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 "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 possibilities 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.

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

Orders

Antiques

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 own) 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. In general, you should always use Dot notation as when you change your database, some queries that did not use Dot notation may cease working because they become ambiguous.

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 occurrences 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:

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.

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.

Modifying the Database

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 (Parentheses optional):

ALTER TABLE ANTIQUES ADD (PRICE DECIMAL(8,2) NULL);

The data for this new column can be updated or inserted as shown later.

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 table:

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);