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https://github.com/Imran53/SQL-Mastery-for-Interviews

Level up your SQL skills for interviews! Explore a curated collection of SQL resources, interview questions, answers, PDFs, YouTube channels, websites, and Hackerrank solutions. Get ready to excel in SQL-related interviews with comprehensive learning materials and real-world problem-solving examples.
https://github.com/Imran53/SQL-Mastery-for-Interviews

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Level up your SQL skills for interviews! Explore a curated collection of SQL resources, interview questions, answers, PDFs, YouTube channels, websites, and Hackerrank solutions. Get ready to excel in SQL-related interviews with comprehensive learning materials and real-world problem-solving examples.

Awesome Lists containing this project

README 

        
# Important_SQL



**Revising the Select Query I**



Problem Link: https://www.hackerrank.com/challenges/revising-the-select-query/problem?isFullScreen=true

```javascript

select *

from city

where population>100000 and countrycode="USA";

```



**Revising the Select Query II**



Problem Link: https://www.hackerrank.com/challenges/revising-the-select-query-2/problem?isFullScreen=true

```

select name from city where population>120000 and countrycode="usa";

```



**Select All**



Problem Link: https://www.hackerrank.com/challenges/select-all-sql/problem?isFullScreen=true

```

select * from city;

```



**Select By ID**



Problem Link: https://www.hackerrank.com/challenges/select-by-id/problem?isFullScreen=true

```

select * from city where id=1661;

```



**Japanese Cities' Attributes**



Problem Link: https://www.hackerrank.com/challenges/japanese-cities-attributes/problem?isFullScreen=true

```

Select *

from city

where countrycode="jpn";

```



**Japanese Cities' Names**



Problem Link: https://www.hackerrank.com/challenges/japanese-cities-name/problem?isFullScreen=true

```

select name

from city

where countrycode="jpn";

```



**Weather Observation Station 1**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-1/problem?isFullScreen=true

```

select city,state from station;

```



**Weather Observation Station 3**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-3/problem?isFullScreen=true

```

select distinct city from station where id%2=0

```



**Weather Observation Station 4**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-4/problem?isFullScreen=true



```

select count(city)-count(distinct city) from station;

```



**Weather Observation Station 5**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-5/problem?isFullScreen=true

```

select city, length(city) from station order by length(city), city limit 1;

select city, length(city) from station order by length(city)desc, city limit 1;

```



**Weather Observation Station 6**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-6/problem?isFullScreen=true

```

select distinct(city) from station where

city like "a%" or

city like "e%" or

city like "i%" or

city like "o%" or

city like "u%";

```



**Weather Observation Station 7**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-7/problem?isFullScreen=true

```

select distinct(city) from station where

city like "%a" or

city like "%e" or

city like "%i" or

city like "%o" or

city like "%u";

```



**Weather Observation Station 8**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-8/problem?isFullScreen=true



```

select distinct city from station where

(city like "a%" or city like "e%" or city like "i%" or city like "o%" or city like "u%")

and

(city like "%a" or city like "%e" or city like "%i" or city like "%o" or city like "%u");

```



**Weather Observation Station 9**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-9/problem?isFullScreen=true

```

select distinct city from station where

city not like "a%" and

city not like "e%" and

city not like "i%" and

city not like "o%" and

city not like "u%";

```



**Weather Observation Station 10**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-10/problem?isFullScreen=true

```

select distinct city from station where

city not like "%a" and

city not like "%e" and

city not like "%i" and

city not like "%o" and

city not like "%u";

```



**Weather Observation Station 11**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-11/problem?isFullScreen=true

```

select distinct city from station where (city not like 'a%' and city not like 'e%' and city not like 'i%' and city not like 'o%' and city not like 'u%') or (city not like '%a' and city not like '%e' and city not like '%i' and city not like '%o' and city not like '%u');

```



**Weather Observation Station 12**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-12/problem?isFullScreen=true

```

select distinct city from station where (city not like 'a%' and city not like 'e%' and city not like 'i%' and city not like 'o%' and city not like 'u%') and (city not like '%a' and city not like '%e' and city not like '%i' and city not like '%o' and city not like '%u');

```

**Higher Than 75 Marks**



Problem Link: https://www.hackerrank.com/challenges/more-than-75-marks/problem?isFullScreen=true

```

select name from students where marks>75 order by right(name,3),id;

```



**Employee Names**



Problem Link: https://www.hackerrank.com/challenges/name-of-employees/problem?isFullScreen=true



```

select name from employee order by name;

```



**Employee Salaries**



Problem Link: https://www.hackerrank.com/challenges/salary-of-employees/problem?isFullScreen=true

```

select name from employee where salary>2000 and months<10 order by employee_id;

```



**Revising Aggregations - The Count Function**



Problem Link: https://www.hackerrank.com/challenges/revising-aggregations-the-count-function/problem?isFullScreen=true

```

select count(*) from city where population>100000;

```



**Revising Aggregations - The Sum Function**



Problem Link: https://www.hackerrank.com/challenges/revising-aggregations-sum?isFullScreen=true

```

select sum(population) from city where district="California";

```



**Revising Aggregations - Averages**



Problem Link: https://www.hackerrank.com/challenges/revising-aggregations-the-average-function?isFullScreen=true

```

select avg(population) from city where district="california";

```



**Average Population**



Problem Link: https://www.hackerrank.com/challenges/average-population?isFullScreen=true

```

select floor(avg(population)) from city;

```



**Japan Population**



Problem Link: https://www.hackerrank.com/challenges/japan-population?isFullScreen=true

```

select sum(population) from city where countrycode="jpn";

```



**Population Density Difference**



Problem Link: https://www.hackerrank.com/challenges/population-density-difference?isFullScreen=true

```

select max(population)-min(population) from city;

```



**The Blunder**



Problem Link: https://www.hackerrank.com/challenges/the-blunder?isFullScreen=true

```

select ceil(avg(salary)-avg(replace(salary,0,''))) from employees;

```



**Top Earners**



Problem Link: https://www.hackerrank.com/challenges/earnings-of-employees?isFullScreen=true

```

select salary*months as earnings, count(*)

from employee

group by earnings

order by earnings desc

limit 1;

```



**Weather Observation Station 2**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-2?isFullScreen=true

```

select round(sum(lat_n),2),round(sum(long_w),2)

from station;

```



**Weather Observation Station 13**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-13?isFullScreen=true

```

select round(sum(lat_n),4) from station

where lat_n>38.7880 and lat_n<137.2345;

```



**Weather Observation Station 14**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-14?isFullScreen=true

```

select round(max(lat_n),4)

from station

where lat_n<137.2345;

```



**Weather Observation Station 15**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-15?isFullScreen=true

```

select round(long_w,4)

from station

where lat_n=(select max(lat_n) from station where lat_n<137.2345);

```



**Weather Observation Station 16**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-16?isFullScreen=true

```

select round(min(lat_n),4) from station where lat_n>38.7780;

```



**Weather Observation Station 17**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-17?isFullScreen=true

```

select round(long_w,4) from station where lat_n= (select min(lat_n) from station where lat_n>38.7780);

```



**Weather Observation Station 18**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-18?isFullScreen=true

```

select round(abs(min(lat_n)-max(lat_n))+abs(min(long_w)-max(long_w)),4) from station;

```



**Weather Observation Station 19**



Problem Link: https://www.hackerrank.com/challenges/weather-observation-station-19?isFullScreen=true

```

select round(sqrt(power(max(lat_n)-min(lat_n),2)+power(max(long_w)-min(long_w),2)),4) from station;

```



**Population Census**



Problem Link: https://www.hackerrank.com/challenges/asian-population?isFullScreen=true

```

select sum(city.population)

from city, country

where city.countrycode = country.code and country.continent= 'asia';

```



**African Cities**



Problem Link: https://www.hackerrank.com/challenges/african-cities?isFullScreen=true

```

select city.name from city,country where city.countrycode = country.code and country.continent='Africa';

```



**Average Population of Each Continent**



Problem Link: https://www.hackerrank.com/challenges/average-population-of-each-continent?isFullScreen=true

```

SELECT Country.Continent, FLOOR(AVG(City.Population))

FROM Country, City 

WHERE Country.Code = City.CountryCode 

GROUP BY Country.Continent ;

```



**Department Highest Salary**



Problem Link: https://leetcode.com/problems/department-highest-salary/

```

select d.name as department,e.name as employee, e.salary 

from department d, employee e

where e.departmentid=d.id

and e.salary=(select max(salary) from employee e1 

             where e1.departmentid=d.id);

```



**Department Top Three Salaries**



Problem Link: https://leetcode.com/problems/department-top-three-salaries/

```

select d.name as Department, e1.name as Employee, e1.salary as Salary

    From Employee as e1  join Department as d

    on e1.departmentId = d.id

    where 3 > (Select count(distinct(e2.salary)) 

            from Employee as e2

            where e2.salary>e1.salary

            and e1.departmentId = e2.departmentId);

```



**Second Highest Salary**



Problem Link: https://leetcode.com/problems/second-highest-salary/

```

SELECT MAX(salary) as SecondHighestSalary

FROM Employee

WHERE salary < (SELECT MAX(salary) FROM Employee);

```



**Dept wise highest salary**

```

Select max(salary), deptNo 

From emp 

Group by deptNo;

```



**Salary decreasing order**

```

Select salary from emp order by salary desc;

```



**2nd highest salary**

```

Select max(Salary) from emp where salary <(select max(salary) from emp);

```



**Top 3 highest salary**

```

Select * from(select distinct salary from emp order by salary desc) where rownum<=3;

```



**3rd highest salary**



```

Select * from(select distinct salary from emp order by salary desc) where rownum<=3

Minus

Select * from(select distinct salary from emp order by salary desc) where rownum<=2;

```



**SQL Aliases**



_SQL aliases are used to give a table, or a column in a table, a temporary name._

Aliases are often used to make column names more readable.

```

Select customerName as customer, customerId as id

From customerTable;

```



**SQL FULL OUTER JOIN**



_The FULL OUTER JOIN keyword returns all matching records from both tables whether the other table matches or not. So, if there are rows in "Customers" that do not have matches in "Orders", or if there are rows in "Orders" that do not have matches in "Customers", those rows will be listed as well._

```

SELECT Customers.CustomerName, Orders.OrderID

FROM Customers

FULL OUTER JOIN Orders ON Customers.CustomerID=Orders.CustomerID

ORDER BY Customers.CustomerName;

```



link : https://www.w3schools.com/sql/sql_join_full.asp