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Introduction to Structured Query Language
This page is a tutorial of the Structured Query Language (also
known as SQL). 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.
Any questions send mail to sql@teentwo.8m.com
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
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 ('). Note: Position is now an illegal identifier
because it is now an unused, but reserved, keyword in the SQL-92 standard.
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.
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 BENEFITS > 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)
- NOT
- AND
- OR
Using LIKE
Look at the EmployeeStatisticsTable, and say you wanted to see all people whose last
names started with "S"; try:
SELECT EMPLOYEEIDNO
FROM EMPLOYEEADDRESSTABLE
WHERE LASTNAME LIKE 'S%';
The percent sign (%) is used to represent any possible character (number, letter, or
punctuation) or set of characters that might appear after the "S". To find those
people with LastName's ending in "S", use '%S', or if you wanted the
"S" in the middle of the word, try '%S%'. 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 (however, it is generally not necessary to strictly
put the Distinct in front of the column name).
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
This gives:
Last Name Item Ordered
--------- ------------
Smith Table
Smith Desk
Akins Chair
Lawson Mirror
There are several things to note about this query:
- First, the "Last Name" and "Item Ordered" in the Select lines gives
the headers on the report.
- 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.
- 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).
- 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.
- 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 >
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
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 =
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
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
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
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 <stdio.h>
/* 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
- 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.
- 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. Also, QML, referring to Select statements,
stands for Query Manipulation Language.
- 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.
- (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.
- 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.
- 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). An excellent page about relational database
design was recently brought to my attention by the author, Fernando Lozano (you may also wish to see his mSQL page). Also, if you wish to practice SQL on an
interactive site (using Java technologies), I highly recommend Frank Torres' (torresf@uswest.net) site
at http://sqlcourse.com. Frank did an outstanding job with his site, and if you
have a recent release browser, it's definitely worth a visit. In addition, point
your browser to http://www.tipworld.com/, and
subscribe to their SQL e-mail Tips of the Day...they are oustanding; Tim Quinlan goes into
topics that I can't even begin to go into here, such index data structures (B-trees and
B+-trees) and join algorithms, so advanced IT RDBMS pros will get a daily insight into
these data management tools.
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). Also, look for the recent
publications, "SQL from the Ground Up" and "SQL Unleashed".
- 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.
- I understand that Oracle offers a special keyword, Decode, that allows for some
"if-then" logic. How does that work? -- Technically, Decode allows for
conditional output based on the value of a column or function. The syntax looks like this
(from the Oracle: Complete Reference series):
Select ...DECODE (Value, If1, Then1,
[If 2, Then 2, ...,] Else) ...From ...;
The Value is the name of a column, or a function (conceivably based on a column or
columns), and for each If included in the statement, the corresponding Then clause is the
output if the condition is true. If none of the conditions are true, then the Else value
is output. Let's look at an example:
Select Distinct City,
DECODE (City, 'Cincinnati', 'Queen City', 'New York', 'Big Apple', 'Chicago',
'City of Broad Shoulders', City) AS Nickname
From Cities;
The output might look like this:
City Nickname
------------ ------------------------------
Boston Boston
Cincinnati Queen City
Cleveland Cleveland
New York Big Apple
'City' in the first argument denotes the column name used for the test. The second,
fourth, etc. arguments are the individual equality tests (taken in the orden given)
against each value in the City column. The third, fifth, etc. arguments are the
corresponding outputs if the corresponding test is true. The final parameter is the
default output if none of the tests are true; in this case, just print out the column
value.
TIP: If you want nothing to be output for a given condition, such as the default
"Else" value, enter the value Null for that value, such as:
Select Distinct City,
DECODE (City, 'Cincinnati', 'Queen City', 'New York', 'Big Apple', 'Chicago',
'City of Broad Shoulders', Null) AS Nickname
From Cities;
If the City column value is not one of the ones mentioned, nothing is outputted, rather
than the city name itself.
City Nickname
------------ ----------
Boston
Cincinnati Queen City
Cleveland
New York Big Apple
- You mentioned Referential Integrity before, but what does that have to do with this
concept I've heard about, Cascading Updates and Deletes? --This is a difficult topic to
talk about, because it's covered differently in different DBMS's.
For example,
Microsoft SQL Server (7.0 & below) requires that you write "triggers" (see
the Yahoo SQL Club link to find links that discuss this topic--I may include that topic in
a future version of this page) to implement this. (A quick definition, though; a Trigger
is a SQL statement stored in the database that allows you to perform a given query
[usually an "Action" Query--Delete, Insert, Update] automatically, when a
specified event occurs in the database, such as a column update, but anyway...) Microsoft
Access (believe it or not) will perform this if you define it in the Relationships screen,
but it will still burden you with a prompt. Oracle does this automatically, if you specify
a special "Constraint" (see reference at bottom for definition, not syntax) on
the keyed column.
So, I'll just discuss the concept. First, see the discussion above on Primary and
Foreign keys.
Concept: If a row from the primary key column is deleted/updated, if
"Cascading" is activated, the value of the foreign key in those other tables
will be deleted (the whole row)/updated.
The reverse, a foreign key deletion/update causing a primary key value to be
deleted/changed, may or may not occur: the constraint or trigger may not be defined, a
"one-to-many" relationship may exist, the update might be to another existing
primary key value, or the DBMS itself may or may not have rules governing this. As usual,
see your DBMS's documentation.
For example, if you set up the AntiqueOwners table to have a Primary Key, OwnerID, and
you set up the database to delete rows on the Foreign Key, SellerID, in the Antiques
table, on a primary key deletion, then if you deleted the AntiqueOwners row with OwnerID
of '01', then the rows in Antiques, with the Item values, Bed, Cabinet, and Jewelry Box
('01' sold them), will all be deleted. Of course, assuming the proper DB definition, if
you just updated '01' to another value, those Seller ID values would be updated to that
new value too.
- 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:
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 |
- 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).
- 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.).
- 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.
- 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 'auto-increment 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.
- 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.
- 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. |
LEFT(<string>,X) |
Returns the leftmost X characters of the string. |
RIGHT(<string>,X) |
Returns the rightmost X characters of the string. |
UPPER(<string>) |
Converts the string to all uppercase letters. |
LOWER(<string>) |
Converts the string to all lowercase letters. |
INITCAP(<string>) |
Converts the string to initial caps. |
LENGTH(<string>) |
Returns the number of characters in the string. |
<string>||<string> |
Combines the two strings of text into one, concatenated string,
where the first string is immediately followed by the second. |
LPAD(<string>,X,'*') |
Pads the string on the left with the * (or whatever character is
inside the quotes), to make the string X characters long. |
RPAD(<string>,X,'*') |
Pads the string on the right with the * (or whatever character is
inside the quotes), to make the string X characters long. |
SUBSTR(<string>,X,Y) |
Extracts Y letters from the string beginning at position X. |
NVL(<column>,<value>) |
The Null value function will substitute <value> for any NULLs
for in the <column>. If the current value of <column> 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 <TABLE NAME> 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 <INDEX NAME>
ON <TABLE NAME> (<COLUMN LIST>); --UNIQUE is optional; within
brackets.
CREATE TABLE <TABLE NAME>
(<COLUMN NAME> <DATA TYPE> [(<SIZE>)] <COLUMN CONSTRAINT>,
...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):
- NULL or NOT NULL (see above)
- UNIQUE enforces that no two rows will have the same value for this column
- 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.
- 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.
- 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
- FOREIGN KEY works the same as Primary Key, but is followed by: REFERENCES <TABLE
NAME> (<COLUMN NAME>), which refers to the referential primary key.
CREATE VIEW <TABLE NAME> AS <QUERY>;
DELETE FROM <TABLE NAME> WHERE <CONDITION>;
INSERT INTO <TABLE NAME> [(<COLUMN LIST>)]
VALUES (<VALUE LIST>);
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] <LIST OF COLUMNS, FUNCTIONS, CONSTANTS, ETC.>
FROM <LIST OF TABLES OR VIEWS>
[WHERE <CONDITION(S)>]
[GROUP BY <GROUPING COLUMN(S)>]
[HAVING <CONDITION>]
[ORDER BY <ORDERING COLUMN(S)> [ASC|DESC]]; --where ASC|DESC allows the
ordering to be done in ASCending or DESCending order
UPDATE <TABLE NAME>
SET <COLUMN NAME> = <VALUE>
[WHERE <CONDITION>]; --if the Where clause is left out, all rows will be
updated according to the Set statement.
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