SQL Operators

SQL Operators Overview

An operator is a reserved word or a character used primarily in an SQL statement's WHERE clause to perform operation(s), such as comparisons and arithmetic operations. Operators are used to specify conditions in an SQL statement and to serve as conjunctions for multiple conditions in a statement.

• Arithmetic operators

• Comparison operators

• Logical operators

• Operators used to negate conditions

SQL Arithmetic Operators

Assume variable a holds 10 and variable b holds 20 then:

Here are simple examples showing usage of SQL Arithmetic Operators: SQL> select 10+ 20; +--------+ | 10+ 20 | +--------+ |     30     | +--------+ 1 row in set (0.00 sec) SQL> select 10 * 20; +---------+ | 10 * 20 | +---------+ |     200    | +---------+ 1 row in set (0.00 sec) SQL> select 10 / 5; +--------+ | 10 / 5   | +--------+ | 2.0000| +--------+ 1 row in set (0.03 sec) SQL> select 12 %   5; +---------+ | 12 %  5  | +---------+ |       2       | +---------+ 1 row in set (0.00 sec)

SQL Comparison Operators

Assume variable a holds 10 and variable b holds 20 then:

Consider CUSTOMERS table has following records: SQL> SELECT * FROM CUSTOMERS; +----+----------+-----+-------------- +------------+ | ID | NAME     | AGE | ADDRESS   | SALARY   | +----+----------+-----+---------------+------------+ |  1    | Ramesh |  32   | Ahmedabad |   2000.00 | |  2    | Khilan   |  25   | Delhi             |  1500.00   | |  3    | kaushik |  23   | Kota              |  2000.00   | |  4    | Chaitali |  25   | Mumbai       |  6500.00   | |  5    | Hardik   |   27  | Bhopal         |  8500.00   | |  6    | Komal    |  22   | MP                |  4500.00   | |  7    | Muffy     |  24    | Indore          | 10000.00 | +----+----------+-----+--------------+------------+ 7 rows in set (0.00 sec) Here are simple examples showing usage of SQL Comparison Operators: SQL> SELECT * FROM  CUSTOMERS   WHERE   SALARY > 5000; +----+----------+-----+---------+----------+ | ID | NAME     | AGE | ADDRESS | SALARY    | +----+----------+-----+---------+----------+ |  4 | Chaitali |  25 | Mumbai  |  6500.00 | |  5 | Hardik   |  27 | Bhopal  |  8500.00 | |  7 | Muffy    |  24 | Indore  | 10000.00 | +----+----------+-----+---------+----------+ 3 rows in set (0.00 sec) SQL>  SELECT * FROM CUSTOMERS WHERE SALARY = 2000; +----+---------+-----+-----------+---------+ | ID | NAME    | AGE | ADDRESS    | SALARY  | +----+---------+-----+-----------+---------+ |  1 | Ramesh  |  32 | Ahmedabad | 2000.00 | |  3 | kaushik |  23 | Kota      | 2000.00 | +----+---------+-----+-----------+---------+ 2 rows in set (0.00 sec) SQL>  SELECT * FROM CUSTOMERS WHERE SALARY != 2000; +----+----------+-----+---------+----------+ | ID | NAME     | AGE | ADDRESS | SALARY    | +----+----------+-----+---------+----------+ |  2 | Khilan   |  25 | Delhi   |  1500.00 | |  4 | Chaitali |  25 | Mumbai  |  6500.00 | |  5 | Hardik   |  27 | Bhopal  |  8500.00 | |  6 | Komal    |  22 | MP      |  4500.00 | |  7 | Muffy    |  24 | Indore  | 10000.00 | +----+----------+-----+---------+----------+ 5 rows in set (0.00 sec) SQL> SELECT * FROM CUSTOMERS WHERE SALARY <> 2000; +----+----------+-----+---------+----------+ | ID | NAME     | AGE | ADDRESS | SALARY    | +----+----------+-----+---------+----------+ |  2 | Khilan   |  25 | Delhi   |  1500.00 | |  4 | Chaitali |  25 | Mumbai  |  6500.00 | |  5 | Hardik   |  27 | Bhopal  |  8500.00 | |  6 | Komal    |  22 | MP      |  4500.00 | |  7 | Muffy    |  24 | Indore  | 10000.00 | +----+----------+-----+---------+----------+ 5 rows in set (0.00 sec) SQL> SELECT * FROM CUSTOMERS WHERE SALARY >= 6500; +----+----------+-----+---------+----------+ | ID | NAME     | AGE | ADDRESS | SALARY    | +----+----------+-----+---------+----------+ |  4 | Chaitali |  25 | Mumbai  |  6500.00 | |  5 | Hardik   |  27 | Bhopal  |  8500.00 | |  7 | Muffy    |  24 | Indore  | 10000.00 | +----+----------+-----+---------+----------+ 3 rows in set (0.00 sec)

SQL Logical Operators

Here is a list of all the logical operators available in SQL. Operator          Description ALL                   The ALL operator is used to compare a value to all values in another value set. AND                  The AND operator allows the existence of multiple conditions in an SQL statement's WHERE clause. ANY                   The ANY operator is used to compare a value to any applicable value in the list according to the condition. BETWEEN       The BETWEEN operator is used to search for values that are within a set of values, given the minimum value and the maximum value. EXISTS             The EXISTS operator is used to search for the presence of a row in a specified table that meets certain criteria. IN                       The IN operator is used to compare a value to a list of literal values that have been specified. LIKE                  The LIKE operator is used to compare a value to similar values using wildcard operators. NOT                  The NOT operator reverses the meaning of the logical operator with which it is used. Eg. NOT EXISTS, NOT BETWEEN, NOT IN                              etc. This is negate operator. OR                     The OR operator is used to combine multiple conditions in an SQL statement's WHERE clause. IS NULL           The NULL operator is used to compare a value with a NULL value. UNIQUE           The UNIQUE operator searches every row of a specified table for uniqueness (no duplicates). Consider CUSTOMERS table has following records: SQL> SELECT * FROM CUSTOMERS; +----+----------+-----+-----------+----------+ | ID | NAME     | AGE | ADDRESS   | SALARY   | +----+----------+-----+-----------+----------+ |  1 | Ramesh   |  32 | Ahmedabad |   2000.00 | |  2 | Khilan   |  25 | Delhi     |  1500.00 | |  3 | kaushik  |  23 | Kota      |  2000.00 | |  4 | Chaitali |  25 | Mumbai    |  6500.00 | |  5 | Hardik   |  27 | Bhopal    |  8500.00 | |  6 | Komal    |  22 | MP        |  4500.00 | |  7 | Muffy    |  24 | Indore    | 10000.00 | +----+----------+-----+-----------+----------+ 7 rows in set (0.00 sec) Here are simple examples showing usage of SQL Comparison Operators: SQL> SELECT * FROM CUSTOMERS WHERE AGE >= 25 AND SALARY >= 6500; +----+----------+-----+---------+---------+ | ID | NAME     | AGE | ADDRESS | SALARY   | +----+----------+-----+---------+---------+ |  4 | Chaitali |  25 | Mumbai  | 6500.00 | |  5 | Hardik   |  27 | Bhopal  | 8500.00 | +----+----------+-----+---------+---------+ 2 rows in set (0.00 sec) SQL> SELECT * FROM CUSTOMERS WHERE AGE >= 25 OR SALARY >= 6500; +----+----------+-----+-----------+----------+ | ID | NAME     | AGE | ADDRESS   | SALARY   | +----+----------+-----+-----------+----------+ |  1 | Ramesh   |  32 | Ahmedabad |   2000.00 | |  2 | Khilan   |  25 | Delhi     |  1500.00 | |  4 | Chaitali |  25 | Mumbai    |  6500.00 | |  5 | Hardik   |  27 | Bhopal    |  8500.00 | |  7 | Muffy    |  24 | Indore    | 10000.00 | +----+----------+-----+-----------+----------+ 5 rows in set (0.00 sec) SQL>  SELECT * FROM CUSTOMERS WHERE AGE IS NOT NULL; +----+----------+-----+-----------+----------+ | ID | NAME     | AGE | ADDRESS   | SALARY   | +----+----------+-----+-----------+----------+ |  1 | Ramesh   |  32 | Ahmedabad |   2000.00 | |  2 | Khilan   |  25 | Delhi     |  1500.00 | |  3 | kaushik  |  23 | Kota      |  2000.00 | |  4 | Chaitali |  25 | Mumbai    |  6500.00 | |  5 | Hardik   |  27 | Bhopal    |  8500.00 | |  6 | Komal    |  22 | MP        |  4500.00 | |  7 | Muffy    |  24 | Indore    | 10000.00 | +----+----------+-----+-----------+----------+ 7 rows in set (0.00 sec) SQL> SELECT * FROM CUSTOMERS WHERE NAME LIKE 'Ko%'; +----+-------+-----+---------+---------+ | ID | NAME  | AGE | ADDRESS | SALARY   | +----+-------+-----+---------+---------+ |  6 | Komal |  22 | MP      | 4500.00 | +----+-------+-----+---------+---------+ 1 row in set (0.00 sec) SQL> SELECT * FROM CUSTOMERS WHERE AGE IN ( 25, 27 ); +----+----------+-----+---------+---------+ | ID | NAME     | AGE | ADDRESS | SALARY   | +----+----------+-----+---------+---------+ |  2 | Khilan   |  25 | Delhi   | 1500.00 | |  4 | Chaitali |  25 | Mumbai  | 6500.00 | |  5 | Hardik   |  27 | Bhopal  | 8500.00 | +----+----------+-----+---------+---------+ 3 rows in set (0.00 sec) SQL> SELECT * FROM CUSTOMERS WHERE AGE BETWEEN 25 AND 27; +----+----------+-----+---------+---------+ | ID | NAME     | AGE | ADDRESS | SALARY   | +----+----------+-----+---------+---------+ |  2 | Khilan   |  25 | Delhi   | 1500.00 | |  4 | Chaitali |  25 | Mumbai  | 6500.00 | |  5 | Hardik   |  27 | Bhopal  | 8500.00 | +----+----------+-----+---------+---------+ 3 rows in set (0.00 sec) SQL> SELECT AGE FROM CUSTOMERS WHERE EXISTS (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500); +-----+ | AGE | +-----+ |  32 | |  25 | |  23 | |  25 | |  27 | |  22 | |  24 | +-----+ 7 rows in set (0.02 sec) SQL> SELECT * FROM CUSTOMERS WHERE AGE > ALL (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500); +----+--------+-----+-----------+---------+ | ID | NAME   | AGE | ADDRESS    | SALARY  | +----+--------+-----+-----------+---------+ |  1 | Ramesh |  32 | Ahmedabad | 2000.00 | +----+--------+-----+-----------+---------+ 1 row in set (0.02 sec) SQL> SELECT * FROM CUSTOMERS WHERE AGE > ANY (SELECT AGE FROM CUSTOMERS WHERE SALARY > 6500); +----+----------+-----+-----------+---------+ | ID | NAME     | AGE | ADDRESS   | SALARY  | +----+----------+-----+-----------+---------+ |  1 | Ramesh   |  32 | Ahmedabad | 2000.00 | |  2 | Khilan   |  25 | Delhi     | 1500.00 | |  4 | Chaitali |  25 | Mumbai    | 6500.00 | |  5 | Hardik   |  27 | Bhopal    | 8500.00 | +----+----------+-----+-----------+---------+ 4 rows in set (0.00 sec)