Use regular expressions in MySQL SELECT statements

A very cool and powerful capability in MySQL and other databases is the ability to incorporate regular expression syntax when selecting data. The regular expresion support in MySQL is extensive. This recipe reviews regular expression use in MySQL and lists the supported regular expression metacharacters.

The basic syntax to use regular expressions in a MySQL query is:

SELECT something FROM table WHERE column REGEXP 'regexp'

For example, to select all columns from the table events where the values in the column id end with 5587, use:

SELECT * FROM events WHERE id REGEXP '5587$'

A more elaborate example selects all columns of the table reviews where the values in the column description contain the word excellent:

SELECT * FROM reviews WHERE description REGEXP '[[:<:]]excellent[[:>:]]'

MySQL allows the following regular expression metacharacters:

. match any character ? match zero or one
* match zero or more
+ match one or more
{n} match n times
{m,n} match m through n times
{n,} match n or more times
^ beginning of line
$ end of line
[[:<:]] match beginning of words
[[:>:]] match ending of words
[:class:] match a character class
i.e., [:alpha:] for letters
[:space:] for whitespace
[:punct:] for punctuation
[:upper:] for upper case letters
[abc] match one of enclosed chars
[^xyz] match any char not enclosed
| separates alternatives

MySQL interprets a backslash (\) character as an escape character. To use a backslash in a regular expression, you must escape it with another backslash (\\).

Database Normalization - MySQL

What's Database Normalization ?

Normalization is the process where a database is designed in a way that removes redundancies, and increases the clarity in organizing data in a database.
In easy English, it means take similar stuff out of a collection of data and place them into tables. Keep doing this for each new table recursively and you'll have a Normalized database. From this resultant database you should be able to recreate the data into it's original state if there is a need to do so.
The important thing here is to know when to Normalize and when to be practical. That will come with experience. For now, read on...
Normalization of a database helps in modifying the design at later times and helps in being prepared if a change is required in the database design. Normalization raises the efficiency of the datatabase in terms of management, data storage and scalability.
Now Normalization of a Database is achieved by following a set of rules called 'forms' in creating the database.
These rules are 5 in number (with one extra one stuck in-between 3&4) and they are:

1st Normal Form or 1NF:

Each Column Type is Unique.

2nd Normal Form or 2NF:

The entity under consideration should already be in the 1NF and all attributes within the entity should depend solely on the entity's unique identifier.

3rd Normal Form or 3NF:

The entity should already be in the 2NF and no column entry should be dependent on any other entry (value) other than the key for the table.
If such an entity exists, move it outside into a new table.
Now if these 3NF are achieved, the database is considered normalized. But there are three more 'extended' NF for the elitist.
These are:

BCNF (Boyce & Codd):

The database should be in 3NF and all tables can have only one primary key.

4NF:

Tables cannot have multi-valued dependencies on a Primary Key.

5NF:

There should be no cyclic dependencies in a composite key. Trying to find website design company softnep ? Check out this page: http://www.softnep.com
Well this is a highly simplified explanation for Database Normalization. One can study this process extensively though. After working with databases for some time you'll automatically create Normalized databases. As, it's logical and practical.