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132 lines
4.2 KiB
SQL
132 lines
4.2 KiB
SQL
/*EXERCISE lecture 15-06-2020 */
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CREATE TABLE stadium
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(
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city varchar NOT NULL, /*To be sure we specify NOT NULL
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but is implicity implemented
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using primary key*/
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name varchar NOT NULL,
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country integer NOT NULL REFERENCES country(id) ON UPDATE CASCADE ON DELETE NO ACTION,
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/* what happen to stadium when we update the country?
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CASCADE, ON DELETE or NO ACTION
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since in this case there is not specification, we will leave NO ACTION
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*/
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address varchar,
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capacity integer DEFAULT 10000 CHECK (capacity > 10000 ),
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PRIMARY KEY(name,city,country)
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/* we need a vector since we need multiple teams in a stadium but in a RELATIONAL
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DB is incorrect. We need a table called team
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team vector(?)
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*/
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);
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-- 1)
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-- consider that a team has just one associated stadium_city
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-- modify the structure of the team table
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ALTER TABLE team ADD COLUMN stadium_name varchar;
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ALTER TABLE team ADD COLUMN stadium_city varchar;
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ALTER TABLE team ADD COLUMN stadium_country integer;
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ALTER TABLE team ADD CONSTRAINT fk_stadium FOREIGN KEY (stadium_name, stadium_city, stadium_country)
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REFERENCES stadium(name, city, country) ON UPDATE CASCADE ON DELETE NO ACTION;
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ALTER TABLE team ADD COLUMN gallery varchar;
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-- 2)
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-- Consider that a team can have more than one associated stadium
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-- We need to create a new table
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CREATE TABLE team_stadium
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(
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/*If team deleted the association with the stadium needs to be deleted*/
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team integer REFERENCES team(id) ON UPDATE CASCADE ON DELETE CASCADE,
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stadium_name varchar,
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stadium_city varchar,
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stadium_country integer,
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gallery varchar,
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FOREIGN KEY (stadium name,stadium_city, stadium_country)
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REFERENCES stadium(name, city, country) ON UPDATE CASCADE ON DELETE NO ACTION,
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PRIMARY KEY(team, stadium_name, stadium_city, stadium_country)
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);
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-- ================ QUERIES EXERCISES =================
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-- retrieve the league name and the
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-- corresponding country name for Italy and France
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-- league
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-- id
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-- country
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-- name
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/* We need to JOIN the league with country table*/
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SELECT league.name AS "league name", league.country AS "country name"
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FROM league INNER JOIN country ON country.id = league.country_id
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WHERE country.name = "Italy" OR country.name = "France"
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-- retrieve teams that have "Real" in their name
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SELECT *
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FROM team
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WHERE team_long_name ilike "%real%"
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-- ilike is insensitive (we do not know if is upper or lower case)
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-- retrieve bets where away_odds are higher than home_odds
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SELECT *
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FROM bets
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WHERE bets.away_odds > bets.home_odds
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-- retrieve the bets where the draw_odds are not provided
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SELECT *
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FROM bets
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WHERE draw_odds IS NULL
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-- IS NOT NULL if we want to check NOT NULL
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-- retrieve the total number of goals scored by Real Madrid
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-- in hoem meatches in 2010/2011
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SELECT SUM(home_team_goal)
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FROM team INNER JOIN match ON match.home_team_id = team.id
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WHERE team_long_name ilike "%real madrid%"
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AND match.season = "2010/2011"
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-- >> 61 is the result.
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-- Real Madrid gives NULL since the real name of Real Madrid CF
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-- ===== aggregate OPERATORS: SUM, MAX, MIN, AVG, COUNT
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-- ===== group by
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-- retrieve the average odds
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-- for any match of Spain Liga of 2010/2011
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SELECT match.id AS "match" AVG(home_odds) AS "home odds",
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AVG(draw_odds) AS "draw odds",
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AVG(away_odds) AS "away odds"
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FROM match
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INNER JOIN league ON match.league_id = league.id
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INNER JOIN country ON country.id = league.country_id
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INNER JOIN bet ON match.id = bet.match_id
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WHERE country.name = "Spain" AND league.name = "Liga" AND match.season = "2010/2011"
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GROUP BY match.id;
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-- retrieve the average odds
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-- for any match of Spain Liga of 2010/2011
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-- where the average home_odds are higher than 0.5
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SELECT match.id AS "match" AVG(home_odds) AS "home odds",
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AVG(draw_odds) AS "draw odds",
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AVG(away_odds) AS "away odds"
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FROM match
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INNER JOIN league ON match.league_id = league.id
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INNER JOIN country ON country.id = league.country_id
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INNER JOIN bet ON match.id = bet.match_id
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WHERE country.name = "Spain" AND league.name = "Liga"
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AND match.season = "2010/2011"
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GROUP BY match.id
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HAVING AVG(home_odds) > 0.5;
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-- WHERE filter the record of the TABLE
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-- HAVING filter record of the GROUP BY
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