tl;dr: I want to generate a dates table in Redshift in order to make a report easier to generate. Preferable without needing large tables already in redshift, needing to up
As a workaround, you can spin Postgres instance on your local machine, run the code there, export to CSV, then run CREATE TABLE portion only in Redshift and load data from CSV. Since this is a one-time operation it's ok to do, this is what I'm actually doing for new Redshift deployments.
In asking the question, I figured it out. Oops.
I started with a "facts" schema.
CREATE SCHEMA facts;
Run the following to start a numbers table:
create table facts.numbers
(
number int PRIMARY KEY
)
;
Use this to generate your number list. I used a million to get started
SELECT ',(' || generate_series(0,1000000,1) || ')'
;
Then copy-paste the numbers from your results in the query below, after VALUES:
INSERT INTO facts.numbers
VALUES
(0)
,(1)
,(2)
,(3)
,(4)
,(5)
,(6)
,(7)
,(8)
,(9)
-- etc
^ Make sure to remove the leading comma from the copy-pasted list of numbers
Once you have a numbers table, then you can generate a dates table (again, stealing code from elliot land http://elliot.land/post/building-a-date-dimension-table-in-redshift ) :
CREATE TABLE facts.dates (
"date_id" INTEGER NOT NULL PRIMARY KEY,
-- DATE
"full_date" DATE NOT NULL,
-- YEAR
"year_number" SMALLINT NOT NULL,
"year_week_number" SMALLINT NOT NULL,
"year_day_number" SMALLINT NOT NULL,
-- QUARTER
"qtr_number" SMALLINT NOT NULL,
-- MONTH
"month_number" SMALLINT NOT NULL,
"month_name" CHAR(9) NOT NULL,
"month_day_number" SMALLINT NOT NULL,
-- WEEK
"week_day_number" SMALLINT NOT NULL,
-- DAY
"day_name" CHAR(9) NOT NULL,
"day_is_weekday" SMALLINT NOT NULL,
"day_is_last_of_month" SMALLINT NOT NULL
) DISTSTYLE ALL SORTKEY (date_id)
;
INSERT INTO facts.dates
(
"date_id"
,"full_date"
,"year_number"
,"year_week_number"
,"year_day_number"
-- QUARTER
,"qtr_number"
-- MONTH
,"month_number"
,"month_name"
,"month_day_number"
-- WEEK
,"week_day_number"
-- DAY
,"day_name"
,"day_is_weekday"
,"day_is_last_of_month"
)
SELECT
cast(seq + 1 AS INTEGER) AS date_id,
-- DATE
datum AS full_date,
-- YEAR
cast(extract(YEAR FROM datum) AS SMALLINT) AS year_number,
cast(extract(WEEK FROM datum) AS SMALLINT) AS year_week_number,
cast(extract(DOY FROM datum) AS SMALLINT) AS year_day_number,
-- QUARTER
cast(to_char(datum, 'Q') AS SMALLINT) AS qtr_number,
-- MONTH
cast(extract(MONTH FROM datum) AS SMALLINT) AS month_number,
to_char(datum, 'Month') AS month_name,
cast(extract(DAY FROM datum) AS SMALLINT) AS month_day_number,
-- WEEK
cast(to_char(datum, 'D') AS SMALLINT) AS week_day_number,
-- DAY
to_char(datum, 'Day') AS day_name,
CASE WHEN to_char(datum, 'D') IN ('1', '7')
THEN 0
ELSE 1 END AS day_is_weekday,
CASE WHEN
extract(DAY FROM (datum + (1 - extract(DAY FROM datum)) :: INTEGER +
INTERVAL '1' MONTH) :: DATE -
INTERVAL '1' DAY) = extract(DAY FROM datum)
THEN 1
ELSE 0 END AS day_is_last_of_month
FROM
-- Generate days for 81 years starting from 2000.
(
SELECT
'2000-01-01' :: DATE + number AS datum,
number AS seq
FROM facts.numbers
WHERE number between 0 and 81 * 365 + 20
) DQ
ORDER BY 1;
^ Be sure to set the numbers at the end for the date range you need
Here is a different suggestion for building the facts.numbers that does not require manual intervention:
Cross join that table to itself enough times to get the desired number of rowsrow_number() over (order by 1) to turn those created records into an ascending set of numbersExample using the Redshift system table pg_catalog.pg_operator (which as of Oct 2020 has 659 records):
-- Prep, so that you can copy/paste the code sample
create schema if not exists facts; -- Make sure the schema exists
drop table if exists facts.numbers; -- Avoid an error if that table already exists;
create table facts.numbers -- Create the table definition
(
number int primary key
);
-- The bit you care about
insert into facts.numbers
select row_number() over (order by 1) -- return 1..n in place of the original record
from pg_catalog.pg_operator a -- 659 records
cross join pg_catalog.pg_operator b -- to get 659^2=434k records
cross join pg_catalog.pg_operator c -- to get 659^3=286M records
limit 2000000 -- to limit the result to a reasonable size
;