Understanding Tables

Tables are quite possibly the most important aspect of SQL to understand inside and out, as all of your data will reside within them. In order to be able to correctly plan and design your SQL data structures, and any programmatic routines toward accessing and applying that data, a thorough understanding of tables is an absolute pre-requisite.

A table is composed of columns and rows , and their intersections are fields . If you have ever used spreadsheet software before (such as Excel), these two terms are visually represented in the same manner, and the fields within a table are equivalent to the cells within a spreadsheet. From a general perspective, columns within a table describe the name and type of data that will be found (and can be entered) by row for that column's fields. Rows within a table represent records composed of fields that are described from left to right by their corresponding column's name and type. Each field in a row is implicitly correlated with each other field in that row. In this sense, columns can be thought of as descriptors for the discrete, sequential elements of a row, and each row can be thought of as a stored record matching that description.

Table 3-1 illustrates a simple table called books, used by our imaginary bookstore, Book Town . We will frequently refer to this table in later examples. Each of its stored records describes a book by a numeric identifier, title, author identifier, and subject identifier. These characteristics, from left to right, are described by its columns (id, title, author_id, and subject_id).

As you can see, this describes a table with four columns, in a fixed, left-to-right order, currently populated by six rows (also known as tuples, or records). It is essential to understand that in a relational database, while a table has a fixed column order, rows themselves are inherently unordered. You will see later, as the SQL's query structure is explained in Chapter 4, that there are ways within SQL to order selected rows. However, the rows in the database itself are not automatically ordered in any consistently predictable way. When order is meaningful for a SQL query, you must carefully consider and explicitly order records.

Every table must have at least one column, but tables may at times contain no rows, because each vertical column corresponds to a relatively fixed attribute of the data represented in that table (such as the title column in the previous example's books table). Without a column, a row's contents would be ambiguous; without a row, a table is merely lacking recorded data. As of PostgreSQL 7.1, there is a maximum of 1600 columns to a table, and an unlimited number of rows (i.e., you are limited only by hardware limitations, such as disk space).

In Table 3-1, the column names fairly clearly indicate the significance of each column. The decision of how to name columns is fairly arbitrary, though, and care must be taken in planning table names and conventions to avoid ambiguity.

Though it may not be immediately obvious, each of the columns of a table have an associated data type . While a column's data type helps to further describe the sort of information it contains, it constrains the kind of data that may be inserted into the column. For example, the author_id column is of type integer; this signifies that any insertion attempts not consisting of pure a integer (e.g., 110a) will fail. These types are described in more detail in the Section called Data Types ."

This section introduced the general concepts of how data is logically arranged in a relational database and within tables. The next section explains why statements are the basis for all interactions with the database.