Prerequisites

• Docker
• Docker Compose

Installation

docker-compose up

docker-compose exec db bash

Create the Database

psql -U postgres -c 'create database pagila;'

Import the data

psql -U postgres -d pagila -f ~/data/pagila-schema.sql

psql -U postgres -d pagila -f ~/data/pagila-data.sql

Usage

Creating Dimensions

Creating the Date Dimension

Create the Table

CREATE TABLE dimDate
(
  date_key integer NOT NULL PRIMARY KEY,
  date date NOT NULL,
  year smallint NOT NULL,
  quarter smallint NOT NULL,
  month smallint NOT NULL,
  day smallint NOT NULL,
  week smallint NOT NULL,
  is_weekend boolean
);

Insert the Data

INSERT INTO dimDate (date_key, date, year, quarter, month, day, week, is_weekend)
SELECT DISTINCT(TO_CHAR(payment_date :: DATE, 'yyyyMMDD')::integer) AS date_key,
       date(payment_date)                                           AS date,
       EXTRACT(year FROM payment_date)                              AS year,
       EXTRACT(quarter FROM payment_date)                           AS quarter,
       EXTRACT(month FROM payment_date)                             AS month,
       EXTRACT(day FROM payment_date)                               AS day,
       EXTRACT(week FROM payment_date)                              AS week,
       CASE WHEN EXTRACT(ISODOW FROM payment_date) IN (6, 7) THEN true ELSE false END AS is_weekend
FROM payment;

Creating the Customer Dimension

Create the Table

CREATE TABLE dimCustomer
(
  customer_key SERIAL PRIMARY KEY,
  customer_id  smallint NOT NULL,
  first_name   varchar(45) NOT NULL,
  last_name    varchar(45) NOT NULL,
  email        varchar(50),
  address      varchar(50) NOT NULL,
  address2     varchar(50),
  district     varchar(20) NOT NULL,
  city         varchar(50) NOT NULL,
  country      varchar(50) NOT NULL,
  postal_code  varchar(10),
  phone        varchar(20) NOT NULL,
  active       smallint NOT NULL,
  create_date  timestamp NOT NULL,
  start_date   date NOT NULL,
  end_date     date NOT NULL
);

Insert the Data

INSERT INTO dimCustomer (customer_key, customer_id, first_name, last_name, email, address, address2, district, city, country, postal_code, phone, active, create_date, start_date, end_date)
SELECT c.customer_id AS customer_key,
       c.customer_id,
       c.first_name,
       c.last_name,
       c.email,
       a.address,
       a.address2,
       a.district,
       ci.city,
       co.country,
       postal_code,
       a.phone,
       c.active,
       c.create_date,
       now()         AS start_date,
       now()         AS end_date
FROM customer c
JOIN address a  ON (c.address_id = a.address_id)
JOIN city ci    ON (a.city_id = ci.city_id)
JOIN country co ON (ci.country_id = co.country_id);

Creating the Movie Dimension

Create the Table

CREATE TABLE dimMovie
(
  movie_key          SERIAL PRIMARY KEY,
  film_id            smallint NOT NULL,
  title              varchar(255) NOT NULL,
  description        text,
  release_year       year,
  language           varchar(20) NOT NULL,
  original_language  varchar(20),
  rental_duration    smallint NOT NULL,
  length             smallint NOT NULL,
  rating             varchar(5) NOT NULL,
  special_features   varchar(60) NOT NULL
);

Insert the Data

INSERT INTO dimMovie (movie_key, film_id, title, description, release_year, language, original_language, rental_duration, length, rating, special_features)
SELECT f.film_id      AS movie_key,
       f.film_id,
       f.title,
       f.description,
       f.release_year,
       l.name         AS language,
       orig_lang.name AS original_language,
       f.rental_duration,
       f.length,
       f.rating,
       f.special_features
FROM film f
JOIN language l              ON (f.language_id=l.language_id)
LEFT JOIN language orig_lang ON (f.original_language_id = orig_lang.language_id);

Creating the Store Dimension

Create the Table

CREATE TABLE dimStore
(
  store_key           SERIAL PRIMARY KEY,
  store_id            smallint NOT NULL,
  address             varchar(50) NOT NULL,
  address2            varchar(50),
  district            varchar(20) NOT NULL,
  city                varchar(50) NOT NULL,
  country             varchar(50) NOT NULL,
  postal_code         varchar(10),
  manager_first_name  varchar(45) NOT NULL,
  manager_last_name   varchar(45) NOT NULL,
  start_date          date NOT NULL,
  end_date            date NOT NULL
);

Insert the Data

INSERT INTO dimStore (store_key, store_id, address, address2, district, city, country, postal_code, manager_first_name, manager_last_name, start_date, end_date)
SELECT s.store_id    AS store_key,
       s.store_id,
       a.address,
       a.address2,
       a.district,
       c.city,
       co.country,
       a.postal_code,
       st.first_name AS manager_first_name,
       st.last_name  AS manager_last_name,
       now()         AS start_date,
       now()         AS end_date
FROM store s
JOIN staff st   ON (s.manager_staff_id = st.staff_id)
JOIN address a  ON (s.address_id = a.address_id)
JOIN city c     ON (a.city_id = c.city_id)
JOIN country co ON (c.country_id = co.country_id)
;

Creating Facts

Sales

Create the Table

CREATE TABLE factSales
(
  sales_key        SERIAL PRIMARY KEY,
  date_key         INT NOT NULL REFERENCES dimDate(date_key),
  customer_key     INT NOT NULL REFERENCES dimCustomer(customer_key),
  movie_key        INT NOT NULL REFERENCES dimMovie(movie_key),
  store_key        INT NOT NULL REFERENCES dimStore(store_key),
  sales_amount     decimal(5,2) NOT NULL
);

Insert the data

INSERT INTO factSales (date_key, customer_key, movie_key, store_key, sales_amount)
SELECT TO_CHAR(p.payment_date :: DATE, 'yyyyMMDD')::integer AS date_key ,
       p.customer_id                                        AS customer_key,
       i.film_id                                            AS movie_key,
       i.store_id                                           AS store_key,
       p.amount                                             AS sales_amount
FROM payment p
JOIN rental r    ON ( p.rental_id = r.rental_id )
JOIN inventory i ON ( r.inventory_id = i.inventory_id );

Cube using the fact table

SELECT date_key, customer_key, movie_key, store_key,
       COUNT(*),
       SUM(sales_amount) AS sales_amount
FROM factSales
GROUP BY CUBE(date_key, customer_key, movie_key, store_key);