Friday, November 30, 2007

Introduction to Structured Query Language

Introduction to Structured Query Language
Version 4.15
Copyright 1996-1999, James Hoffman
jhoffman@one.net
Introduction to Structured Query Language
Version 4.15
This page is a tutorial of the Structured Query Language (also known as SQL) and is a pioneering effort on the
World Wide Web, as this is the first comprehensive SQL tutorial available on the Internet. SQL allows users to
access data in relational database management systems, such as Oracle, Sybase, Informix, Microsoft SQL Server,
Access, and others, by allowing users to describe the data the user wishes to see. SQL also allows users to define the
data in a database, and manipulate that data. This page will describe how to use SQL, and give examples. The SQL
used in this document is "ANSI", or standard SQL, and no SQL features of specific database management systems
will be discussed until the "Nonstandard SQL" section. It is recommended that you print this page, so that you can
easily refer back to previous examples.
Table of Contents
Basics of the SELECT Statement
Conditional Selection
Relational Operators
Compound Conditions
IN & BETWEEN
Using LIKE
Joins
Keys
Performing a Join
Eliminating Duplicates
Aliases & In/Subqueries
Aggregate Functions
Views
Creating New Tables
Altering Tables
Adding Data
Deleting Data
Updating Data
Indexes
GROUP BY & HAVING
More Subqueries
EXISTS & ALL
UNION & Outer Joins
Embedded SQL
Common SQL Questions
Nonstandard SQL
Syntax Summary
Important Links
Basics of the SELECT Statement
In a relational database, data is stored in tables. An example table would relate Social Security Number, Name, and
Address:
EmployeeAddressTable
SSN FirstName LastName Address City State
512687458 Joe Smith 83 First Street Howard Ohio
758420012 Mary Scott 842 Vine Ave. Losantiville Ohio
102254896 Sam Jones 33 Elm St. Paris New York
876512563 Sarah Ackerman 440 U.S. 110 Upton Michigan
Now, let's say you want to see the address of each employee. Use the SELECT statement, like so:
SELECT FirstName, LastName, Address, City, State
FROM EmployeeAddressTable;
The following is the results of your query of the database:
First Name Last Name Address City State
Joe Smith 83 First Street Howard Ohio
Mary Scott 842 Vine Ave. Losantiville Ohio
Sam Jones 33 Elm St. Paris New York
Sarah Ackerman 440 U.S. 110 Upton Michigan
To explain what you just did, you asked for the all of data in the EmployeeAddressTable, and specifically, you
asked for the columns called FirstName, LastName, Address, City, and State. Note that column names and table
names do not have spaces...they must be typed as one word; and that the statement ends with a semicolon (;). The
general form for a SELECT statement, retrieving all of the rows in the table is:
SELECT ColumnName, ColumnName, ...
FROM TableName;
To get all columns of a table without typing all column names, use:
SELECT * FROM TableName;
Each database management system (DBMS) and database software has different methods for logging in to the
database and entering SQL commands; see the local computer "guru" to help you get onto the system, so that you
can use SQL.
Conditional Selection
To further discuss the SELECT statement, let's look at a new example table (for hypothetical purposes only):
EmployeeStatisticsTable
EmployeeIDNo Salary Benefits Position
010 75000 15000 Manager
105 65000 15000 Manager
152 60000 15000 Manager
215 60000 12500 Manager
244 50000 12000 Staff
300 45000 10000 Staff
335 40000 10000 Staff
400 32000 7500 Entry-Level
441 28000 7500 Entry-Level
Relational Operators
There are six Relational Operators in SQL, and after introducing them, we'll see how they're used:
= Equal
<> or != (see
manual) Not Equal
< Less Than
> Greater Than
<= Less Than or Equal To
>= Greater Than or Equal To
The WHERE clause is used to specify that only certain rows of the table are displayed, based on the criteria
described in that WHERE clause. It is most easily understood by looking at a couple of examples.
If you wanted to see the EMPLOYEEIDNO's of those making at or over $50,000, use the following:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE SALARY >= 50000;
Notice that the >= (greater than or equal to) sign is used, as we wanted to see those who made greater than $50,000,
or equal to $50,000, listed together. This displays:
EMPLOYEEIDNO
------------
010
105
152
215
244
The WHERE description, SALARY >= 50000, is known as a condition (an operation which evaluates to True or
False). The same can be done for text columns:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE POSITION = 'Manager';
This displays the ID Numbers of all Managers. Generally, with text columns, stick to equal to or not equal to, and
make sure that any text that appears in the statement is surrounded by single quotes (').
More Complex Conditions: Compound Conditions / Logical Operators
The AND operator joins two or more conditions, and displays a row only if that row's data satisfies ALL conditions
listed (i.e. all conditions hold true). For example, to display all staff making over $40,000, use:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE SALARY > 40000 AND POSITION = 'Staff';
The OR operator joins two or more conditions, but returns a row if ANY of the conditions listed hold true. To see all
those who make less than $40,000 or have less than $10,000 in benefits, listed together, use the following query:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE SALARY < 40000 OR BENEFITS < 10000;
AND & OR can be combined, for example:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE POSITION = 'Manager' AND SALARY > 60000 OR BENEFITS > 12000;
First, SQL finds the rows where the salary is greater than $60,000 and the position column is equal to Manager, then
taking this new list of rows, SQL then sees if any of these rows satisfies the previous AND condition or the
condition that the Benefits column is greater than $12,000. Subsequently, SQL only displays this second new list of
rows, keeping in mind that anyone with Benefits over $12,000 will be included as the OR operator includes a row if
either resulting condition is True. Also note that the AND operation is done first.
To generalize this process, SQL performs the AND operation(s) to determine the rows where the AND operation(s)
hold true (remember: all of the conditions are true), then these results are used to compare with the OR conditions,
and only display those remaining rows where any of the conditions joined by the OR operator hold true (where a
condition or result from an AND is paired with another condition or AND result to use to evaluate the OR, which
evaluates to true if either value is true). Mathematically, SQL evaluates all of the conditions, then evaluates the
AND "pairs", and then evaluates the OR's (where both operators evaluate left to right).
To look at an example, for a given row for which the DBMS is evaluating the SQL statement Where clause to
determine whether to include the row in the query result (the whole Where clause evaluates to True), the DBMS has
evaluated all of the conditions, and is ready to do the logical comparisons on this result:
True AND False OR True AND True OR False AND False
First simplify the AND pairs:
False OR True OR False
Now do the OR's, left to right:
True OR False
True
The result is True, and the row passes the query conditions. Be sure to see the next section on NOT's, and the order
of logical operations. I hope that this section has helped you understand AND's or OR's, as it's a difficult subject to
explain briefly (especially when you write a version and the editor loses the changes--on multiple occasions no
less!).
To perform OR's before AND's, like if you wanted to see a list of employees making a large salary (>$50,000) or
have a large benefit package (>$10,000), and that happen to be a manager, use parentheses:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE POSITION = 'Manager' AND (SALARY > 50000 OR BENEFIT > 10000);
IN & BETWEEN
An easier method of using compound conditions uses IN or BETWEEN. For example, if you wanted to list all
managers and staff:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE POSITION IN ('Manager', 'Staff');
or to list those making greater than or equal to $30,000, but less than or equal to $50,000, use:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE SALARY BETWEEN 30000 AND 50000;
To list everyone not in this range, try:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE SALARY NOT BETWEEN 30000 AND 50000;
Similarly, NOT IN lists all rows excluded from the IN list.
Additionally, NOT's can be thrown in with AND's & OR's, except that NOT is a unary operator (evaluates one
condition, reversing its value, whereas, AND's & OR's evaluate two conditions), and that all NOT's are performed
before any AND's or OR's.
SQL Order of Logical Operations (each operates from left to right)
1. NOT
2. AND
3. OR
Using LIKE
Look at the EmployeeStatisticsTable, and say you wanted to see all people whose last names started with "L"; try:
SELECT EMPLOYEEIDNO
FROM EMPLOYEESTATISTICSTABLE
WHERE LASTNAME LIKE 'L%';
The percent sign (%) is used to represent any possible character (number, letter, or punctuation) or set of characters
that might appear after the "L". To find those people with LastName's ending in "L", use '%L', or if you wanted the
"L" in the middle of the word, try '%L%'. The '%' can be used for any characters in the same position relative to the
given characters. NOT LIKE displays rows not fitting the given description. Other possiblities of using LIKE, or any
of these discussed conditionals, are available, though it depends on what DBMS you are using; as usual, consult a
manual or your system manager or administrator for the available features on your system, or just to make sure that
what you are trying to do is available and allowed. This disclaimer holds for the features of SQL that will be
discussed below. This section is just to give you an idea of the possibilities of queries that can be written in SQL.
Joins
In this section, we will only discuss inner joins, and equijoins, as in general, they are the most useful. For more
information, try the SQL links at the bottom of the page.
Good database design suggests that each table lists data only about a single entity, and detailed information can be
obtained in a relational database, by using additional tables, and by using a join.
First, take a look at these example tables:
AntiqueOwners
OwnerID OwnerLastName OwnerFirstName
01 Jones Bill
02 Smith Bob
15 Lawson Patricia
21 Akins Jane
50 Fowler Sam
Orders
OwnerID ItemDesired
02 Table
02 Desk
21 Chair
15 Mirror
Antiques
SellerID BuyerID Item
01 50 Bed
02 15 Table
15 02 Chair
21 50 Mirror
50 01 Desk
01 21 Cabinet
02 21 Coffee Table
15 50 Chair
01 15 Jewelry Box
02 21 Pottery
21 02 Bookcase
50 01 Plant Stand
Keys
First, let's discuss the concept of keys. A primary key is a column or set of columns that uniquely identifies the rest
of the data in any given row. For example, in the AntiqueOwners table, the OwnerID column uniquely identifies that
row. This means two things: no two rows can have the same OwnerID, and, even if two owners have the same first
and last names, the OwnerID column ensures that the two owners will not be confused with each other, because the
unique OwnerID column will be used throughout the database to track the owners, rather than the names.
A foreign key is a column in a table where that column is a primary key of another table, which means that any data
in a foreign key column must have corresponding data in the other table where that column is the primary key. In
DBMS-speak, this correspondence is known as referential integrity. For example, in the Antiques table, both the
BuyerID and SellerID are foreign keys to the primary key of the AntiqueOwners table (OwnerID; for purposes of
argument, one has to be an Antique Owner before one can buy or sell any items), as, in both tables, the ID rows are
used to identify the owners or buyers and sellers, and that the OwnerID is the primary key of the AntiqueOwners
table. In other words, all of this "ID" data is used to refer to the owners, buyers, or sellers of antiques, themselves,
without having to use the actual names.
Performing a Join
The purpose of these keys is so that data can be related across tables, without having to repeat data in every table--
this is the power of relational databases. For example, you can find the names of those who bought a chair without
having to list the full name of the buyer in the Antiques table...you can get the name by relating those who bought a
chair with the names in the AntiqueOwners table through the use of the OwnerID, which relates the data in the two
tables. To find the names of those who bought a chair, use the following query:
SELECT OWNERLASTNAME, OWNERFIRSTNAME
FROM ANTIQUEOWNERS, ANTIQUES
WHERE BUYERID = OWNERID AND ITEM = 'Chair';
Note the following about this query...notice that both tables involved in the relation are listed in the FROM clause of
the statement. In the WHERE clause, first notice that the ITEM = 'Chair' part restricts the listing to those who have
bought (and in this example, thereby owns) a chair. Secondly, notice how the ID columns are related from one table
to the next by use of the BUYERID = OWNERID clause. Only where ID's match across tables and the item
purchased is a chair (because of the AND), will the names from the AntiqueOwners table be listed. Because the
joining condition used an equal sign, this join is called an equijoin. The result of this query is two names: Smith,
Bob & Fowler, Sam.
Dot notation refers to prefixing the table names to column names, to avoid ambiguity, as follows:
SELECT ANTIQUEOWNERS.OWNERLASTNAME, ANTIQUEOWNERS.OWNERFIRSTNAME
FROM ANTIQUEOWNERS, ANTIQUES
WHERE ANTIQUES.BUYERID = ANTIQUEOWNERS.OWNERID AND ANTIQUES.ITEM = 'Chair';
As the column names are different in each table, however, this wasn't necessary.
DISTINCT and Eliminating Duplicates
Let's say that you want to list the ID and names of only those people who have sold an antique. Obviously, you want
a list where each seller is only listed once--you don't want to know how many antiques a person sold, just the fact
that this person sold one (for counts, see the Aggregate Function section below). This means that you will need to
tell SQL to eliminate duplicate sales rows, and just list each person only once. To do this, use the DISTINCT
keyword.
First, we will need an equijoin to the AntiqueOwners table to get the detail data of the person's LastName and
FirstName. However, keep in mind that since the SellerID column in the Antiques table is a foreign key to the
AntiqueOwners table, a seller will only be listed if there is a row in the AntiqueOwners table listing the ID and
names. We also want to eliminate multiple occurences of the SellerID in our listing, so we use DISTINCT on the
column where the repeats may occur.
To throw in one more twist, we will also want the list alphabetized by LastName, then by FirstName (on a
LastName tie). Thus, we will use the ORDER BY clause:
SELECT DISTINCT SELLERID, OWNERLASTNAME, OWNERFIRSTNAME
FROM ANTIQUES, ANTIQUEOWNERS
WHERE SELLERID = OWNERID
ORDER BY OWNERLASTNAME, OWNERFIRSTNAME;
In this example, since everyone has sold an item, we will get a listing of all of the owners, in alphabetical order by
last name. For future reference (and in case anyone asks), this type of join is considered to be in the category of
inner joins.
Aliases & In/Subqueries
In this section, we will talk about Aliases, In and the use of subqueries, and how these can be used in a 3-table
example. First, look at this query which prints the last name of those owners who have placed an order and what the
order is, only listing those orders which can be filled (that is, there is a buyer who owns that ordered item):
SELECT OWN.OWNERLASTNAME Last Name, ORD.ITEMDESIRED Item Ordered
FROM ORDERS ORD, ANTIQUEOWNERS OWN
WHERE ORD.OWNERID = OWN.OWNERID
AND ORD.ITEMDESIRED IN
(SELECT ITEM
FROM ANTIQUES);
This gives:
Last Name Item Ordered
--------- ------------
Smith Table
Smith Desk
Akins Chair
Lawson Mirror
There are several things to note about this query:
1. First, the "Last Name" and "Item Ordered" in the Select lines gives the headers on the report.
2. The OWN & ORD are aliases; these are new names for the two tables listed in the FROM clause that are
used as prefixes for all dot notations of column names in the query (see above). This eliminates ambiguity,
especially in the equijoin WHERE clause where both tables have the column named OwnerID, and the dot
notation tells SQL that we are talking about two different OwnerID's from the two different tables.
3. Note that the Orders table is listed first in the FROM clause; this makes sure listing is done off of that table,
and the AntiqueOwners table is only used for the detail information (Last Name).
4. Most importantly, the AND in the WHERE clause forces the In Subquery to be invoked ("= ANY" or "=
SOME" are two equivalent uses of IN). What this does is, the subquery is performed, returning all of the
Items owned from the Antiques table, as there is no WHERE clause. Then, for a row from the Orders table
to be listed, the ItemDesired must be in that returned list of Items owned from the Antiques table, thus
listing an item only if the order can be filled from another owner. You can think of it this way: the subquery
returns a set of Items from which each ItemDesired in the Orders table is compared; the In condition is true
only if the ItemDesired is in that returned set from the Antiques table.
5. Also notice, that in this case, that there happened to be an antique available for each one
desired...obviously, that won't always be the case. In addition, notice that when the IN, "= ANY", or "=
SOME" is used, that these keywords refer to any possible row matches, not column matches...that is, you
cannot put multiple columns in the subquery Select clause, in an attempt to match the column in the outer
Where clause to one of multiple possible column values in the subquery; only one column can be listed in
the subquery, and the possible match comes from multiple row values in that one column, not vice-versa.
Whew! That's enough on the topic of complex SELECT queries for now. Now on to other SQL statements.
Miscellaneous SQL Statements
Aggregate Functions
I will discuss five important aggregate functions: SUM, AVG, MAX, MIN, and COUNT. They are called aggregate
functions because they summarize the results of a query, rather than listing all of the rows.
· SUM () gives the total of all the rows, satisfying any conditions, of the given column, where the given
column is numeric.
· AVG () gives the average of the given column.
· MAX () gives the largest figure in the given column.
· MIN () gives the smallest figure in the given column.
· COUNT(*) gives the number of rows satisfying the conditions.
Looking at the tables at the top of the document, let's look at three examples:
SELECT SUM(SALARY), AVG(SALARY)
FROM EMPLOYEESTATISTICSTABLE;
This query shows the total of all salaries in the table, and the average salary of all of the entries in the table.
SELECT MIN(BENEFITS)
FROM EMPLOYEESTATISTICSTABLE
WHERE POSITION = 'Manager';
This query gives the smallest figure of the Benefits column, of the employees who are Managers, which is 12500.
SELECT COUNT(*)
FROM EMPLOYEESTATISTICSTABLE
WHERE POSITION = 'Staff';
This query tells you how many employees have Staff status (3).
Views
In SQL, you might (check your DBA) have access to create views for yourself. What a view does is to allow you to
assign the results of a query to a new, personal table, that you can use in other queries, where this new table is given
the view name in your FROM clause. When you access a view, the query that is defined in your view creation
statement is performed (generally), and the results of that query look just like another table in the query that you
wrote invoking the view. For example, to create a view:
CREATE VIEW ANTVIEW AS SELECT ITEMDESIRED FROM ORDERS ;
Now, write a query using this view as a table, where the table is just a listing of all Items Desired from the Orders
table:
SELECT SELLERID
FROM ANTIQUES, ANTVIEW
WHERE ITEMDESIRED = ITEM;
This query shows all SellerID's from the Antiques table where the Item in that table happens to appear in the
Antview view, which is just all of the Items Desired in the Orders table. The listing is generated by going through
the Antique Items one-by-one until there's a match with the Antview view. Views can be used to restrict database
access, as well as, in this case, simplify a complex query.
Creating New Tables
All tables within a database must be created at some point in time...let's see how we would create the Orders table:
CREATE TABLE ORDERS
(OWNERID INTEGER NOT NULL,
ITEMDESIRED CHAR(40) NOT NULL);
This statement gives the table name and tells the DBMS about each column in the table. Please note that this
statement uses generic data types, and that the data types might be different, depending on what DBMS you are
using. As usual, check local listings. Some common generic data types are:
· Char(x) - A column of characters, where x is a number designating the maximum number of characters
allowed (maximum length) in the column.
· Integer - A column of whole numbers, positive or negative.
· Decimal(x, y) - A column of decimal numbers, where x is the maximum length in digits of the decimal
numbers in this column, and y is the maximum number of digits allowed after the decimal point. The
maximum (4,2) number would be 99.99.
· Date - A date column in a DBMS-specific format.
· Logical - A column that can hold only two values: TRUE or FALSE.
One other note, the NOT NULL means that the column must have a value in each row. If NULL was used, that
column may be left empty in a given row.
Altering Tables
Let's add a column to the Antiques table to allow the entry of the price of a given Item:
ALTER TABLE ANTIQUES ADD (PRICE DECIMAL(8,2) NULL);
The data for this new column can be updated or inserted as shown later.
Adding Data
To insert rows into a table, do the following:
INSERT INTO ANTIQUES VALUES (21, 01, 'Ottoman', 200.00);
This inserts the data into the table, as a new row, column-by-column, in the pre-defined order. Instead, let's change
the order and leave Price blank:
INSERT INTO ANTIQUES (BUYERID, SELLERID, ITEM)
VALUES (01, 21, 'Ottoman');
Deleting Data
Let's delete this new row back out of the database:
DELETE FROM ANTIQUES
WHERE ITEM = 'Ottoman';
But if there is another row that contains 'Ottoman', that row will be deleted also. Let's delete all rows (one, in this
case) that contain the specific data we added before:
DELETE FROM ANTIQUES
WHERE ITEM = 'Ottoman' AND BUYERID = 01 AND SELLERID = 21;
Updating Data
Let's update a Price into a row that doesn't have a price listed yet:
UPDATE ANTIQUES SET PRICE = 500.00 WHERE ITEM = 'Chair';
This sets all Chair's Prices to 500.00. As shown above, more WHERE conditionals, using AND, must be used to
limit the updating to more specific rows. Also, additional columns may be set by separating equal statements with
commas.
Miscellaneous Topics
Indexes
Indexes allow a DBMS to access data quicker (please note: this feature is nonstandard/not available on all systems).
The system creates this internal data structure (the index) which causes selection of rows, when the selection is
based on indexed columns, to occur faster. This index tells the DBMS where a certain row is in the table given an
indexed-column value, much like a book index tells you what page a given word appears. Let's create an index for
the OwnerID in the AntiqueOwners column:
CREATE INDEX OID_IDX ON ANTIQUEOWNERS (OWNERID);
Now on the names:
CREATE INDEX NAME_IDX ON ANTIQUEOWNERS (OWNERLASTNAME, OWNERFIRSTNAME) ;
To get rid of an index, drop it:
DROP INDEX OID_IDX;
By the way, you can also "drop" a table, as well (careful!--that means that your table is deleted). In the second
example, the index is kept on the two columns, aggregated together--strange behavior might occur in this
situation...check the manual before performing such an operation.
Some DBMS's do not enforce primary keys; in other words, the uniqueness of a column is not enforced
automatically. What that means is, if, for example, I tried to insert another row into the AntiqueOwners table with an
OwnerID of 02, some systems will allow me to do that, even though we do not, as that column is supposed to be
unique to that table (every row value is supposed to be different). One way to get around that is to create a unique
index on the column that we want to be a primary key, to force the system to enforce prohibition of duplicates:
CREATE UNIQUE INDEX OID_IDX ON ANTIQUEOWNERS (OWNERID);
GROUP BY & HAVING
One special use of GROUP BY is to associate an aggregate function (especially COUNT; counting the number of
rows in each group) with groups of rows. First, assume that the Antiques table has the Price column, and each row
has a value for that column. We want to see the price of the most expensive item bought by each owner. We have to
tell SQL to group each owner's purchases, and tell us the maximum purchase price:
SELECT BUYERID, MAX(PRICE)
FROM ANTIQUES
GROUP BY BUYERID;
Now, say we only want to see the maximum purchase price if the purchase is over $1000, so we use the HAVING
clause:
SELECT BUYERID, MAX(PRICE)
FROM ANTIQUES
GROUP BY BUYERID
HAVING PRICE > 1000;
More Subqueries
Another common usage of subqueries involves the use of operators to allow a Where condition to include the Select
output of a subquery. First, list the buyers who purchased an expensive item (the Price of the item is $100 greater
than the average price of all items purchased):
SELECT BUYERID
FROM ANTIQUES
WHERE PRICE >
(SELECT AVG(PRICE) + 100
FROM ANTIQUES);
The subquery calculates the average Price, plus $100, and using that figure, an OwnerID is printed for every item
costing over that figure. One could use DISTINCT BUYERID, to eliminate duplicates.
List the Last Names of those in the AntiqueOwners table, ONLY if they have bought an item:
SELECT OWNERLASTNAME
FROM ANTIQUEOWNERS
WHERE OWNERID IN
(SELECT DISTINCT BUYERID
FROM ANTIQUES);
The subquery returns a list of buyers, and the Last Name is printed for an Antique Owner if and only if the Owner's
ID appears in the subquery list (sometimes called a candidate list). Note: on some DBMS's, equals can be used
instead of IN, but for clarity's sake, since a set is returned from the subquery, IN is the better choice.
For an Update example, we know that the gentleman who bought the bookcase has the wrong First Name in the
database...it should be John:
UPDATE ANTIQUEOWNERS
SET OWNERFIRSTNAME = 'John'
WHERE OWNERID =
(SELECT BUYERID
FROM ANTIQUES
WHERE ITEM = 'Bookcase');
First, the subquery finds the BuyerID for the person(s) who bought the Bookcase, then the outer query updates his
First Name.
Remember this rule about subqueries: when you have a subquery as part of a WHERE condition, the Select
clause in the subquery must have columns that match in number and type to those in the Where clause of the outer
query. In other words, if you have "WHERE ColumnName = (SELECT...);", the Select must have only one
column in it, to match the ColumnName in the outer Where clause, and they must match in type (both being
integers, both being character strings, etc.).
EXISTS & ALL
EXISTS uses a subquery as a condition, where the condition is True if the subquery returns any rows, and False if
the subquery does not return any rows; this is a nonintuitive feature with few unique uses. However, if a prospective
customer wanted to see the list of Owners only if the shop dealt in Chairs, try:
SELECT OWNERFIRSTNAME, OWNERLASTNAME
FROM ANTIQUEOWNERS
WHERE EXISTS
(SELECT *
FROM ANTIQUES
WHERE ITEM = 'Chair');
If there are any Chairs in the Antiques column, the subquery would return a row or rows, making the EXISTS clause
true, causing SQL to list the Antique Owners. If there had been no Chairs, no rows would have been returned by the
outside query.
ALL is another unusual feature, as ALL queries can usually be done with different, and possibly simpler methods;
let's take a look at an example query:
SELECT BUYERID, ITEM
FROM ANTIQUES
WHERE PRICE >= ALL
(SELECT PRICE
FROM ANTIQUES);
This will return the largest priced item (or more than one item if there is a tie), and its buyer. The subquery returns a
list of all Prices in the Antiques table, and the outer query goes through each row of the Antiques table, and if its
Price is greater than or equal to every (or ALL) Prices in the list, it is listed, giving the highest priced Item. The
reason ">=" must be used is that the highest priced item will be equal to the highest price on the list, because this
Item is in the Price list.
UNION & Outer Joins (briefly explained)
There are occasions where you might want to see the results of multiple queries together, combining their output;
use UNION. To merge the output of the following two queries, displaying the ID's of all Buyers, plus all those who
have an Order placed:
SELECT BUYERID
FROM ANTIQUES
UNION
SELECT OWNERID
FROM ORDERS;
Notice that SQL requires that the Select list (of columns) must match, column-by-column, in data type. In this case
BuyerID and OwnerID are of the same data type (integer). Also notice that SQL does automatic duplicate
elimination when using UNION (as if they were two "sets"); in single queries, you have to use DISTINCT.
The outer join is used when a join query is "united" with the rows not included in the join, and are especially useful
if constant text "flags" are included. First, look at the query:
SELECT OWNERID, 'is in both Orders & Antiques'
FROM ORDERS, ANTIQUES
WHERE OWNERID = BUYERID
UNION
SELECT BUYERID, 'is in Antiques only'
FROM ANTIQUES
WHERE BUYERID NOT IN
(SELECT OWNERID
FROM ORDERS);
The first query does a join to list any owners who are in both tables, and putting a tag line after the ID repeating the
quote. The UNION merges this list with the next list. The second list is generated by first listing those ID's not in the
Orders table, thus generating a list of ID's excluded from the join query. Then, each row in the Antiques table is
scanned, and if the BuyerID is not in this exclusion list, it is listed with its quoted tag. There might be an easier way
to make this list, but it's difficult to generate the informational quoted strings of text.
This concept is useful in situations where a primary key is related to a foreign key, but the foreign key value for
some primary keys is NULL. For example, in one table, the primary key is a salesperson, and in another table is
customers, with their salesperson listed in the same row. However, if a salesperson has no customers, that person's
name won't appear in the customer table. The outer join is used if the listing of all salespersons is to be printed,
listed with their customers, whether the salesperson has a customer or not--that is, no customer is printed (a logical
NULL value) if the salesperson has no customers, but is in the salespersons table. Otherwise, the salesperson will be
listed with each customer.
Another important related point about Nulls having to do with joins: the order of tables listed in the From clause is
very important. The rule states that SQL "adds" the second table to the first; the first table listed has any rows where
there is a null on the join column displayed; if the second table has a row with a null on the join column, that row
from the table listed second does not get joined, and thus included with the first table's row data. This is another
occasion (should you wish that data included in the result) where an outer join is commonly used. The concept of
nulls is important, and it may be worth your time to investigate them further.
ENOUGH QUERIES!!! you say?...now on to something completely different...
Embedded SQL--an ugly example (do not write a program like this...for purposes
of argument ONLY)
/* -To get right to it, here is an example program that uses Embedded
SQL. Embedded SQL allows programmers to connect to a database and
include SQL code right in the program, so that their programs can
use, manipulate, and process data from a database.
-This example C Program (using Embedded SQL) will print a report.
-This program will have to be precompiled for the SQL statements,
before regular compilation.
-The EXEC SQL parts are the same (standard), but the surrounding C
code will need to be changed, including the host variable
declarations, if you are using a different language.
-Embedded SQL changes from system to system, so, once again, check
local documentation, especially variable declarations and logging
in procedures, in which network, DBMS, and operating system
considerations are crucial. */
/************************************************/
/* THIS PROGRAM IS NOT COMPILABLE OR EXECUTABLE */
/* IT IS FOR EXAMPLE PURPOSES ONLY */
/************************************************/
#include
/* This section declares the host variables; these will be the
variables your program uses, but also the variable SQL will put
values in or take values out. */
EXEC SQL BEGIN DECLARE SECTION;
int BuyerID;
char FirstName[100], LastName[100], Item[100];
EXEC SQL END DECLARE SECTION;
/* This includes the SQLCA variable, so that some error checking can be done.
*/
EXEC SQL INCLUDE SQLCA;
main() {
/* This is a possible way to log into the database */
EXEC SQL CONNECT UserID/Password;
/* This code either says that you are connected or checks if an error
code was generated, meaning log in was incorrect or not possible. */
if(sqlca.sqlcode) {
printf(Printer, "Error connecting to database server.\n");
exit();
}
printf("Connected to database server.\n");
/* This declares a "Cursor". This is used when a query returns more
than one row, and an operation is to be performed on each row
resulting from the query. With each row established by this query,
I'm going to use it in the report. Later, "Fetch" will be used to
pick off each row, one at a time, but for the query to actually
be executed, the "Open" statement is used. The "Declare" just
establishes the query. */
EXEC SQL DECLARE ItemCursor CURSOR FOR
SELECT ITEM, BUYERID
FROM ANTIQUES
ORDER BY ITEM;
EXEC SQL OPEN ItemCursor;
/* +-- You may wish to put a similar error checking block here --+ */
/* Fetch puts the values of the "next" row of the query in the host
variables, respectively. However, a "priming fetch" (programming
technique) must first be done. When the cursor is out of data, a
sqlcode will be generated allowing us to leave the loop. Notice
that, for simplicity's sake, the loop will leave on any sqlcode,
even if it is an error code. Otherwise, specific code checking must
be performed. */
EXEC SQL FETCH ItemCursor INTO :Item, :BuyerID;
while(!sqlca.sqlcode) {
/* With each row, we will also do a couple of things. First, bump the
price up by $5 (dealer's fee) and get the buyer's name to put in
the report. To do this, I'll use an Update and a Select, before
printing the line on the screen. The update assumes however, that
a given buyer has only bought one of any given item, or else the
price will be increased too many times. Otherwise, a " RowID" logic
would have to be used (see documentation). Also notice the colon before host
variable names when used inside of SQL statements. */
EXEC SQL UPDATE ANTIQUES
SET PRICE = PRICE + 5
WHERE ITEM = :Item AND BUYERID = :BuyerID;
EXEC SQL SELECT OWNERFIRSTNAME, OWNERLASTNAME
INTO :FirstName, :LastName
FROM ANTIQUEOWNERS
WHERE BUYERID = :BuyerID;
printf("%25s %25s %25s", FirstName, LastName, Item);
/* Ugly report--for example purposes only! Get the next row. */
EXEC SQL FETCH ItemCursor INTO :Item, :BuyerID;
}
/* Close the cursor, commit the changes (see below), and exit the
program. */
EXEC SQL CLOSE ItemCursor;
EXEC SQL COMMIT RELEASE;
exit();
}
Common SQL Questions--Advanced Topics (see FAQ link for several more)
1. Why can't I just ask for the first three rows in a table? --Because in relational databases, rows are inserted in
no particular order, that is, the system inserts them in an arbitrary order; so, you can only request rows
using valid SQL features, like ORDER BY, etc.
2. What is this DDL and DML I hear about? --DDL (Data Definition Language) refers to (in SQL) the Create
Table statement...DML (Data Manipulation Language) refers to the Select, Update, Insert, and Delete
statements.
3. Aren't database tables just files? --Well, DBMS's store data in files declared by system managers before
new tables are created (on large systems), but the system stores the data in a special format, and may spread
data from one table over several files. In the database world, a set of files created for a database is called a
tablespace. In general, on small systems, everything about a database (definitions and all table data) is kept
in one file.
4. (Related question) Aren't database tables just like spreadsheets? --No, for two reasons. First, spreadsheets
can have data in a cell, but a cell is more than just a row-column-intersection. Depending on your
spreadsheet software, a cell might also contain formulas and formatting, which database tables cannot have
(currently). Secondly, spreadsheet cells are often dependent on the data in other cells. In databases, "cells"
are independent, except that columns are logically related (hopefully; together a row of columns describe
an entity), and, other than primary key and foreign key constraints, each row in a table is independent from
one another.
5. How do I import a text file of data into a database? --Well, you can't do it directly...you must use a utility,
such as Oracle's SQL*Loader, or write a program to load the data into the database. A program to do this
would simply go through each record of a text file, break it up into columns, and do an Insert into the
database.
6. What web sites and computer books would you recommend for more information about SQL and
databases? --First, look at the sites at the bottom of this page. I would especially suggest the following: Ask
the SQL Pro (self-explanatory), DB Ingredients (more theorical topics), DBMS Lab/Links (comprehensive
academic DBMS link listing), Access on the Web (about web access of Access databases), Tutorial Page
(listing of other tutorials), and miniSQL (more information about the best known free DBMS).
Unfortunately, there is not a great deal of information on the web about SQL; the list I have below is fairly
comprehensive (definitely representative).
As far as books are concerned (go to amazon.com or Barnes & Noble for more information), I would
suggest (for beginners to intermediate-level) "Oracle: The Complete Reference" from Oracle and
"Understanding SQL" from Sybex for general SQL information. Also, I would recommend O'Reilly
Publishing's books, and Joe Celko's writings for advanced users. Additionally, I would suggest mcp.com
for samples of computer books, and for specific DBMS info (especially in the Access area), I recommend
Que's "Using" series, and the books of Alison Balter (search for these names at the bookstore sites for a list
of titles).
7. What is a schema? --A schema is a logical set of tables, such as the Antiques database above...usually, it is
thought of as simply "the database", but a database can hold more than one schema. For example, a star
schema is a set of tables where one large, central table holds all of the important information, and is linked,
via foreign keys, to dimension tables which hold detail information, and can be used in a join to create
detailed reports.
8. Show me an example of an outer join. --Well, from the questions I receive, this is an extremely common
example, and I'll show you both the Oracle and Access queries...
Think of the following Employee table (the employees are given numbers, for simplicity):
Name Department
1 10
2 10
3 20
4 30
5 30
Now think of a department table:
Department
10
20
30
40
Now suppose you want to join the tables, seeing all of the employees and all of the departments
together...you'll have to use an outer join which includes a null employee to go with Dept. 40.
In the book, "Oracle 7: the Complete Reference", about outer joins, "think of the (+), which must
immediately follow the join column of the table, as saying add an extra (null) row anytime there's no
match". So, in Oracle, try this query (the + goes on Employee, which adds the null row on no match):
Select E.Name, D.Department
From Department D, Employee E
Where E.Department(+) = D.Department;
This is a left (outer) join, in Access:
SELECT DISTINCTROW Employee.Name, Department.Department
FROM Department LEFT JOIN Employee ON Department.Department =
Employee.Department;
And you get this result:
Name Department
1 10
2 10
3 20
4 30
5 30
40
9. What are some general tips you would give to make my SQL queries and databases better and faster
(optimized)?
· You should try, if you can, to avoid expressions in Selects, such as SELECT ColumnA +
ColumnB, etc. The query optimizer of the database, the portion of the DBMS that determines the
best way to get the required data out of the database itself, handles expressions in such a way that
would normally require more time to retrieve the data than if columns were normally selected, and
the expression itself handled programmatically.
· Minimize the number of columns included in a Group By clause.
· If you are using a join, try to have the columns joined on (from both tables) indexed.
· When in doubt, index.
· Unless doing multiple counts or a complex query, use COUNT(*) (the number of rows generated
by the query) rather than COUNT(Column_Name).
10. What is normalization? --Normalization is a technique of database design that suggests that certain criteria
be used when constructing a table layout (deciding what columns each table will have, and creating the key
structure), where the idea is to eliminate redundancy of non-key data across tables. Normalization is usually
referred to in terms of forms, and I will introduce only the first three, even though it is somewhat common
to use other, more advanced forms (fourth, fifth, Boyce-Codd; see documentation).
First Normal Form refers to moving data into separate tables where the data in each table is of a similar
type, and by giving each table a primary key.
Putting data in Second Normal Form involves removing to other tables data that is only dependent of a part
of the key. For example, if I had left the names of the Antique Owners in the items table, that would not be
in Second Normal Form because that data would be redundant; the name would be repeated for each item
owned; as such, the names were placed in their own table. The names themselves don't have anything to do
with the items, only the identities of the buyers and sellers.
Third Normal Form involves getting rid of anything in the tables that doesn't depend solely on the primary
key. Only include information that is dependent on the key, and move off data to other tables that are
independent of the primary key, and create a primary key for the new tables.
There is some redundancy to each form, and if data is in 3NF (shorthand for 3rd normal form), it is already
in 1NF and 2NF. In terms of data design then, arrange data so that any non-primary key columns are
dependent only on the whole primary key. If you take a look at the sample database, you will see that the
way then to navigate through the database is through joins using common key columns.
Two other important points in database design are using good, consistent, logical, full-word names for the
tables and columns, and the use of full words in the database itself. On the last point, my database is
lacking, as I use numeric codes for identification. It is usually best, if possible, to come up with keys that
are, by themselves, self-explanatory; for example, a better key would be the first four letters of the last
name and first initial of the owner, like JONEB for Bill Jones (or for tiebreaking purposes, add numbers to
the end to differentiate two or more people with similar names, so you could try JONEB1, JONEB2, etc.).
11. What is the difference between a single-row query and a multiple-row query and why is it important to
know the difference? --First, to cover the obvious, a single-row query is a query that returns one row as its
result, and a multiple-row query is a query that returns more than one row as its result. Whether a query
returns one row or more than one row is entirely dependent on the design (or schema) of the tables of the
database. As query-writer, you must be aware of the schema, be sure to include enough conditions, and
structure your SQL statement properly, so that you will get the desired result (either one row or multiple
rows). For example, if you wanted to be sure that a query of the AntiqueOwners table returned only one
row, consider an equal condition of the primary key-column, OwnerID.
Three reasons immediately come to mind as to why this is important. First, getting multiple rows when you
were expecting only one, or vice-versa, may mean that the query is erroneous, that the database is
incomplete, or simply, you learned something new about your data. Second, if you are using an update or
delete statement, you had better be sure that the statement that you write performs the operation on the
desired row (or rows)...or else, you might be deleting or updating more rows than you intend. Third, any
queries written in Embedded SQL must be carefully thought out as to the number of rows returned. If you
write a single-row query, only one SQL statement may need to be performed to complete the programming
logic required. If your query, on the other hand, returns multiple rows, you will have to use the Fetch
statement, and quite probably, some sort of looping structure in your program will be required to iterate
processing on each returned row of the query.
12. Tell me about a simple approach to relational database design. --This was sent to me via a news posting; it
was submitted by John Frame ( jframe@jframe.com ) and Richard Freedman ( rfreedm@voicenet.com ); I
offer a shortened version as advice, but I'm not responsible for it, and some of the concepts are readdressed
in the next question...
First, create a list of important things (entities) and include those things you may not initially believe is
important. Second, draw a line between any two entities that have any connection whatsoever; except that
no two entities can connect without a 'rule'; e.g.: families have children, employees work for a department.
Therefore put the 'connection' in a diamond, the 'entities' in squares. Third, your picture should now have
many squares (entities) connected to other entities through diamonds (a square enclosing an entity, with a
line to a diamond describing the relationship, and then another line to the other entity). Fourth, put
descriptors on each square and each diamond, such as customer -- airline -- trip. Fifth, give each diamond
and square any attributes it may have (a person has a name, an invoice has a number), but some
relationships have none (a parent just owns a child). Sixth, everything on your page that has attributes is
now a table, whenever two entities have a relationship where the relationship has no attributes, there is
merely a foreign key between the tables. Seventh, in general you want to make tables not repeat data. So, if
a customer has a name and several addresses, you can see that for every address of a customer, there will be
repeated the customer's first name, last name, etc. So, record Name in one table, and put all his addresses in
another. Eighth, each row (record) should be unique from every other one; Mr. Freedman suggests a 'autoincrement
number' primary key, where a new, unique number is generated for each new inserted row.
Ninth, a key is any way to uniquely identify a row in a table...first and last name together are good as a
'composite' key. That's the technique.
13. What are relationships? --Another design question...the term "relationships" (often termed "relation")
usually refers to the relationships among primary and foreign keys between tables. This concept is
important because when the tables of a relational database are designed, these relationships must be defined
because they determine which columns are or are not primary or foreign keys. You may have heard of an
Entity-Relationship Diagram, which is a graphical view of tables in a database schema, with lines
connecting related columns across tables. See the sample diagram at the end of this section or some of the
sites below in regard to this topic, as there are many different ways of drawing E-R diagrams. But first, let's
look at each kind of relationship...
A One-to-one relationship means that you have a primary key column that is related to a foreign key
column, and that for every primary key value, there is one foreign key value. For example, in the first
example, the EmployeeAddressTable, we add an EmployeeIDNo column. Then, the
EmployeeAddressTable is related to the EmployeeStatisticsTable (second example table) by means of that
EmployeeIDNo. Specifically, each employee in the EmployeeAddressTable has statistics (one row of data)
in the EmployeeStatisticsTable. Even though this is a contrived example, this is a "1-1" relationship. Also
notice the "has" in bold...when expressing a relationship, it is important to describe the relationship with a
verb.
The other two kinds of relationships may or may not use logical primary key and foreign key constraints...it
is strictly a call of the designer. The first of these is the one-to-many relationship ("1-M"). This means that
for every column value in one table, there is one or more related values in another table. Key constraints
may be added to the design, or possibly just the use of some sort of identifier column may be used to
establish the relationship. An example would be that for every OwnerID in the AntiqueOwners table, there
are one or more (zero is permissible too) Items bought in the Antiques table (verb: buy).
Finally, the many-to-many relationship ("M-M") does not involve keys generally, and usually involves
idenifying columns. The unusual occurence of a "M-M" means that one column in one table is related to
another column in another table, and for every value of one of these two columns, there are one or more
related values in the corresponding column in the other table (and vice-versa), or more a common
possibility, two tables have a 1-M relationship to each other (two relationships, one 1-M going each way).
A [bad] example of the more common situation would be if you had a job assignment database, where one
table held one row for each employee and a job assignment, and another table held one row for each job
with one of the assigned employees. Here, you would have multiple rows for each employee in the first
table, one for each job assignment, and multiple rows for each job in the second table, one for each
employee assigned to the project. These tables have a M-M: each employee in the first table has many job
assignments from the second table, and each job has many employees assigned to it from the first table.
This is the tip of the iceberg on this topic...see the links below for more information and see the diagram
below for a simplified example of an E-R diagram.
14. What are some important nonstandard SQL features (extremely common question)? --Well, see the next
section...
Nonstandard SQL..."check local listings"
· INTERSECT and MINUS are like the UNION statement, except that INTERSECT produces rows that
appear in both queries, and MINUS produces rows that result from the first query, but not the second.
· Report Generation Features: the COMPUTE clause is placed at the end of a query to place the result of an
aggregate function at the end of a listing, like COMPUTE SUM (PRICE); Another option is to use break
logic: define a break to divide the query results into groups based on a column, like BREAK ON
BUYERID. Then, to produce a result after the listing of a group, use COMPUTE SUM OF PRICE ON
BUYERID. If, for example, you used all three of these clauses (BREAK first, COMPUTE on break second,
COMPUTE overall sum third), you would get a report that grouped items by their BuyerID, listing the sum
of Prices after each group of a BuyerID's items, then, after all groups are listed, the sum of all Prices is
listed, all with SQL-generated headers and lines.
· In addition to the above listed aggregate functions, some DBMS's allow more functions to be used in Select
lists, except that these functions (some character functions allow multiple-row results) are to be used with
an individual value (not groups), on single-row queries. The functions are to be used only on appropriate
data types, also. Here are some Mathematical Functions:
ABS(X) Absolute value-converts negative numbers to positive, or leaves positive numbers alone
CEIL(X) X is a decimal value that will be rounded up.
FLOOR(X) X is a decimal value that will be rounded down.
GREATEST(
X,Y) Returns the largest of the two values.
LEAST(X,Y) Returns the smallest of the two values.
MOD(X,Y) Returns the remainder of X / Y.
POWER(X,Y) Returns X to the power of Y.
ROUND(X,Y) Rounds X to Y decimal places. If Y is omitted, X is rounded to the nearest integer.
SIGN(X) Returns a minus if X < 0, else a plus.
SQRT(X) Returns the square root of X.
Character Functions
LEFT(g>,X) Returns the leftmost X characters of the string.
RIGHT(ng>,X) Returns the rightmost X characters of the string.
UPPER(ng>) Converts the string to all uppercase letters.
LOWER(ing>) Converts the string to all lowercase letters.
INITCAP(ring>) Converts the string to initial caps.
LENGTH(ring>) Returns the number of characters in the string.
||ing> followed by the second.
LPAD(g>,X,'*')
Pads the string on the left with the * (or whatever character is inside the quotes), to make the string
X characters long.
RPAD(g>,X,'*')
Pads the string on the right with the * (or whatever character is inside the quotes), to make the string
X characters long.
SUBSTR(ing>,X,Y) Extracts Y letters from the string beginning at position X.
NVL(n>,)
The Null value function will substitute for any NULLs for in the . If the current
value of is not NULL, NVL has no effect.
Syntax Summary--For Advanced Users Only
Here are the general forms of the statements discussed in this tutorial, plus some extra important ones (explanations
given). REMEMBER that all of these statements may or may not be available on your system, so check
documentation regarding availability:
ALTER TABLE ADD|DROP|MODIFY (COLUMN SPECIFICATION[S]...see
Create Table); --allows you to add or delete a column or columns from a table, or change the specification
(data type, etc.) on an existing column; this statement is also used to change the physical specifications of a table
(how a table is stored, etc.), but these definitions are DBMS-specific, so read the documentation. Also, these
physical specifications are used with the Create Table statement, when a table is first created. In addition, only one
option can be performed per Alter Table statement--either add, drop, OR modify in a single statement.
COMMIT; --makes changes made to some database systems permanent (since the last COMMIT; known as a
transaction)
CREATE [UNIQUE] INDEX
ON
(); --UNIQUE is optional; within brackets.
CREATE TABLE

( [()] ,
...other columns); (also valid with ALTER TABLE)
--where SIZE is only used on certain data types (see above), and constraints include the following possibilities
(automatically enforced by the DBMS; failure causes an error to be generated):
1. NULL or NOT NULL (see above)
2. UNIQUE enforces that no two rows will have the same value for this column
3. PRIMARY KEY tells the database that this column is the primary key column (only used if the key is a one
column key, otherwise a PRIMARY KEY (column, column, ...) statement appears after the last column
definition.
4. CHECK allows a condition to be checked for when data in that column is updated or inserted; for example,
CHECK (PRICE > 0) causes the system to check that the Price column is greater than zero before
accepting the value...sometimes implemented as the CONSTRAINT statement.
5. DEFAULT inserts the default value into the database if a row is inserted without that column's data being
inserted; for example, BENEFITS INTEGER DEFAULT = 10000
6. FOREIGN KEY works the same as Primary Key, but is followed by: REFERENCES

(), which refers to the referential primary key.
CREATE VIEW
AS ;
DELETE FROM
WHERE ;
INSERT INTO
[()]
VALUES ();
ROLLBACK; --Takes back any changes to the database that you have made, back to the last time you gave a
Commit command...beware! Some software uses automatic committing on systems that use the transaction features,
so the Rollback command may not work.
SELECT [DISTINCT|ALL]
FROM
[WHERE ]
[GROUP BY ]
[HAVING ]
[ORDER BY [ASC|DESC]]; --where ASC|DESC allows the ordering to be
done in ASCending or DESCending order
UPDATE

SET =
[WHERE ]; --if the Where clause is left out, all rows will be updated according to the Set
statement
Important Links
Computing & SQL/DB Links: Netscape -- Oracle -- Sybase -- Informix --Microsoft
SQL Reference Page -- Ask the SQL Pro -- SQL Pro's Relational DB Useful Sites
Programmer's Source -- DBMS Sites -- inquiry.com -- DB Ingredients -- SQL Trainer S/W
Web Authoring -- DBMS Lab/Links -- SQL FAQ -- Query List -- MySQL
Database Jump Site -- Programming Tutorials on the Web -- PostgreSQL -- Adobe Acrobat
DB Stuff -- DBMS/IS Pages -- Access on the Web -- Online Books -- A Good DB Course
Tutorial Page -- DBMS Magazine -- Database Mining -- miniSQL -- Adabas
Miscellaneous: CNN -- USA Today -- Pathfinder -- ZDNet -- CNet -- TechWeb -- LookSmart -- Amazon.com
Books
Search Engines: Yahoo -- Alta Vista -- Excite -- WebCrawler -- Lycos -- Infoseek -- search.com
These sites are encouraged, but not officially endorsed by the author.
Disclaimer
I hope you have learned something from this introductory look at a very important language that is becoming more
prevalent in the world of client-server computing. I wrote this web page in order to contribute something of value to
the web and the Internet community. In fact, I have been informed that this document is being used at several
colleges and companies for use in database classes, and as a resource for many others. In addition, I would like to
thank all of the people from across five continents who have contacted me regarding this web page.
In addition, I strongly urge you to visit some of the database links shown above, especially if you're interested in
advanced topics, such as the SQL-92 standard, different relational DBMS's, and advanced query processing.
Unfortunately, however, the number of database web sites remains small, and if you are unable to find the
information for which you are looking at the links displayed above, the information may not be available on the
web, and that you will have to potentially contact a database vendor for the information you seek. In fact, if you're
using a well-known, name-brand DBMS, the web site of your vendor is often the first and best place to look for
information...you'll just have to do some hunting for the documentation when you get there. Another good place is to
search for book publisher sites; you'll occasionally find some gems.
I also hope to continue to add more material to this tutorial, such as topics about database design and nonstandard
SQL extensions, even though I wish to stay away from material about individual Database Management Systems.
Good luck in your SQL and other computing adventures.
Jim Hoffman
Comments or suggestions? Mail me at jhoffman@one.net.
Or you may wish to look at Jim Hoffman's Web Pages for more information about myself, or my Algorithms
Tutorial.
Copyright 1996-1999, James Hoffman. This document can be used for free by any Internet user, but cannot be
included in another document, another web site or server, published in any other form, or mass produced in any way.
This page is best viewed with Netscape Navigator; it doesn't look quite right with Microsoft Internet Explorer.
Last updated: 1-12-1999; deleted links to download files.
http://w3.one.net/~jhoffman/sqltut.htm

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