This would most likely be use for filtering a search for things like a time/date span, price range, weight range …etc.

SELECT * FROM table WHERE field BETWEEN $low AND $high

or

SELECT * FROM table WHERE field >= $num1 AND field <= $num2

The codes below I found very useful.

the WHERE clause.

The WHERE clause in SQL provides conditions that must be met in order for a particular row within a table to be part of the result set. To use this clause, simply append it to the end of any applicable query as shown:

mysql> SELECT * FROM books WHERE author_id=1;

 --------- ----------- ------------------ ------------
| book_id | author_id | title            | pub_date   |
 --------- ----------- ------------------ ------------
| 1       | 1         | PHP Unleashed    | 2003-11-01 |
| 2       | 1         | PHP4 Programming | 2002-10-01 |
 --------- ----------- ------------------ ------------ 

2 rows in set (0.00 sec)

The SQL WHERE clause supports several different logical operations. Here are the most common, represented in terms of A and B:

Note: The reason for a special NULL Safe comparison operator (the <=> operator) relates to the way MySQL handles NULL values. By definition, the comparison of two NULL values is false (since NULL is an undefined value). You must use this operator when comparing two values in SQL that may be NULL.

The LIKE operator matches parts of strings. For example, to return a result set containing all of the books that have PHP in their title:

mysql> SELECT * FROM books WHERE title LIKE "%PHP%";

 --------- ----------- ------------------ ------------
| book_id | author_id | title            | pub_date   |
 --------- ----------- ------------------ ------------
| 1       | 1         | PHP Unleashed    | 2003-11-01 |
| 2       | 1         | PHP4 Programming | 2002-10-01 |
 --------- ----------- ------------------ ------------ 

2 rows in set (0.04 sec)

The syntax for the LIKE operator is LIKE <pattern> where the percent sign (%) serves as a wildcard. In the above example, the pattern %PHP% matches every row whose title column has the string PHP. This is case-insensitive.

Note: If you would like to match the literal percent character, escape it by doubling it; i.e., %%.

Although I have introduced the WHERE clause to you in terms of the SELECT statement, this technique of identifying particular rows within a table works when deleting and updating records as well. To update specific records within a table, use an UPDATE statement instead of a SELECT statement. For instance, assume I no longer live in Michigan, having moved to warmer climes. The first step in modifying the records is to identify which record in the authors table needs to change:

mysql> SELECT * FROM authors WHERE name LIKE "%Coggeshall";

 ----------- ----------------- -------
| author_id | name            | state |
 ----------- ----------------- -------
| 1         | John Coggeshall | MI    |
 ----------- ----------------- ------- 

1 row in set (0.00 sec)

As you can see, my author_id is 1. Since this number is assumed in our table to be a unique identifier (called a primary key) for my record, we can use it in conjunction with the UPDATE statement to modify my specific record in the table:

mysql> UPDATE authors SET state='FL' WHERE author_id=1;

Query OK, 1 row affected (0.05 sec)
Rows matched: 1 Changed: 1 Warnings: 0

Note: Although we technically could have used the same WHERE clause as the SELECT statement used to identify the author_id value, it is considered general bad practice to rely on such conditionals as the basis of which rows within a table are modified. For instance, what would have happened had there been two people with the last name Coggeshall? Always use a unique identifier as the conditional when performing modifications.

As you can see, the above query modifies a single row (since there is only one row with an author_id value of 1), changing the state column to FL. The general syntax of the UPDATE statement is:

UPDATE <table> SET <column>=<value>, <column>=<value>, ... WHERE <conditions>

<table> represents the table name being manipulated, and the column/value pairs represent the individual values to modify in the rows identified by the WHERE clause. Although it is rare, there are times where you would like to universally modify the value of a particular column in a table. In these cases, you may omit the WHERE clause entirely. Be very cautious, though.

If it’s possible to modify existing records within a table, obviously it must also be possible to remove certain records from tables. This operation is handled through the appropriately named DELETE statement. For instance, to remove my record from the authors table, use the following statement:

mysql> DELETE FROM authors WHERE author_id=1;

Query OK, 1 row affected (0.06 sec)

Note: To follow along with the examples later in the column, the row deleted in this example must actually exist. The above is shown only as an example.

As you can see, deleting rows from a table is a fairly straightforward process. The general syntax for the DELETE statement is as follows:

DELETE FROM <table> WHERE <conditions>

As was the case with the UPDATE statement, you can omit the WHERE clause in the DELETE statement, causing the entire contents of the table to be deleted. In SQL, there is no (reasonable) way to recover data once it has been deleted from a table, so take extreme caution to ensure that any DELETE queries will behave as expected. It’s often useful to issue a SELECT COUNT(*) query with the WHERE clause to verify that you’re affecting only the rows you want to delete.

Also note that unlike the example provided, when removing the entire contents of a table, MySQL will not report how many rows were affected. This is due to the fact that a table could potentially contain thousands of rows and to count each individual row when they all are being removed is simply inefficient.

The final two statements of the day are used to modify tables themselves within a database. The ALTER statement changes the properties of tables themselves (for instance, adding an entirely new column to the table definition). If you wanted to add a column that kept track of the ISBN for each book in the books table, you could add that column to the table in the following fashion:

mysql> ALTER TABLE books ADD isbn VARCHAR(25) AFTER pub_date;

Query OK, 4 rows affected (0.10 sec)

Records: 4 Duplicates: 0 Warnings: 0

In this case, I have added a new column named isbn of type VARCHAR as the last item in the table by placing it after the pub_date column (itself previously the last column in the books table). To visualize this, use the DESC statement:

mysql> DESC books;

 ----------- -------------- ------------------- ------ ----- --------- ----------------
| Field     | Type         | Collation         | Null | Key | Default | Extra          |
 ----------- -------------- ------------------- ------ ----- --------- ----------------
| book_id   | int(11)      | binary            | YES  | PRI | NULL    | auto_increment |
| author_id | int(11)      | binary            | YES  |     | NULL    |                |
| title     | varchar(255) | latin1_swedish_ci | YES  |     | NULL    |                |
| pub_date  | date         | latin1_swedish_ci | YES  |     | NULL    |                |
| isbn      | varchar(25)  | latin1_swedish_ci | YES  |     | NULL    |                |
 ----------- -------------- ------------------- ------ ----- --------- ---------------- 

5 rows in set (0.00 sec)

To remove this column from the table, use the ALTER statement again. However, instead of using the ADD qualifier, use DROP:

mysql> ALTER TABLE books DROP isbn;
Query OK, 4 rows affected (0.00 sec)
Records: 4 Duplicates: 0 Warnings: 0

To add a new column to a table as the first column, use the FIRST qualifier used instead of AFTER:

mysql> ALTER TABLE books ADD isbn VARCHAR(25) FIRST;
Query OK, 4 rows affected (0.00 sec)
Records: 4 Duplicates: 0 Warnings: 0

Here’s the general syntax of the ALTER statement:

ALTER TABLE <table> [ADD | DROP] <column definition> [FIRST | AFTER <column>]

Note: When altering a table that already contains data, the default value for the additional column will be used to populate those records which already exist.

The final statement I will introduce is the DROP statement. This statement can delete entire databases as well as individual tables within a database. Since the syntax for this statement is incredibly simple, I will just give you the general syntax:

DROP [TABLE | DATABASE] <table or database name>

As was the case with the DELETE statement, it is extremely important to be cautious when deleting any table or database! Although technically feasible, the process of recovering deleted data from a database can be extremely time-consuming (not to mention extremely costly).