SELECT ...
FROM ...
JOIN ... ON ...
WHERE ...
GROUP BY ...
HAVING ...
ORDER BY ...
LIMIT ...

SELECT col1, col2
FROM table_name
WHERE condition
ORDER BY col1 DESC, col2 ASC
LIMIT 10 OFFSET 20;

SELECT DISTINCT user_id
FROM Orders;

SELECT *
FROM Products
WHERE price BETWEEN 10 AND 100;

SELECT *
FROM Users
WHERE name LIKE 'A%';

SELECT *
FROM Users
WHERE id IN (1, 2, 3);

WHERE col IS NULL
WHERE col IS NOT NULL

SELECT IFNULL(score, 0) AS score
FROM T;

SELECT COALESCE(col1, col2, 'default') AS value
FROM T;

SELECT a.id, b.name
FROM A a
JOIN B b
  ON a.id = b.a_id;

SELECT a.id, b.name
FROM A a
LEFT JOIN B b
  ON a.id = b.a_id;

SELECT a.*
FROM A a
LEFT JOIN B b
  ON a.id = b.a_id
WHERE b.a_id IS NULL;

SELECT s.student_id, sub.subject_name
FROM Students s
CROSS JOIN Subjects sub;

SELECT department_id,
       COUNT(*) AS employee_count,
       AVG(salary) AS avg_salary,
       MAX(salary) AS max_salary,
       MIN(salary) AS min_salary,
       SUM(salary) AS total_salary
FROM Employee
GROUP BY department_id;

SELECT class
FROM Courses
GROUP BY class
HAVING COUNT(*) >= 5;

SELECT user_id,
       COUNT(DISTINCT product_id) AS product_count
FROM Orders
GROUP BY user_id;

SELECT IF(score >= 60, 'pass', 'fail') AS result
FROM Exam;

SELECT name,
       CASE
           WHEN income < 20000 THEN 'Low Salary'
           WHEN income <= 50000 THEN 'Average Salary'
           ELSE 'High Salary'
       END AS category
FROM Accounts;

SELECT
    COUNT(*) AS total_count,
    SUM(state = 'approved') AS approved_count,
    ROUND(AVG(state = 'approved'), 2) AS approved_rate,
    SUM(IF(state = 'approved', amount, 0)) AS approved_amount
FROM Transactions;

SELECT product_id
FROM Product
WHERE price > (
    SELECT AVG(price)
    FROM Product
);

SELECT customer_id
FROM Customer
WHERE product_key IN (
    SELECT product_key
    FROM Product
);

SELECT c.customer_id
FROM Customer c
WHERE EXISTS (
    SELECT 1
    FROM Orders o
    WHERE o.customer_id = c.customer_id
);

SELECT *
FROM Sales
WHERE (product_id, year) IN (
    SELECT product_id, MIN(year)
    FROM Sales
    GROUP BY product_id
);

WITH first_login AS (
    SELECT player_id, MIN(event_date) AS first_date
    FROM Activity
    GROUP BY player_id
)
SELECT *
FROM first_login;

SELECT name,
       salary,
       ROW_NUMBER() OVER (ORDER BY salary DESC) AS rn,
       RANK() OVER (ORDER BY salary DESC) AS rnk,
       DENSE_RANK() OVER (ORDER BY salary DESC) AS dense_rnk
FROM Employee;

SELECT department_id,
       name,
       salary,
       DENSE_RANK() OVER (
           PARTITION BY department_id
           ORDER BY salary DESC
       ) AS rnk
FROM Employee;

SELECT turn,
       person_name,
       SUM(weight) OVER (ORDER BY turn) AS total_weight
FROM Queue;

SELECT id,
       num,
       LAG(num, 1) OVER (ORDER BY id) AS prev_num,
       LEAD(num, 1) OVER (ORDER BY id) AS next_num
FROM Logs;

SELECT visited_on,
       SUM(amount) OVER (
           ORDER BY visited_on
           ROWS BETWEEN 6 PRECEDING AND CURRENT ROW
       ) AS seven_day_amount
FROM DailySales;

SELECT CONCAT(UPPER(LEFT(name, 1)), LOWER(SUBSTRING(name, 2))) AS fixed_name
FROM Users;

SELECT sell_date,
       GROUP_CONCAT(DISTINCT product ORDER BY product SEPARATOR ',') AS products
FROM Activities
GROUP BY sell_date;

SELECT *
FROM Users
WHERE mail REGEXP '^[A-Za-z][A-Za-z0-9_.-]*@leetcode[.]com$';

SELECT *
FROM Patients
WHERE conditions REGEXP '(^| )DIAB1';

SELECT DATE_FORMAT(trans_date, '%Y-%m') AS month
FROM Transactions;

SELECT w1.id
FROM Weather w1
JOIN Weather w2
  ON DATEDIFF(w1.recordDate, w2.recordDate) = 1
WHERE w1.temperature > w2.temperature;

SELECT ROUND(AVG(score), 2) AS avg_score
FROM Exam;

SELECT requester_id AS id
FROM RequestAccepted
UNION ALL
SELECT accepter_id AS id
FROM RequestAccepted;

SELECT 'Low Salary' AS category, COUNT(*) AS accounts_count
FROM Accounts
WHERE income < 20000
UNION ALL
SELECT 'Average Salary' AS category, COUNT(*) AS accounts_count
FROM Accounts
WHERE income BETWEEN 20000 AND 50000
UNION ALL
SELECT 'High Salary' AS category, COUNT(*) AS accounts_count
FROM Accounts
WHERE income > 50000;

DELETE p1
FROM Person p1
JOIN Person p2
  ON p1.email = p2.email
 AND p1.id > p2.id;

UPDATE Employee
SET salary = salary * 1.1
WHERE department_id = 1;

SELECT (
    SELECT DISTINCT salary
    FROM Employee
    ORDER BY salary DESC
    LIMIT 1 OFFSET 1
) AS SecondHighestSalary;

SELECT d.name AS Department,
       e.name AS Employee,
       e.salary AS Salary
FROM Employee e
JOIN Department d
  ON e.departmentId = d.id
WHERE (
    SELECT COUNT(DISTINCT e2.salary)
    FROM Employee e2
    WHERE e2.departmentId = e.departmentId
      AND e2.salary > e.salary
) < 3;

WITH ranked AS (
    SELECT d.name AS Department,
           e.name AS Employee,
           e.salary AS Salary,
           DENSE_RANK() OVER (
               PARTITION BY e.departmentId
               ORDER BY e.salary DESC
           ) AS rnk
    FROM Employee e
    JOIN Department d
      ON e.departmentId = d.id
)
SELECT Department, Employee, Salary
FROM ranked
WHERE rnk <= 3;

SELECT customer_id
FROM Customer
GROUP BY customer_id
HAVING COUNT(DISTINCT product_key) = (
    SELECT COUNT(*)
    FROM Product
);

SELECT ROUND(COUNT(a2.player_id) / COUNT(a1.player_id), 2) AS fraction
FROM (
    SELECT player_id, MIN(event_date) AS first_login
    FROM Activity
    GROUP BY player_id
) a1
LEFT JOIN Activity a2
  ON a1.player_id = a2.player_id
 AND DATEDIFF(a2.event_date, a1.first_login) = 1;

SELECT p.product_id,
       IFNULL(ROUND(SUM(u.units * p.price) / SUM(u.units), 2), 0) AS average_price
FROM Prices p
LEFT JOIN UnitsSold u
  ON p.product_id = u.product_id
 AND u.purchase_date BETWEEN p.start_date AND p.end_date
GROUP BY p.product_id;

SELECT DISTINCT l1.num AS ConsecutiveNums
FROM Logs l1
JOIN Logs l2 ON l2.id = l1.id + 1
JOIN Logs l3 ON l3.id = l1.id + 2
WHERE l1.num = l2.num
  AND l2.num = l3.num;