This chapter covers how one creates the database structures that
will hold one's data. In a relational database, the raw data is
stored in tables, so the majority of this chapter is devoted to
explaining how tables are created and modified and what features are
available to control what data is stored in the tables.
Subsequently, we discuss how tables can be organized into
schemas, and how privileges can be assigned to tables. Finally,
we will briefly look at other features that affect the data storage,
such as views, functions, and triggers. Detailed information on
these topics is found in the PostgreSQL 7.3 Programmer's Guide.
A table in a relational database is much like a table on paper: It
consists of rows and columns. The number and order of the columns
is fixed, and each column has a name. The number of rows is
variable -- it reflects how much data is stored at a given moment.
SQL does not make any guarantees about the order of the rows in a
table. When a table is read, the rows will appear in random order,
unless sorting is explicitly requested. This is covered in Chapter 4. Furthermore, SQL does not assign unique
identifiers to rows, so it is possible to have several completely
identical rows in a table. This is a consequence of the
mathematical model that underlies SQL but is usually not desirable.
Later in this chapter we will see how to deal with this issue.
Each column has a data type. The data type constrains the set of
possible values that can be assigned to a column and assigns
semantics to the data stored in the column so that it can be used
for computations. For instance, a column declared to be of a
numerical type will not accept arbitrary text strings, and the data
stored in such a column can be used for mathematical computations.
By contrast, a column declared to be of a character string type
will accept almost any kind of data but it does not lend itself to
mathematical calculations, although other operations such as string
concatenation are available.
PostgreSQL includes a sizable set of
built-in data types that fit many applications. Users can also
define their own data types. Most built-in data types have obvious
names and semantics, so we defer a detailed explanation to Chapter 5. Some of the frequently used data types are
integer for whole numbers, numeric for
possibly fractional numbers, text for character
strings, date for dates, time for
time-of-day values, and timestamp for values
containing both date and time.
To create a table, you use the aptly named CREATE
TABLE command. In this command you specify at least a
name for the new table, the names of the columns and the data type
of each column. For example:
CREATE TABLE my_first_table (
first_column text,
second_column integer
);
This creates a table named my_first_table with
two columns. The first column is named
first_column and has a data type of
text; the second column has the name
second_column and the type integer.
The table and column names follow the identifier syntax explained
in Section 1.1.1. The type names are
usually also identifiers, but there are some exceptions. Note that the
column list is comma-separated and surrounded by parentheses.
Of course, the previous example was heavily contrived. Normally,
you would give names to your tables and columns that convey what
kind of data they store. So let's look at a more realistic
example:
CREATE TABLE products (
product_no integer,
name text,
price numeric
);
(The numeric type can store fractional components, as
would be typical of monetary amounts.)
Tip: When you create many interrelated tables it is wise to choose a
consistent naming pattern for the tables and columns. For
instance, there is a choice of using singular or plural nouns for
table names, both of which are favored by some theorist or other.
There is a limit on how many columns a table can contain.
Depending on the column types, it is between 250 and 1600.
However, defining a table with anywhere near this many columns is
highly unusual and often a questionable design.
If you don't need a table anymore, you can remove it using the
DROP TABLE command. For example:
DROP TABLE my_first_table;
DROP TABLE products;
Attempting to drop a table that does not exist is an error.
Nevertheless, it is common in SQL script files to unconditionally
try to drop each table before creating it, ignoring the error
messages.
If you need to modify a table that already exists look into Section 2.6 later in this chapter.
With the tools discussed so far you can create fully functional
tables. The remainder of this chapter is concerned with adding
features to the table definition to ensure data integrity,
security, or convenience. If you are eager to fill your tables with
data now you can skip ahead to Chapter 3 and read the
rest of this chapter later.
