1) n from users limit 60
Now that we’ve made a list of dates, aggregating and joining data from other tables for time series charts is a breeze!