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 upload a csv file.
long version: I am working on a report where I have to average new items created per day of the week. The date range could span months or more, so there could be, say, 5 Mondays but only 4 Sundays, which can make the math a little tricky. Also, I am not guaranteed an instance of a single item per day, especially once a user starts slicing the data. Which, this is tripping up the BI tool.
The best way to tackle this problem is most likely a dates table. However, most of the tutorials for dates tables use SQL commands that are not available or not fully supported by Redshift (I'm looking at you, generate_series).
Is there an easy way to generate a dates table in Redshift?
The code I was attempting to use: (based on this also-not-working recommendation: 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 + generate_series AS datum,
generate_series AS seq
FROM generate_series(0,81 * 365 + 20,1)
) DQ
ORDER BY 1;
Which throws this error
[Amazon](500310) Invalid operation: Specified types or functions (one per INFO message) not supported on Redshift tables.;
1 statement failed.
... because, I assume, INSERT and generate_series are not allowed in the same command in Redshift
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.
Run the following to start a numbers table:
Use this to generate your number list. I used a million to get started
Then copy-paste the numbers from your results in the query below, after VALUES:
^ 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 ) :
^ Be sure to set the numbers at the end for the date range you need