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This chapter is from the book

A Table: The Primary Storage for Data

The table is the primary storage object for data in a relational database. A table consists of row(s) and column(s), both of which hold the data. A table takes up physical space in a database and can be permanent or temporary.

Fields and Columns

A field, also called a column in a relational database, is part of a table that is assigned a specific data type; a field should be named to correspond with the type of data that will be entered into that column. Columns can be specified as NULL or NOT NULL, meaning that if a column is NOT NULL, something must be entered. If a column is specified as NULL, nothing has to be entered.

Every database table must consist of at least one column. Columns are those elements within a table that hold specific types of data, such as a person's name or address. For example, a valid column in a customer table may be the customer's name.

Generally, a name must be one continuous string. An object name must typically be one continuous string and can be limited to the number of characters used according to each implementation of SQL. It is typical to use underscores with names to provide separations between characters. For example, a column for the customer's name can be named CUSTOMER_NAME instead of CUSTOMERNAME.

Additionally, data can be stored as either uppercase or lowercase for character-defined fields. The case that you use for data is simply a matter of preference, which should be based on how the data will be used. In many cases, data is stored in uppercase for simplicity and consistency. However, if data is stored in different case types throughout the database (uppercase, lowercase, and mixedcase), functions can be applied to convert the data to either uppercase or lowercase if needed. These functions will be covered in Hour 11, "Restructuring the Appearance of Data."


Be sure to check your implementation for rules when naming objects and other database elements.


A row is a record of data in a database table. For example, a row of data in a customer table might consist of a particular customer's identification number, name, address, phone number, fax number, and so on. A row is comprised of fields that contain data from one record in a table. A table can contain as little as one row of data and up to as many as millions of rows of data or records.

The CREATE TABLE Statement

The CREATE TABLE statement in SQL is used to create a table. Although the very act of creating a table is quite simple, much time and effort should be put into planning table structures before the actual execution of the CREATE TABLE statement.

Some elementary questions need to be answered when creating a table:

  • What type of data will be entered into the table?

  • What will be the table's name?

  • What column(s) will compose the primary key?

  • What names shall be given to the columns (fields)?

  • What data type will be assigned to each column?

  • What will be the allocated length for each column?

  • Which columns in a table can be left blank?

After these questions are answered, the actual CREATE TABLE statement is simple.

The basic syntax to create a table is as follows:

CREATE TABLE table_name
( field1 data type [ not null ],
 field2 data type [ not null ],
 field3 data type [ not null ],
 field4 data type [ not null ],
 field5 data type [ not null ] );

A semicolon is the last character in the previous statement. Most SQL implementations have some character that terminates a statement or submits a statement to the database server. Oracle and MySQL use the semicolon. Transact-SQL uses the GO statement. This book uses the semicolon.


In this hour's examples, we use the popular data types CHAR (constant-length character), VARCHAR (variable-length character), NUMBER (numeric values, decimal and non-decimal), and DATE (date and time values).

Create a table called EMPLOYEE_TBL in the following example:


Eight different columns make up this table. Notice the use of the underscore character to break the column names up into what appears to be separate words (EMPLOYEE ID is stored as EMP_ID). This is a technique that is used to make a table or column name more readable. Each column has been assigned a specific data type and length, and by using the NULL/NOT NULL constraint, you have specified which columns require values for every row of data in the table. The EMP_PHONE is defined as NULL, meaning that NULL values are allowed in this column because there may be individuals without a telephone number. The information concerning each column is separated by a comma, with parentheses surrounding all columns (a left parenthesis before the first column and a right parenthesis following the information on the last column) .

Each record, or row of data, in this table would consist of the following:


In this table, each field is a column. The column EMP_ID could consist of one employee's identification number or many employees' identification numbers, depending on the requirements of a database query or transactions. The column is a vertical entity in a table, whereas a row of data is a horizontal entity.


NULL is a default attribute for a column; therefore, it does not have to be entered in the CREATE TABLE statement. NOT NULL must always be specified.


Some form of a STORAGE clause is available in many relational database implementations of SQL. The STORAGE clause in a CREATE TABLE statement is used for initial table sizing and is usually done at table creation. The syntax of a STORAGE clause as used in one implementation is shown in the following example:

(EMP_ID    CHAR(9)     NOT NULL,
EMP_ST     CHAR(2)     NOT NULL,
  (INITIAL   20M
   NEXT    1M );

In some implementations, there are several options available in the STORAGE clause. INITIAL allocates a set amount of space in bytes, kilobytes, and so on, for the initial amount of space to be used by a table. The NEXT part of the STORAGE identifies the amount of additional space that should be allocated to the table if it should grow beyond the space allocated for the initial allocation. You will find that there are other options available with the STORAGE clause, and remember that these options vary from implementation to implementation. If the STORAGE clause is omitted from most major implementations, there are default storage parameters invoked, which may not be the best for the application. Default storage values are set by the DBA. If default storage values are not set by the DBA, then the default storage values, which are usually very low, are set by the database itself.

Notice the neatness of the CREATE TABLE statement. This is for ease of reading and error resolution. Indentation has been used to help.


The STORAGE clause differs between relational database implementations of SQL. The previous example used Oracle's STORAGE clause, which was added to the CREATE TABLE statement. Remember that the ANSI standard for SQL is just that, a standard. The standard is not a language itself, but guidelines on how vendors should develop their SQL implementation. You also find that data types differ between implementations. Most issues concerning the actual storage and processing of data are implementation-specific.

Naming Conventions

When selecting names for objects, specifically tables and columns, the name should reflect the data that is to be stored. For example, the name for a table pertaining to employee information could be named EMPLOYEE_TBL. Names for columns should follow the same logic. When storing an employee's phone number, an obvious name for that column would be PHONE_NUMBER.


Check your particular implementation for name length limits and characters that are allowed; they could differ from implementation to implementation.


A table can be modified through the use of the ALTER TABLE command after that table's creation. You can add column(s), drop column(s), change column definitions, add and drop constraints, and, in some implementations, modify table STORAGE values. The standard syntax for the ALTER TABLE command follows:

alter table table_name [modify] [column column_name][datatype|null not null]
            [drop]  [constraint constraint_name]
            [add]  [column] column definition

Modifying Elements of a Table

The attributes of a column refer to the rules and behavior of data in a column. -You can modify the attributes of a column with the ALTER TABLE command. The word attributes here refers to the following:

  • The data type of a column

  • The length, precision, or scale of a column

  • Whether the column can contain NULL values

The following example uses the ALTER TABLE command on EMPLOYEE_TBL to modify the attributes of the column EMP_ID:


The MySQL version of the previous ALTER TABLE statement would appear as follows:

Table altered.

The column was already defined as data type VARCHAR2 (a varying-length character), but you increased the maximum length from 9 to 10.

Adding Mandatory Columns to a Table

One of the basic rules for adding columns to an existing table is that the column you are adding cannot be defined as NOT NULL if data currently exists in the table. NOT NULL means that a column must contain some value for every row of data in the table. So, if you are adding a column defined as NOT NULL, you are contradicting the NOT NULL constraint right off the bat if the preexisting rows of data in the table do not have values for the new column.

There is, however, a way to add a mandatory column to a table:

  1. Add the column and define it as NULL (the column does not have to contain a value).

  2. Insert a value into the new column for every row of data in the table.

  3. After ensuring that the column contains a value for every row of data in the table, you can alter the table to change the column's attribute to NOT NULL.

Modifying Columns

There are many things to take into consideration when modifying existing columns of a table.

Common rules for modifying columns:

  • The length of a column can be increased to the maximum length of the given data type.

  • The length of a column can be decreased only if the largest value for that column in the table is less than or equal to the new length of the column.

  • The number of digits for a number data type can always be increased.

  • The number of digits for a number data type can be decreased only if the value with the most number of digits for that column is less than or equal to the new number of digits specified for the column.

  • The number of decimal places for a number data type can either be increased or decreased.

  • The data type of a column can normally be changed.

Some implementations may actually restrict you from using certain ALTER TABLE options. For example, you may not be allowed to drop columns from a table. To do this, you would have to drop the table itself, and then rebuild the table with the desired columns. You could run into problems by dropping a column in one table that is dependent on a column in another table, or a column that is referenced by a column in another table. Be sure to refer to your specific implementation documentation.


Take heed when altering and dropping tables. If logical or typing mistakes are made when issuing these statements, important data can be lost.

Creating a Table from an Existing Table

A copy of an existing table can be created using a combination of the CREATE TABLE statement and the SELECT statement. The new table has the same column definitions. All columns or specific columns can be selected. New columns that are created via functions or a combination of columns automatically assume the size necessary to hold the data. The basic syntax for creating a table from another table is as follows:

create table new_table_name as
select [ *|column1, column2 ]
from table_name
[ where ]

Notice some new keywords in the syntax, particularly the SELECT keyword. SELECT is a database query, and is discussed in more detail later. However, it is important to know that you can create a table based on the results from a query.

First, we do a simple query to view the data in the PRODUCTS_TBL table.


You will create the tables that you see in these examples at the end of this hour in the exercise section. In Hour 5, "Manipulating Data," you will populate the tables you create in this hour with data.

select * from products_tbl;
---------- ----------------------------- ------
11235   WITCHES COSTUME        29.99
222    PLASTIC PUMPKIN 18 INCH    7.75
13     FALSE PARAFFIN TEETH      1.1
90     LIGHTED LANTERNS       14.5
15     ASSORTED COSTUMES       10
9     CANDY CORN           1.35
6     PUMPKIN CANDY         1.45
87     PLASTIC SPIDERS        1.05
119    ASSORTED MASKS         4.95


SELECT * selects data from all fields in the given table. The * represents a complete row of data, or record, in the table.

Next, create a table called PRODUCTS_TMP based on the previous query:

create table products_tmp as
select * from products_tbl;
Table created.

Now, if you run a query on the PRODUCTS_TMP table, your results appear the same as if you had selected data from the original table.

select *
from products_tmp;
---------- ----------------------------- ------
11235   WITCHES COSTUME        29.99
222    PLASTIC PUMPKIN 18 INCH    7.75
13     FALSE PARAFFIN TEETH      1.1
90     LIGHTED LANTERNS       14.5
15     ASSORTED COSTUMES       10
9     CANDY CORN           1.35
6     PUMPKIN CANDY         1.45
87     PLASTIC SPIDERS        1.05
119    ASSORTED MASKS         4.95


When creating a table from an existing table, the new table takes on the same STORAGE attributes as the original table.

Dropping Tables

Dropping a table is actually one of the easiest things to do. When the RESTRICT option is used and the table is referenced by a view or constraint, the DROP statement returns an error. When the CASCADE option is used, the drop succeeds and all referencing views and constraints are dropped. The syntax to drop a table follows:

drop table table_name [ restrict|cascade ]

In the following example, you drop the table that you just created:

drop table products.tmp;
Table dropped.


Whenever dropping a table, be sure to specify the schema name or owner of the table before submitting your command. You could drop the incorrect table. If you have access to multiple user accounts, ensure that you are connected to the database through the correct user account before dropping tables.

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