At the core of most queries is an underlying table
structure. Part II discusses how we can issue the most basic of SELECT
statements to extract information from a database table.
A Database Table
Most often, we query information from a database where that
information is stored inside a table structure. Most explain a table as a
series of rows and columns. Much like a spreadsheet where the spreadsheet is
the TABLE, each line (horizontally across the page) in the spreadsheet is
considered a ROW, and then sets of lines (vertically down the page) are denoted
as a COLUMN. Each cell (the intersection of a ROW and COLUMN) is then
considered a VALUE of a COLUMN for a specific ROW. For example, look at Table
1. The table is called DOG_ORIGIN, and represents the country a particular
bread of dog originates. There is also a designator for the size of the bread.
We will, at a latter date, discuss the types of VALUEs (or data) that can be
stored in each column. For now you can see there is just TEXT data; the COLUMNS
are COUNTRY, BREED, and SIZE. A ROW is composed of an occurrence of COUNTRY,
BREED, and SIZE.
We are not going into table design concepts or modeling
here. However, please note that there are repeated VALUES in the COUNTRY and
SIZE COLUMNS. Also, note that there is no pre-defined order of the rows in the
table. This is a key concept when writing SQL and is often times misunderstood.
Just because rows of information were created in a table, in a particular order,
does not mean they will be returned in that order when extracted with a SQL
statement.
Table 1.
DOG_ORIGIN table
Country |
Breed |
Size |
Germany |
German Shepherd Dog |
Big |
Germany |
Dobermann |
Big |
Germany |
Rottweiler |
Big |
USA |
Siberian Husky |
Medium |
USA |
Alaskan Malamute |
Medium |
USA |
American Bulldog |
Big |
Switzerland |
Bernese Mountain Dog |
Big |
Switzerland |
Saint Bernard Dog |
Big |
Switzerland |
Entlebuch Cattle Dog |
Medium |
Australia |
Australian Cattle Dog |
Medium |
Australia |
Jack Russell Terrier |
Small |
Often times a TABLE is defined textually by the following
notation.
DOG_ORIGIN(COUNTRY, BREED, SIZE)
There is nothing you can do with this notation but makes it
easy to read and communicate the columns of a table.
Often times the individual COLUMNs of the TABLE are denoted
by a dot. This ‘dot’ notation containing table_name.column_name is used quite
often in SQL and you should get familiar to this representation. There is an
example later in this article.
DOG_ORIGIN.COUNTRY
DOG_ORIGIN.BREED
DOG_ORIGIN.SIZE
Writing a simple SQL Query
The SELECT statement is the basic unit for extracting information from a
database table. While there are many options within the SELECT syntax, there
are only four required parts to form a valid SQL SELECT statement. Table 2
contains the required parts of a SELECT statement. These definitions are in
their simplest form; I will expand on them later in this article.
Table 2.
Required parts for a SELECT
statement
SQL required part |
Description |
SELECT |
Key word that signifies you want to query a table. |
<select_list> |
The list of |
FROM |
Key word that |
<table_reference> |
The TABLE that the COLUMNS reside in. |
Therefore, if we wanted to list all
the COUNTRY of origin and the BREED of the dog from the DOG_ORIGIN table we
would construct a SELECT statement as follows.
SELECT country, breed FROM dog_origin;
The query could also be written in
two different forms. The first uses the TABLE name as a prefix on the COLUMNs
that are being selected. The second uses an alias for the same purpose as the
first option. Alias can be any character string. Some people use letters of the
alphabet (a,b,c,…) while others use some abbreviation of the table name. It does
not matter what you use. Just try to make it consistent throughout your code so
that you do not confuse someone. The reason for using the table name or alias
is for more advanced queries where a query might be selecting from two
different tables that have a column name that is the same. The alias specifies
to the database engine which table you would like the column to be queried
from. This will become clearer in Part III of this series.
1.
SELECT dog_origin.country, dog_origin.breed FROM dog_origin;
2.
SELECT alias.country, alias.breed FROM dog_origin alias;
In addition, this is a good place
to introduce the concept of the wildcard ‘*’ (an asterisk). The asterisk can be
used instead of listing the individual COLUMNs of the table you are selecting
from. For instance, consider the following.
SELECT * FROM dog_origin;
The database engine at this point
will expand the asterisk to mean all of the columns in the dog_origin table.
While this might be a very handy and quick way to get everything, it is a very
discouraged practice. For many reasons I will not go into, the asterisk
basically is inflexible when trying to use it within a true database
application and typically causes applications to break when the table structure
changes by adding or removing columns. So it is always a good practice to list each
and every column you really want to be used in the query.
If this all is second nature to you, GREAT! Please be patient as there are
many without this basic understanding of SQL queries and we all need to start
somewhere. If this is still confusing to you then please send me an email. SQL
is one of those lost arts. We often just throw something together without
considering the ramifications to our applications and the database engine that
must crunch through the tables to get at the information we require. Bear with
me. This series will introduce more difficult SQL as time goes on. Just read
each and every part, try the SQL and let’s become the next SQL experts.