Math in SQL is an essential skill for anyone working with databases. It allows you to manipulate data and extract insights from it. In this blog post, we will explore how to perform math in SQL using various functions and techniques.
1. Basic Arithmetic Operations
SQL supports basic arithmetic operations such as addition, subtraction, multiplication, and division. These operations can be performed on numeric data types such as INT, FLOAT, and DECIMAL.
Example:
sql
SELECT 2 + 3 AS sum;
Output:
++
 sum 
+====+
 5 
++
In the above example, we added two numbers using the `+` operator. The result is stored in a column named `sum`.
2. Exponentiation
SQL supports exponentiation using the `POWER` function. This function raises one number to the power of another.
Example:
sql
SELECT POWER(2, 3) AS result;
Output:
++
 result 
+====+
 8 
++
In the above example, we raised 2 to the power of 3 using the `POWER` function. The result is stored in a column named `result`.
3. Modulus
SQL supports modulus using the `MOD` function. This function returns the remainder when one number is divided by another.
Example:
sql
SELECT MOD(10, 3) AS result;
Output:
++
 result 
+====+
 1 
++
In the above example, we used the `MOD` function to find the remainder when 10 is divided by 3. The result is stored in a column named `result`.
4. Trigonometry
SQL supports basic trigonometric functions such as sine, cosine, and tangent. These functions can be used to calculate angles and distances in geometry problems.
Example:
sql
SELECT SIN(30) AS result;
Output:
++
 result 
+====+
 0.5 
++
In the above example, we used the `SIN` function to calculate the sine of 30 degrees. The result is stored in a column named `result`.
5. Logarithms
SQL supports logarithmic functions such as natural logarithm (ln) and base10 logarithm (log10). These functions can be used to calculate exponential growth and decay.
Example:
sql
SELECT LN(10) AS result;
Output:
++
 result 
+====+
 3.014 
++
In the above example, we used the `LN` function to calculate the natural logarithm of 10. The result is stored in a column named `result`.
6. Aggregation Functions
SQL supports various aggregation functions such as SUM, AVG, MAX, and MIN. These functions can be used to calculate summary statistics for a dataset.
Example:
sql
SELECT SUM(sales) AS total_sales
FROM sales;
Output:
++
 total_sales 
+====+
 10000 
++
In the above example, we used the `SUM` function to calculate the total sales for all records in the `sales` table. The result is stored in a column named `total_sales`.
7. Window Functions
SQL supports window functions such as ROW\_NUMBER and RANK. These functions can be used to perform calculations across a set of rows within a single query.
Example:
sql
SELECT *,
RANK() OVER (ORDER BY sales DESC) AS rank
FROM sales;
Output:
```
+++++
 id  product  price  sales  rank 
+====+========+=====+=====+=====
 1  A  10.0  5000  1 
 2  B  20.0  8000  2 
