Correlated subqueries

Data Manipulation in SQL

Mona Khalil

Data Scientist, Greenhouse Software

Correlated subquery

Uses values from the outer query to generate a result
Re-run for every row generated in the final data set
Used for advanced joining, filtering, and evaluating data

A simple example

Which match stages tend to have a higher than average number of goals scored?

SELECT 
    s.stage,
    ROUND(s.avg_goals,2) AS avg_goal,
    (SELECT AVG(home_goal + away_goal) FROM match 
     WHERE season = '2012/2013') AS overall_avg 
FROM 
    (SELECT
         stage,
         AVG(home_goal + away_goal) AS avg_goals
     FROM match
     WHERE season = '2012/2013'
     GROUP BY stage) AS s
WHERE s.avg_goals > (SELECT AVG(home_goal + away_goal) 
                     FROM match 
                     WHERE season = '2012/2013');

A simple example

Which match stages tend to have a higher than average number of goals scored?

SELECT 
    s.stage,
    ROUND(s.avg_goals,2) AS avg_goal,
    (SELECT AVG(home_goal + away_goal) 
     FROM match 
     WHERE season = '2012/2013') AS overall_avg 
FROM (SELECT
        stage,
        AVG(home_goal + away_goal) AS avg_goals
      FROM match
      WHERE season = '2012/2013'
      GROUP BY stage) AS s -- Subquery in FROM
WHERE s.avg_goals > (SELECT AVG(home_goal + away_goal) 
                     FROM match 
                     WHERE season = '2012/2013'); -- Subquery in WHERE

A correlated example

SELECT
    s.stage,
    ROUND(s.avg_goals,2) AS avg_goal,
    (SELECT AVG(home_goal + away_goal) 
     FROM match 
     WHERE season = '2012/2013') AS overall_avg 
FROM 
    (SELECT
         stage,
         AVG(home_goal + away_goal) AS avg_goals
     FROM match
     WHERE season = '2012/2013'
     GROUP BY stage) AS s
WHERE s.avg_goals > (SELECT AVG(home_goal + away_goal) 
                     FROM match AS m 
                     WHERE s.stage > m.stage);

A correlated example

| stage | avg_goals |
|-------|-----------|
| 3     | 2.83      |
| 4     | 2.8       |
| 6     | 2.78      |
| 8     | 3.09      |
| 10    | 2.96      |

Simple vs. correlated subqueries

Simple Subquery

Can be run independently from the main query
Evaluated once in the whole query

Correlated Subquery

Dependent on the main query to execute
Evaluated in loops
- Significantly slows down query runtime

Correlated subqueries

What is the average number of goals scored in each country?

SELECT
  c.name AS country,
  AVG(m.home_goal + m.away_goal) 
     AS avg_goals
FROM country AS c
LEFT JOIN match AS m
ON c.id = m.country_id
GROUP BY country;

| country     | avg_goals        |
|-------------|------------------|
| Belgium     | 2.89344262295082 |
| England     | 2.76776315789474 |
| France      | 2.51052631578947 |
| Germany     | 2.94607843137255 |
| Italy       | 2.63150867823765 |
| Netherlands | 3.14624183006536 |
| Poland      | 2.49375          |
| Portugal    | 2.63255360623782 |
| Scotland    | 2.74122807017544 |
| Spain       | 2.78223684210526 |
| Switzerland | 2.81054131054131 |

Correlated subqueries

What is the average number of goals scored in each country?

SELECT
  c.name AS country,
  (SELECT 
     AVG(home_goal + away_goal)
   FROM match AS m
   WHERE m.country_id = c.id) 
     AS avg_goals
FROM country AS c
GROUP BY country;

| country     | avg_goals        |
|-------------|------------------|
| Belgium     | 2.89344262295082 |
| England     | 2.76776315789474 |
| France      | 2.51052631578947 |
| Germany     | 2.94607843137255 |
| Italy       | 2.63150867823765 |
| Netherlands | 3.14624183006536 |
| Poland      | 2.49375          |
| Portugal    | 2.63255360623782 |
| Scotland    | 2.74122807017544 |
| Spain       | 2.78223684210526 |
| Switzerland | 2.81054131054131 |

Let's practice!

Data Manipulation in SQL