Generate Series in Redshift and MySQL_MySQL
Postgres has a great function for generating a list of dates (seeUse generate_series to get continuous results), and making a list of the last 60 days withgenerate_series
is easy:
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 togenerate_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 sequentialid
column and never delete rows from it, you can just select theid
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:
Redshift:
select (getdate()::date - n)::date from numbers
MySQL:
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 nfrom users limit 60
And now creating the list of dates directly:
select (getdate()::date - row_number() over (order by true))::date as nfrom 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) nfrom users limit 60
And now creating the list of dates directly:
set @n:=date(now() + interval 1 day);select (select @n:= @n - interval 1 day) nfrom 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!
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