Oracle for Beginners

A Short Oracle Tutorial For Beginners

This is just a short introduction to Oracle for beginners, to give a brief history of databases and

Oracle's role in that history, explain relational theory and provide a few practical examples to

show how relational databases work. If you would like to learn more just contact us and ask for

our free tutorial.

History of Databases - From Trees To Objects

The storage and management of data is probably the biggest headache for all businesses.

It has been so for a long while and is likely to continue for a long while too. As companies aim to

store more and more details about their customers and their buying habits, they need to store and

manage more and more data. The only way this can be done efficiently and at a reasonable cost

is by the use of computers.

In the late 1960s/early 1970s, specialised data management software appeared - the first database

management systems (DBMS). These early DBMS were either

hierarchical (tree) or network (CODASYL) databases and were, thererfore, very complex and

inflexible which made life difficult when it came to adding new applications or reorganising the

data.

The solution to this was relational databases which are based on the concept of normalisation -

the separation of the logical and physical representation of data.

In 1970 the relational data model was defined by E.F. Codd (see "A Relational Model of Data for

Large Shared Data Banks" Comm. ACM. 13 (June 6, 1970), 377-387).

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In 1974 IBM started a project called System/R to prove the theory of relational databases. This

led to the development of a query language called SEQUEL (Structured English Query

Language) later renamed to Structured Query Language (SQL) for legal reasons and now the

query language of all databases.

In 1978 a prototype System/R implementation was evaluated at a number of IBM customer sites.

By 1979 the project finished with the conclusion that relational databases were a feasible

commercial product.

Meanwhile, IBM's research into relational databases had come to the attention of a group of

engineers in California. They were so convinced of the potential that they formed a company

called Relational Software, Inc. in 1977 to build such a database. Their product was called

Oracle and the first version for VAX/VMS was released in 1979, thereby becoming the first

commercial rdbms, beating IBM to market by 2 years.

In the 1980s the company was renamed to Oracle Corporation. Throughout the 1980s, new

features were added and performance improved as the price of hardware came down and Oracle

became the largest independent rdbms vendor. By 1985 they boasted of having more than 1000

installations.

As relational databases became accepted, companies wanted to expand their use to store images,

spreadsheets, etc. which can't be described in 2-dimensional terms. This led to the Oracle

database becoming an object-relational hybrid in version 8.0, i.e. a relational database with

object extensions, enabling you to have the best of both worlds.

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What is a relational database?

As mentioned before, a relational database is based on the separation and independence of the

the logical and physical representations of the data. This provides enormous flexibility and

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means you can store the data physically in any way without affecting how the data is presented

to the end user. The separation

of physical and logical layers means that you can change either layer without affecting the other.

A relational database can be regarded as a set of 2-dimensional tables which are known as

"relations" in relational database theory. Each table has rows ("tuples") and columns

("domains"). The relationships between the tables is defined by one table having a column with

the same meaning (but not necessarily value) as a column in another table.

For example consider a database with just 2 tables :

emp(id number

,name varchar2(30)

,job_title varchar2(20)

,dept_id number)

holding employee information and

dept(id number

,name varchar2(30))

holding department information.

There is an implied relationship between these tables because emp has a column called dept_id

which is the same as the id column in dept. In Oracle this is usually implemented by what's

called a foreign-key relationship which prevents values being stored that are not present in the

referenced table.

Relational databases obtain their flexibility from being based on set theory (also known as

relational calculus) which enables sets or relations to be combined in various ways, including:

join/intersection union (i.e. the sum of 2 sets); exclusive "OR" (i.e. the difference between 2 sets) and outer-join which is a combination of intersecting and exclusive or ing.

The intersection or join between 2 sets (in this case, tables) produces only those elements that

exist in both sets.

Therefore, if we join Emp and Dept on department id, we will be left with only those employees

who work for a department that is in the dept table and only those departments which have

employees who are in the emp table.

The union produces the sum of the tables - meaning all records in Emp and all records in Dept.

and this may be with or without duplicates.

Let's use the following data to provide specific examples:

Emp

Id Name Dept Id

1 Bill Smith 3

2 Mike Lewis 2

3 Ray Charles 3

4 Andy Mallory 4

5 Mandy Randall 6

6 Allison White 1

Dept

Id Name

1 HR

2 IT

3 Marketing

4 Sales

5 Finance

The join of Emp and Dept. on the department id would produce the following result:

Emp.Id Emp.Name Dept.Id Dept.Name

1 Bill Smith 3 Marketing

2 Mike Lewis 2 IT

3 Ray Charles 3 Marketing

4 Andy Mallory 4 Sales

6 Allison White 1 HR

The union of Emp and Dept. would produce the following results

Id Name

1 Bill Smith

2 Mike Lewis

3 Ray Charles

4 Andy Mallory

5 Mandy Randall

1 HR

2 IT

3 Marketing

4 Sales

5 Finance

The union operator is only allowed when the number and data types of the columns in the 2 sets

are the same. It is not normally be used to combine sub sections from one or more tables rather

than entire tables.

There are other operators and variations but there isn't the space or the time to provide full details

in this short Oracle tutorial.

The later versions of Oracle (Oracle 8 onwards) support both relational and object-oriented

features. The relational features are more prominent at the moment, but this is beginning to

change. In this context an object has both attributes and methods (programs stored with the

object that performs a certain action or task) and in a true object-oriented database would belong

to a class and would allow multilevel inheritance.

Click here for more Oracle Tutorials

Oracle tutorial part1

SQL - (pronounced "sequel")

SQL stands for Structured Query Language, and it is a very powerful and diverse language used

to create and query databases. Its loose syntax makes it easy to learn, but mastering its intricate

architecture may take a bit longer.

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Arming yourself with a firm understanding of its structure and mechanics will allow you to build

simple, dynamic applications for the web or to create robust applications using data and

databases.

The loose structure and flexibility of this language make it an ideal candidate for the web,

especially since there are more than a handful of database applications available for developers o

use for free, such as Microsoft's SQL Server Express and MySQL.

SQL - Fundamentals

Some of the basic functions of SQL are inputting, modifying, and dropping data from databases.

In this tutorial, we use command line examples to give you an idea of what SQL is capable of.

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Coupled with the use of web languages such as HTML and PHP, SQL becomes an even greater

tool for building dynamic web applications.

SQL - Tutorial Scope

Reading further, you will encounter a number of hands-on examples intended to introduce you to

SQL. The majority of these examples are intended to span across the different available

variations of SQL, but the primary focus of this tutorial is Microsoft's SQL Server Express.

SQL - Getting Started

To get started, you will need to install Microsoft SQL Server Express. For installation help, we

suggest you go straight to the developer homepage:

SQL Server Express Download:

SQL Server

It is preferred that you select SQL Server Express 2008 for this tutorial. This version of SQL is

available for private use for free, and we've provided the link to Microsoft's site, or you can find

the download page by searching for "SQL Server Express" on Google.

Follow the online installation guide that Microsoft provides, and launch SQL Server

Management Studio Express to connect to your SQL database. This Management Studio

Application will be your temporary home for the remainder of the tutorial.

SQL - World Wide Web

Building a website on SQL architecture is quickly becoming the standard among web 2.0 sites.

With a SQL backend, it is fairly simple to store user data, email lists, or other kinds of dynamic

data. E-Commerce web sites, community sites, and online web services rely on SQL databases to

manage user data or process user purchases.

SQL has become popular among web developers due to its flexibility and simplicity. With some

basic knowledge of HTML, PHP, and a database program such as Microsoft's SQL Server, a

developer becomes capable of creating complex websites and applications while relying on

online web services to provide a SQL backend in which user data is stored. This tutorial will

provide you with just a small taste of this type of programming and architecture.

SQL - Databases

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What's a Database? A SQL database is nothing more than an empty shell, like a vacant

warehouse. It offers no real functionality whatsoever, but does provide a virtual space to store

data. Data is stored inside of database objects called tables, and tables are the containers that

actually hold specific types of data, such as numbers, files, strings, and dates.


A single database can house hundreds of tables containing more than 1,000 table columns each

and they may be jam packed with relational data ready to be retrieved by SQL. Perhaps the

greatest feature SQL offers is that it doesn't take much effort to rearrange your warehouse to

meet your ever-growing business needs.

SQL - Creating a Database

Creating a database inside of SQL Express has its advantages. After launching Microsoft's SQL

Server Management Studio Express application, simply right-clicking on the Databases folder of

the Object Explorer gives you the option to create a New Database. After selecting the New

Database... option, name your database "MyDatabase" and press "OK".

Now is the time to press the New Query button located toward the top of the screen, just above

the Object Explorer pane.

Pressing this button offers an empty tab. All SQL query statements (code) that we will be

exploring will be entered here and executed against the SQL Express database.

If you haven't yet created a new database, you may also create a database by typing the following

SQL query statement into your new empty query tab, and then pressing the Execute button or

striking the (F5) key.

SQL Create Database Query:

CREATE DATABASE MyDatabase;

After executing this query, SQL will notify you that your query has run successfully and that the

database was created successfully. If you receive an error message instead, Google the error


message for troubleshooting advice. (Vista users must verify that they are running SQL Server

Management Studio Express with administrator privileges.)

Congratulations! You have executed your first SQL command and written what is perhaps your

first bit of SQL code.

SQL - Tables

Data is stored inside SQL tables which are contained within SQL databases. A single database

can house hundreds of tables, each playing its own unique role in the database schema. While

database architecture and schema are concepts far above the scope of this tutorial, we plan on

diving in just past the surface to give you a glimpse of database architecture that begins with a

thorough understanding of SQL Tables.


SQL tables are comprised of table rows and columns. Table columns are responsible for storing

many different types of data, like numbers, texts, dates, and even files. There are many different

types of table columns and these data types vary, depending on how the SQL table has been

created by the SQL developer. A table row is a horizontal record of values that fit into each

different table column.

SQL - Create a SQL Table

Let's now CREATE a SQL table to help us expand our knowledge of SQL and SQL commands.

This new table will serve as a practice table and we will begin to populate this table with some

data which we can then manipulate as more SQL Query commands are introduced. The next

couple of examples will definitely be overwhelming to novice SQL programmers, but we will

take a moment to explain what's going on.

SQL Create Table Query:

USE mydatabase;

CREATE TABLE orders

(id INT IDENTITY(1,1) PRIMARY KEY,

customer VARCHAR(50),

day_of_order DATETIME,

product VARCHAR(50),

quantity INT);

The first line of the example, "USE mydatabase;", is pretty straightforward. This line defines the

query scope and directs SQL to run the command against the MyDatabase object we created

earlier in the SQL Databases lesson. The blank line break after the first command is not required,


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but it makes our query easier to follow. The line starting with the CREATE clause is where we

are actually going to tell SQL to create the new table, which is named orders.

Each table column has its own set of guidelines or schema, and the lines of code above contained

in parenthesis () are telling SQL how to go about setting up each column schema. Table columns

are presented in list format, and each schema is separated with a comma (,). It isn't important to

fully understand exactly what all of these schema details mean just yet. They will be explained in

more detail throughout the remainder of the tutorial. For now, just take note that we are creating

a new, empty SQL table named orders, and this table is 5 columns wide.

SQL - INSERT DATA into your New Table

Next, we will use SQL's INSERT command to draw up a query that will insert a new data row

into our brand new SQL table, orders. If you're already familiar with everything we've covered

so far, please execute the query below and then skip ahead and start learning about other SQL

Queries.

SQL Insert Query:

USE mydatabase;

INSERT INTO orders

(customer,day_of_order,product, quantity)

VALUES('Tizag','8/1/08','Pen',4);

SQL Insert Query Results:

(1 row(s) affected)

This message ("1 row(s) affected") indicates that our query has run successfully and also informs

us that 1 row has been affected by the query. This is the desired result as our goal was to insert a

single record into the newly formed orders table.

Listed above is a typical INSERT query used to insert data into the table we had previously

created. The first line ("USE mydatabase;") identifies the query scope and the line after indicates

what it is we'd like SQL to do for us. ("INSERT INTO orders") inserts data into the orders table.

Then, we have to list each table column by name (customer,day_of_order,product, quantity) and

finally provide a list of values to insert into each table column VALUES('Tizag','8/1/08','Pen',4).

You may notice that we have not included the id column, and this is intentional. We have set this

column up in a way that allows SQL to populate this field automatically, and therefore, we do

not need to worry about including it in any of our INSERT statements. (More on this later.)



SQL - Queries

SQL coins the term query as the name for its commands. Basically, all SQL code is written in

the form of a query statement and then executed against a database. All SQL queries perform

some type of data operation such as selecting data, inserting/updating data, or creating data

objects such as SQL databases and SQL tables. Each query statement begins with a clause such

as SELECT,UPDATE, CREATE or DELETE.


SELECT queries are the most commonly used SQL commands, so let's take a look at a SELECT

query that will return records from the orders table that we created previously in the SQL Tables

lesson.

SQL Query Code:

USE mydatabase;

SELECT * FROM orders;

SQL Query Results:

id customer day_of_order product quantity

1 Tizag 2008-08-01 00:00:00.000 Pen 4

We'll explain the mechanics of this code in the next lesson. For now, just know that SELECT

queries essentially tell SQL to go and "fetch" table data for your viewing pleasure.

Here's a look at a few different query types including a INSERT and SELECT query we will be

covering in the next lesson, SQL Select.

SQL Query Examples:

-- Inserts data into a SQL Database/Table

INSERT INTO orders (customer,day_of_order,product, quantity)

VALUES('Tizag','8/1/08','Pen',4);

-- Selects data from a SQL Database/Table

SELECT * FROM orders;

-- Updates data in a Database/Table

UPDATE orders SET quantity = '6'

WHERE id = '1'


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More information about these queries can be found at the following links: SQL Insert, SQL

Update, SQL Delete

SQL - Query Structure Review

Structurally, each SQL query we have seen in this lesson are similar. Each start with a clause

telling SQL which operation to perform and the remaining lines provide more detailed

information as to how we want SQL to go about performing each SQL Command.

SQL - Select

SQL SELECT may be the most commonly used command by SQL programmers. It is used to

extract data from databases and to present data in a user-friendly table called the result set.


SQL Select Query Template:

SELECT table_column1, table_column2, table_column3

FROM my_table;

Select queries require two essential parts. The first part is the "WHAT", which determines what

we want SQL to go and fetch. The second part of any SELECT command is the "FROM

WHERE". It identifies where to fetch the data from, which may be from a SQL table, a SQL

view, or some other SQL data object.

Now we would like SQL to go and fetch some data for us from the orders table that was created

in the previous lesson. How do we translate this request into SQL code so that the database

application does all the work for us? Simple! We just need to tell SQL what we want to select

and from where to select the data, by following the schema outlined below.

SQL Select Query Code:

USE mydatabase;

SELECT id, customer, day_of_order, product, quantity

FROM orders;

SQL Orders Table Results:


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1 Tizag 2008-08-01 00:00:00.000 Pen 4

Below, we will manipulate the result output by rearranging the list of table column names inside

of the SELECT statement.

SQL Select Query: Rearranged:

USE mydatabase;

SELECT day_of_order, customer, product, quantity

FROM orders;


day_of_order customer product quantity

2008-08-01 00:00:00.000 Tizag Pen 4

By rearranging the table column list inside the SELECT statement, we altered the appearance of

the result set. Also, by not including the id column in the list of table columns, SQL did not fetch

any column data for this column because we didn't ask SQL to do so.

SQL - Select All (*)

"SELECT (*)" is a shortcut that can be used to select all table columns rather than listing each of

them by name. Unfortunately, going this route doesn't allow for you to alter the presentation of

the results.

SQL Select All Query:

USE mydatabase;

SELECT *

FROM orders;



1 Tizag 2008-08-01 00:00:00.000 Pen 4

SQL - Selecting Data

The (*) query statement should be used with caution. Using this against our little tutorial

database will surely do no harm, but using this query against an extremely large database may

not be the best practice. Large databases may have web services or applications attached to them,

so frequently updating and accessing large quantities data may temporarily lock a table for

fractions of a second or more. If this disruption happens to occur just as some piece of data is

being updated, you may experience data corruption.

Taking every precaution to avoid data corruption is in your best interest as a new SQL

programmer. Corrupted data may be lost and never recovered, and it can lead to even more

corruption inside a database. The best habits are to be as precise as possible, and in the case of

select statements, this often means selecting minimal amounts of data when possible.

At this point, you should feel comfortable with SELECT and how to look into your database and

see actual data rows residing inside of tables. This knowledge will prove invaluable as your SQL

skills develop beyond the basics and as you begin to tackle larger, more advanced SQL projects.

SQL - Where

The WHERE clause sets a conditional statement, and it can be used with any type of SQL

query. As the select query executes, SQL processes one row at a time. Each time the conditional

statement is met (returns true), a row is returned as a result. SQL WHERE is essentially, a

filtering mechanism for SQL queries and is a tremendous asset to any aspiring SQL developer.


SQL Where Query:

USE mydatabase;

SELECT *

FROM orders

WHERE customer = 'Tizag'

As we take a look at the results, notice how only the rows that meet the criteria (where the

customer column value is Tizag) are returned. In this example, we are using the WHERE clause

to filter out rows and only selecting data that meets the conditional statement.

SQL Results:



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2 Tizag 2008-08-01 00:00:00.000 Stapler 1

5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

Conditional statements are not unique to SQL, and neither are operators. Operators are symbols

such as (=) or (<), and they are seen inside of conditional statements and expressions in SQL and

other programming languages. While we're not going to dive into much detail about the different

kinds of operators yet, it is a good idea to be familiar with them and be able to recognize them

inside of conditional statements as we look over the next few examples.

SQL - Where Queries

With the WHERE clause on our tool belts, we can be more creative when querying for table

rows. For instance, there may come a time where we would like to take a look at all the orders

placed after a certain date.

SQL Where Date Query:

USE mydatabase;

SELECT *

FROM orders

WHERE day_of_order > '7/31/08'

This conditional statement will return only the orders that have made it into the table since the

end of July, filtering out any orders in the table made prior to July 31st.

SQL Results:


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2 Tizag 2008-08-01 00:00:00.000 Stapler 1

3 A+Maintenance 2008-08-16 00:00:00.000 Hanging Files 12

4 Gerald Garner 2008-08-15 00:00:00.000 19" LCD Screen 3

Notice how the date value is formatted inside the conditional statement. We passed a value

formatted MM/DD/YY, and we've completely neglected the hours, minutes, and seconds values,

yet SQL is intelligent enough to understand this. Therefore, our query is successfully executed.

SQL - Where with Multiple Conditionals

A WHERE statement can accept multiple conditional statements. What this means is that we are

able to select rows meeting two different conditions at the same time.

Perhaps the easiest way to go about this is to add another condition to the previous example,

where we retrieved only the orders placed after July 31st. We can take this example one step

further and link two conditional statements together with "AND".

SQL Where And:

USE mydatabase;

SELECT *

FROM orders


AND customer = 'Tizag'

At this point, we have sent SQL two conditional statements with a single WHERE clause,

essentially applying two filters to the expected result set.

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

By applying the AND clause, SQL has now been asked to return only rows that meet both

conditional statements. In this case, we would like to return all orders that were made before July

31st and made by a specific company - which is, in this case, Tizag. We have more examples of

SQL AND/OR. Just follow the link.

SQL - As

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SQL AS temporarily assigns a table column a new name. This grants the SQL developer the

ability to make adjustments to the presentation of query results and allow the developer to label

results more accurately without permanently renaming table columns.


SQL Select As Code:

USE mydatabase;

SELECT day_of_order AS "Date",

customer As "Client",

product,

quantity

FROM orders;


Date Client product quantity

2008-08-01 00:00:00.000 Tizag Pen 4

SQL AS allows us to use any name at the presentation level and helps the developer better

describe a column in the result set.

SQL Select Arithmetic Query:

USE mydatabase;

SELECT (5 + 12) AS "5 plus 12 is"

SQL Arithmetic Results:

5 plus 12 is

17

SQL - Operators

SQL operators are found in just about every SQL query. Operators are the mathematical and

equality symbols used to compare, evaluate, or calculate values. Equality operators include the

(<), (>), and (=) symbols, which are used to compare one value against another. Each of these


characters have special meaning, and when SQL comes across them, they help tell SQL how to

evaluate an expression or conditional statement. Most operators will appear inside of conditional

statements in the WHERE clause of SQL Commands.


Operators come in three flavors: mathematical, logical, and equality. Mathematical operators

add, subtract, multiply, and divide numbers. Logical operators include AND and OR. Take note

of the following tables for future reference.

SQL operators are generally found inside of queries-- more specifically, in the conditional

statements of the WHERE clause.

SQL Equality Operator Query:

USE mydatabase;

SELECT customer,day_of_order

FROM orders


Sql Equality Operator:

customer day_of_order

Tizag 2008-08-01 00:00:00.000

Tizag 2008-08-01 00:00:00.000

In this case, we've used the equality operator greater than (>) to return orders from the orders

table with a date greater than '7/31/08'.

SQL - Equality Operator Table

Equality involves comparing two values. To do so requires the use of the (<), (>), or (=) special

characters. Does X = Y? Is Y < X? These are both questions that can be answered using a SQL

Equality Operator expression.

SQL Equality Operators:

Operator Example Defined Result

=, IS 5 = 5 5 equal to 5? True

!=, IS NOT 7 != 2 7 IS NOT (!=) equal to 2? True

< 7 < 4 7 less than 4? False


> 7 > 4 greater than 4? True

<= 7 <= 11 Is 7 less than or equal to 11? True

>= 7 >= 11 Is 7 greater than or equal to 11? False

SQL - Mathematical Operators

SQL mathematical operations are performed using mathematical operators (+, -, *, /, and %). We

can use SQL like a calculator to get a feel for how these operators work.

SQL Mathematical Operators:

SELECT

15 + 4, --Addition

15 - 4, --Subtraction

15 * 4, --Multiplication

15 / 5, -- Division

15 % 4; --Modulus

SQL Results:

Addition Subtraction Multiplication Division Modulus

19 11 60 3 3

Modulus may be the only unfamiliar term on the chart. Modulus performs division, dividing the

first digit by the second digit, but instead of returning a quotient, a "remainder" value is returned

instead.

Modulus Example:

USE mydatabase;

SELECT (5 / 2) -- = 2.5

SELECT (5 % 2) -- = 1 is the value that will be returned

SQL - Logical Operators

These operators provide you with a way to specify exactly what you want SQL to go and fetch,

and you may be as specific as you'd like! We'll discuss these a little later on and provide some

real world scenarios as well.

We cover these operators thoroughly in the SQL AND/OR lesson.

AND - Compares/Associates two values or expressions

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OR - Compares/Associates two values or expressions

QL - Create

SQL CREATE is the command used to create data objects, including everything from new

databases and tables to views and stored procedures. In this lesson, we will be taking a closer

look at how table creation is executed in the SQL world and offer some examples of the different

types of data a SQL table can hold, such as dates, number values, and texts.


To accomplish this, it is best to first take a look at the entire CREATE TABLE query and then

review each line individually.

SQL Create Table Code:

USE mydatabase;

CREATE TABLE inventory

(

id INT IDENTITY(1,1) PRIMARY KEY,

product VARCHAR(50) UNIQUE,

quantity INT,

price DECIMAL(18,2)

);

Line 1 identifies the scope of the query specifying a target database for query execution (USE

mydatabase) and we've seen it before so let's skip ahead to the next line, line 2 (CREATE

TABLE inventory). This line informs SQL of the plan to create a new table using the CREATE

clause and specifies the name of the new table (inventory). In this case, we plan on creating an

inventory table to maintain a current inventory of store items for an imaginary e-commerce web

site.

SQL Create Line 3:


Line 3 should appear more foreign as there is a lot of information embedded in this line, but it is

not as hard as it seems. This is the first line that declares how to set up the first table column

inside the new inventory table.

id = The name of this new table column.

INT = The data type. INT is short for integer.

The first word, id, is the name of this new column and the second word declares the data type,

INT (integers). SQL will now expect this table column to house only integer data type values.


IDENTITY (1,1) = The id column will be an identity column.

The next phrase, IDENTITY (1, 1) is a very special attribute and when a table column is marked

as an identity column, the column essentially turns into an automated counter. As new rows are

inserted into the table, this column value will automatically increment (count up). The

parameters (1,1) tell SQL which number to start counting from and by how many to increment

each value. In this case, we'll start with 1, and increment by 1 each time a new row is inserted

into our database. For example, the first INSERT command run against the inventory table will

have an id value of 1, and each consecutive row inserted thereafter will increment by one (1, 2, 3,

4 ... etc). This identity table column is essentially counting each inserted row and also ensuring

that we have a unique identifier value. This is important since this column has also been

identified as a primary key (see below).

PRIMARY KEY = This places a restraint on this column (no duplicate values)

Bringing up the tail-end of Line 3 is reserved for specifying any unique attributes to associate

with this table column. In this case, we have told SQL that this column will act as the PRIMARY

KEY for the inventory table. Declaring this column as the PRIMARY KEY places a restraint on

this column meaning no duplicate values may exist in this column and SQL will throw an error

message if an attempt is made to enter duplicate data. Since this row is set to automatically

increment each time a new record is added, we know that this column will always be a unique

value.

SQL Create Line 4:


Line 4 specifies the name and type of the second column in the inventory table. Product stands

for the inventory table product name and this column is set as a VARCHAR(50), which means it

will be able to handle numbers, letters, and special characters as values. In other words, "Any

words, numbers, or special characters can be placed into this column value, with a 50 character

limit."

The UNIQUE attribute tells SQL that this table column must be a UNIQUE value at all times.

This restraint will stop us from accidentally inserting duplicate records for the same product,

which will serve as an aid to us to help maintain data integrity.

SQL Create Line 5,6:

quantity INT,

price DECIMAL(18,2)

Now that you are more familiar with the structure of this query, lines 5 and 6 should look less

like a foreign language and more like SQL code. These lines are creating two more table

columns: quantity and price. Since the price column will be dealing with decimals, we have set

this column to a DECIMAL data type to handle decimals (sometimes called floating point

numbers).

And there you have it, here's another look at the query:

SQL Create Table Query:

USE mydatabase;

CREATE TABLE inventory

(



quantity INT,

price DECIMAL(18,2)

);

This SQL command will create a new, empty table called inventory, where we will begin to

capture store inventory data to keep track of the price and current stock of items for our make

believe online store.

At this point, this table has been created but remains empty, containing no data. Let's go ahead

and add some records into this table so that we can then use this table to further our learning of

SQL. Since we are now already familiar with the INSERT command, we can run the following

commands all at once, so feel free to copy and paste this code into the query window and

execute.

SQL Insert Into:

USE mydatabase;

INSERT INTO inventory

VALUES('19" LCD Screen','25','179.99');


VALUES('HP Printer','9','89.99');


VALUES('Pen','78','0.99');


VALUES('Stapler','3','7.99');


VALUES('Hanging Files','33','14.99');


VALUES('Laptop','16','499.99');

Successful execution of the above query should yield messages indicating that the queries have

run successfully.

SQL Results:

(1 row(s) affected)

(1 row(s) affected)

(1 row(s) affected)

(1 row(s) affected)

(1 row(s) affected)

(1 row(s) affected)

We can double-check the results by running a SELECT (*) query and doing so will retrieve all

records SQL has stored inside the inventory table.

SQL Code:

USE mydatabase;

SELECT *

FROM inventory;

SQL Results:

id product quantity price

1 19" LCD Screen 25 179.99

2 HP Printer 9 89.99

3 Pen 78 0.99

4 Stapler 3 7.99

5 Hanging Files 33 14.99

6 Laptop 16 499.99

In creating this new table with data that relates to data inside the orders table, you have

unknowingly created a relational database. We can now take a list of items ordered by our

customers and verify that these items are in stock as purchases continue to flow in, so long as we

maintain an up-to-date inventory table.

This is terrific news as you are now well on your way to take your SQL programming skills to

the next level!

SQL - Insert

To use the INSERT command, we must first have an understanding of where we would like to

insert data and what types of data we want to insert. Do we plan on inserting numbers? Strings?

Files? Let's return to the orders table we created in an earlier lesson.


SQL tables store data in rows, one row after another. The INSERT command is the command

used to insert new data (a new row) into a table by specifying a list of values to be inserted into

each table column. The arrangement of values is important, and how they are arranged in the

code corresponds to how the data values will be arranged in the the SQL table.

id - (identity, integer)

customer - (customer name, character string)

day_of_order - (date value)

product - (name of product, character string)

quantity - (quantity, integer)

Looking at the column names alone will give you an idea of what type of data each column is

expected to hold. The quantity column, for example, is expecting a number or integer of some

sort and the day_of_order column is expecting a date value to be inserted.

SQL Insert Query:

USE mydatabase;

INSERT INTO orders (customer,day_of_order,product, quantity)

VALUES('Tizag','8/1/08','Stapler',1);

SQL Insert Results:

(1 row(s) affected)

You may notice that the id column has been left out of the query statement. The reason behind

this is that when we created the orders table, we gave the id column a unique attribute called

identity. SQL handles identity columns automatically for us and therefore, we do not need to

manually insert data into this column.

The first value Tizag corresponds with the customer table column. This ensures SQL will insert

this value into the corresponding table column.

Now when we run the SELECT (*) query, SQL should return two rows with our statement

instead of only a single row.

Verification Query:

USE mydatabase;

SELECT *

FROM orders;


SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

SQL - Inserting Values

As a shortcut, you may omit the table columns entirely and only supply the values in the

INSERT statement:

SQL Insert Shortcut:

USE mydatabase;

INSERT INTO orders

VALUES('A+Maintenance','8/16/08','Hanging Files',12);

Again, we can skip the id column because SQL is able to identify that this column is an identity

column and handle it accordingly.

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1


Before moving on, let's add some more rows and execute some more INSERT queries. If you are

using SQL Express, you should be able to copy the entire code section below and execute all the

queries at once and then track the results with the verification query (SELECT * FROM orders).

SQL Inserts:

USE myDatabase;

INSERT INTO orders

VALUES('Gerald Garner','8/15/08','19" LCD Screen',3)

INSERT INTO orders

VALUES('Tizag','7/25/08','19" LCD Screen',3);

INSERT INTO orders

VALUES('Tizag','7/25/08','HP Printer',2);

Final Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1



5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

SQL - And

SQL AND links together two or more conditional statements for increased filtering when

running SQL commands. AND helps the developer query for very specific records while

answering questions like, "I want to view all orders made by a certain customer AND made on a

special date." There is no limit to the number of AND/OR conditions that can be applied to a

query utilizing the WHERE clause. This makes it possible for the developer to be as precise as

needed when querying for results.


SQL And Code:

USE mydatabase;

SELECT *

FROM orders


AND day_of_order = '08/01/08'

AND product = 'Pen';

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

This example illustrates how SQL AND combines multiple conditional statements (3 total now)

into a single condition with multiple circumstances (filters). Each filter removes rows from the

result set that doesn't meet the condition.


SQL - Or

SQL OR also applies logic to help filter results. The difference is that instead of linking together

conditional statements, an OR condition just asks SQL to look for 2 separate conditions within

the same query and return any records/rows matching either of the conditions.

SQL Or Code:

USE mydatabase;

SELECT *

FROM orders

WHERE product = 'Pen'

OR product = '19" LCD Screen';

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4


5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

The first record returned matches the first condition since the product = 'Pen'. The two records

after that match the other condition; the product in each of those orders is the '19" LCD Screen'.

This type of logic allows the developer to filter results based on one or more conditions.

SQL AND allows the developer to query for more specific data by linking together conditional

statements. On the other end of the spectrum, SQL OR creates a new, independent condition not

linked to any other conditional statement.

SQL - And / Or Combination

Conditional statements can be grouped together using parentheses (). Doing so links together

conditions and provides robust solutions for data querying.

SQL And/Or Code:

USE mydatabase;

SELECT *

FROM orders

WHERE (quantity > 2 AND customer = 'Tizag')

OR (quantity > 0 AND customer = 'Gerald Garner')

By encapsulating the first two conditions (quantity > 2 AND customer = 'Tizag') SQL now treats

this as a single condition, and the same is true for the next line. These two conditions have been

linked together with the OR operator, creating very unique behavior.

SQL is now looking for rows where the customer is Tizag AND the quantity is more than 2, and

ALSO looking for rows where the customer is Gerald Garner AND the quantity is greater than

0. All rows meeting either condition will be returned as demonstrated in our results below.

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4


5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

QL - Between

BETWEEN is a conditional statement found in the WHERE clause. It is used to query for table

rows that meet a condition falling between a specified range of numeric values. It would be used

to answer questions like, "How many orders did we receive BETWEEN July 20th and August

5th?"


SQL Select Between:

USE mydatabase;

SELECT *

FROM orders

WHERE day_of_order BETWEEN '7/20/08' AND '8/05/08';

SQL Results:



1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

BETWEEN essentially combines two conditional statements into one and simplifies the

querying process for you. To understand exactly what we mean, we could create another query

without using the BETWEEN condition and still come up with the same results, (using AND

instead).

SQL Select Between:

USE mydatabase;

SELECT *

FROM orders

WHERE day_of_order >= '7/20/08'

AND day_of_order <= '8/05/08';

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

As you can see from comparing the results of these two queries, we are able to retrieve the same

data, but you may find BETWEEN easier to use and less cumbersome than writing two different

conditional statements. In the end, the preference is really up to the individual writing the SQL

Code

SQL - Order By

ORDER BY is the SQL command used to sort rows as they are returned from a SELECT query.

SQL order by command may be added to the end of any select query and it requires at least one

table column to be specified in order for SQL to sort the results.


SQL Order by query:

USE mydatabase;

SELECT *

FROM orders


ORDER BY day_of_order;

Executing this query should offer a list of orders made by Tizag and you may noticed that the

result set has now been sorted (low to high) according to the date value. In other words, the

oldest order to the newest order.

SQL Results:


5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

SQL - Ascending Descending

The default sort order for ORDER BY is an ascending list, [a - z] for characters or [0 - 9] for

numbers. As an alternative to the default sorting for our results, which is ASCENDING (ASC),

we can instead tell SQL to order the table columns in a DESCENDING (DESC) fashion [z-a].

SQL Order by Descending:

USE mydatabase;

SELECT *

FROM orders



ORDER BY day_of_order DESC

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

If you compare these results to the results above, you should notice that we've pulled the same

information but it is now arranged in a reverse (descending) order.

SQL - Sorting on Multiple Columns

Results may be sorted on more than one column by listing multiple column names in the

ORDER BY clause, similar to how we would list column names in each SELECT statement.

SQL Order by Multiple columns:

USE mydatabase;

SELECT *

FROM orders

ORDER BY customer, day_of_order;

This query should alphabetize by customer, grouping together orders made by the same customer

and then by the purchase date. SQL sorts according to how the column names are listed in the

ORDER BY clause.

SQL Results:




5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 3

6 Tizag 2008-07-25 00:00:00.000 HP Printer 2

1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 1

SQL - Update

SQL UPDATE is the command used to update existing table rows with new data values.

UPDATE is a very powerful command in the SQL world. It has the ability to update every single

row in a database with the execution of only a single query. Due to UPDATE's supreme

authority, it is in your best interest to always include a WHERE clause when working with

UPDATE query statements. That way, you will not accidentally update more rows than you

intend to.


Execute the following UPDATE command to update the customer orders table. Since we've

provided a WHERE condition with this update command, this update will only modify rows that

match the condition and in this case it happens to be order number 1 made by Tizag. This update

should increase the quantity from 4 Pens to 6 Pens for Tizag's first order.

SQL Update Query:

USE mydatabase;

UPDATE orders

SET quantity = '6'

WHERE id = '1'

SQL Results:

(1 row(s) affected)

Let's verify our results by selecting this row from the orders table.

SQL Verification Query:

USE mydatabase;


SELECT *

FROM orders

WHERE id = '1'

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 6

The orders table now indicates that the customer Tizag will be ordering 6 Pens instead of 4. If

the WHERE condition is removed from this statement, SQL would modify every row with the

new quantity value of 6 instead of just the single row that meets the condition of id = "1". SQL

UPDATE replaces data, much like overwriting a previously saved file on a computer hard drive.

Once you click "Save," the old file is lost and replaced with the new file. Once an UPDATE

command has been executed, the old data values are lost, being overwritten by the new value.

SQL - Update Incrementing a Value

In the previous example, an order quantity was updated from 4 to 6. Say what we really wanted

to do was not necessarily change it to 6, but to add 2 to the original order quantity. Updating the

order quantity from 4 to 6 might have gotten the job done in that scenario, but that solution

doesn't scale well. In the long run, we wouldn't get very much "bang for our buck," as they say.

So, perhaps a better way to tackle the same problem would be to increment the existing value

(add 2) rather than updating with a single, static value. So, instead of setting the quantity table

column to a specific value of 6, we can send it the current table column value directly and then

add 2 to that already existing value.

SQL Update Code:

USE mydatabase;

UPDATE orders

SET quantity = (quantity + 2)

WHERE id = '1'

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 8

Executing this update statement instead of the first update query is a huge timesaver. We no

longer need to know the quantity of the order beforehand and we can add or subtract values from

it in its current state. All we need to know is that we need to add 2 more to the quantity column

to update the order correctly. This query is also more scalable, meaning we can update many

rows at once. We will do so in the next example.

SQL - Update Multiple Rows

As mentioned earlier, removing the WHERE clause from any UPDATE command is generally

not a good idea since doing so will result in SQL updating every row in the table. However, since

the intention of this next example is to update multiple rows, let's go ahead and remove the

WHERE clause from the above example.

SQL Update Multiple Rows:

USE mydatabase;

UPDATE orders

SET quantity = (quantity + 2)

SQL Results:

(6 row(s) affected)

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 10

2 Tizag 2008-08-01 00:00:00.000 Stapler 3



5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 5

6 Tizag 2008-07-25 00:00:00.000 HP Printer 4

SQL Update Multiple Values

SQL UPDATE can also be utilized to change multiple column values at once. Once again, let's

update the same order id (1) changing the quantity of products ordered. But let's also take it

another step further, by changing the quantity only when the products are Hanging Files.

SQL Update Multiple Values:

USE mydatabase;

UPDATE orders

SET quantity = '11',

Product = 'Hanging Files'

WHERE id = '1'

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Hanging Files 11

The results show that we have successfully updated an order (order id 1). Notice that after the

SET keyword, the column and value sets are listed with each column/value pair being separated

with a comma (,).

SQL - Alter

SQL ALTER is the command used to add, edit, and modify data objects like tables, databases,

and views. ALTER is the command responsible for making table column adjustments or

renaming table columns. New table columns can also be added and dropped from existing SQL

tables.


SQL Add:

USE mydatabase;

ALTER TABLE orders

ADD discount VARCHAR(10);

SQL Results:


id customer day_of_order product quantity discount

1 Tizag 2008-08-01 00:00:00.000 Pen 8 NULL

2 Tizag 2008-08-01 00:00:00.000 Stapler 3 NULL

3 A+Maintenance 2008-08-16 00:00:00.000 Hanging Files 14 NULL

4 Gerald Garner 2008-08-15 00:00:00.000 19" LCD Screen 5 NULL

5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 5 NULL

6 Tizag 2008-07-25 00:00:00.000 HP Printer 4 NULL

As you can see from the results panel, SQL has added an additional column, discount, to the

orders table. Since this column was just created, it contains no data, and only NULL values have

been returned.

SQL - Alter Table: Modify Column

SQL table columns can be altered and changed using the MODIFY COLUMN command. This

allows the developer the opportunity to mold table columns or adjust settings as needed.

SQL Modify Column:

USE mydatabase;

ALTER TABLE orders

ALTER COLUMN discount DECIMAL(18,2);

Above, we have modified the new discount table column changing the column data type from a

varchar to a decimal table column. This example can be expanded to modify table columns as

needed by the developer.

SQL - SQL Alter Table: Drop

This column can be deleted using the SQL DROP command. Once this column has been

dropped, however, the data stored inside of it will be lost forever. Proceed with caution!

SQL Drop Column Code:

USE mydatabase;

ALTER TABLE orders

DROP COLUMN discount;

SQL - Distinct

SQL SELECT DISTINCT is a very useful way to eliminate retrieving duplicate data reserved

for very specific situations. To understand when to use the DISTINCT command, let's look at a

real world example where this tool will certainly come in handy.


If you've been following along in the tutorial, we have created an orders table with some data

inside that represents different orders made by some of our very loyal customers over a given

time period. Let's pretend that we have just heard word from our preferred shipping agent that

orders made in August require no shipping charges, and we now have to notify our customers.

We do not want to send mailers to all of our customers, just the ones that have placed orders in

August. Also, we want to avoid retrieving duplicate customers as our customers may have placed

more than one order during the month of August.

We can write a very simple SQL query to extract this information from the orders table:

SQL Select Distinct:

USE mydatabase;

SELECT DISTINCT customer

FROM orders

WHERE day_of_order BETWEEN '7/31/08' AND '9/1/08';

SQL Results:

customer

A+Maintenance

Gerald Garner

Tizag

Running this query yields a list of all the customer's affected by our unexpected news from the

shipping agency. With this list, we can now go about contacting each of these customers and

informing them of the good news without worrying about contacting the same customer multiple

times.


SQL - Subqueries

Subqueries are query statements tucked inside of query statements. Like the order of operations

from your high school Algebra class, order of operations also come into play when you start to

embed SQL commands inside of other SQL commands (subqueries). Let's take a look at a real

world example involving the orders table and figure out how to select only the most recent

order(s) in our orders table.


To accomplish this, we are first going to introduce a built-in SQL function, MAX(). This

function wraps around a table column and quickly returns the current highest (max) value for the

specified column. We are going to use this function to return the current "highest", aka most

recent date value in the orders table.

SQL Subquery Preview:

USE mydatabase;

SELECT MAX(day_of_order)

FROM orders

SQL Results:

day_of_order

2008-08-16 00:00:00.000

Now we can throw this query into the WHERE clause of another SELECT query and obtain the

results to our little dilemma.

SQL Select Subquery Code:

USE mydatabase;

SELECT *

FROM orders

WHERE day_of_order = (SELECT MAX(day_of_order) FROM orders)

:




This query is a dynamic query as it pulls current information and will change if a new order is

placed. Utilizing a subquery we were able to build a dynamic and robust solution for providing

us with current order information.

SQL - Join

SQL JOIN joins together two tables on a matching table column, ultimately forming one single

temporary table. The key word here is temporary. The tables themselves remain intact, and

running a JOIN query does not in any way change the data or table structure. JOIN is another

way to select specific data from two or more relational tables.


In order to perform a JOIN query, we need a few pieces of information: the name of the table

and table column we want to join on and a condition to meet for the JOIN to happen. This

should sound a little confusing as there is much going on in a JOIN query, so let's take a look at

an example:

SQL Join Query Code:

USE mydatabase;

SELECT *

FROM orders

JOIN inventory

ON orders.product = inventory.product;

SQL Join Results:

id customer day_of_order product quantity id product quantity price

1 Tizag 2008-08-01

00:00:00.000 Hanging Files 11 5 Hanging Files 33 14.99

2 Tizag 2008-08-01

00:00:00.000 Stapler 3 4 Stapler 3 7.99

3 A+Maintenance 2008-08-16



4 Gerald Garner 2008-08-15

00:00:00.000

19" LCD

Screen 5 1

19" LCD

Screen 25 179.99

5 Tizag 2008-07-25

00:00:00.000

19" LCD

Screen 5 1

19" LCD

Screen 25 179.99

6 Tizag 2008-07-25

00:00:00.000 HP Printer 4 2 HP Printer 9 89.99

The line beginning with JOIN (Line 4) is where we tell SQL which table we would like to join.

The next line (Line 5) is a different story. Here is where we have specified the condition to JOIN

ON. In this case, both tables have identical product columns which makes them an ideal target

for a join. Basically we are temporarily merging the tables connecting them where they match,

the product column.

This type of join matches values from one table column with a corresponding value in another

table and uses that match to merge the tables together. In our make-believe store world, this let's

us join the inventory table with the orders table to show us all the items we currently have in

stock for our customers and also the price of each item.

Let's rework this query a bit and strip away a few of the table columns to make our results easier

to read and understand. We will replace the (*) parameter with a list containing only the table

columns we are interested in viewing.

SQL Join:

USE mydatabase;

SELECT orders.customer,

orders.day_of_order,

orders.product,

orders.quantity as number_ordered,

inventory.quantity as number_instock,

inventory.price

FROM orders

JOIN inventory

ON orders.product = inventory.product

SQL Results:

customer day_of_order product number_ordered number_instock price

Tizag 2008-08-01 00:00:00.000 Hanging Files 11 33 14.99

Tizag 2008-08-01 00:00:00.000 Stapler 3 3 7.99

A+Maintenance 2008-08-16 00:00:00.000 Hanging Files 14 33 14.99

Gerald Garner 2008-08-15 00:00:00.000 19" LCD Screen 5 25 179.99

Tizag 2008-07-25 00:00:00.000 19" LCD Screen 5 25 179.99

Tizag 2008-07-25 00:00:00.000 HP Printer 4 9 89.99

Since we have one column in each table named the same thing (quantity), we used AS to modify

how these columns would be named when our results were returned. These results should be

more satisfying and easier to read now that we have removed some of the unnecessary columns.

SQL - Right Join

RIGHT JOIN is another method of JOIN we can use to join together tables, but its behavior is

slightly different. We still need to join the tables together based on a conditional statement. The

difference is that instead of returning ONLY rows where a join occurs, SQL will list EVERY row

that exists on the right side, (The JOINED table).

SQL - Right Join:

USE mydatabase;

SELECT *

FROM orders

RIGHT JOIN inventory


SQL Results:

id customer day_of_order product quantity id product quantity price

4 Gerald Garner 2008-08-15

00:00:00.000

19" LCD

Screen 5 1

19" LCD

Screen 25 179.99

5 Tizag 2008-07-25

00:00:00.000

19" LCD

Screen 5 1

19" LCD

Screen 25 179.99

6 Tizag 2008-07-25 HP Printer 4 2 HP Printer 9 89.99

00:00:00.000

NULL NULL NULL NULL NULL 3 Pen 78 0.99

2 Tizag 2008-08-01

00:00:00.000 Stapler 3 4 Stapler 3 7.99

1 Tizag 2008-08-01


3 A+Maintenance 2008-08-16


NULL NULL NULL NULL NULL 6 Laptop 16 499.99

You should see a new row at the bottom of the results box with a bunch of NULL values. This is

a result of the RIGHT JOIN and is the intended result from running the query. We end up with

an extra row because inside of the inventory table, the Laptop item was not joined with a product

from the orders table. This just means that we have not sold a laptop as of yet and it shouldn't be

much a surprise since we already know from querying the orders table in previous lessons that

there have been no laptop orders so far.

By specifying RIGHT JOIN, we have told SQL to join together the tables even if no matches are

found in the conditional statement. All records that exist in the table on the right side of the

conditional statement (ON orders.product = inventory.product) will be returned and NULL

values will be placed on the left if no matches are found.

SQL - Left Join

SQL LEFT JOIN works exactly the same way as RIGHT JOIN except that they are opposites.

NULL values will appear on the right instead of the left and all rows from the table on the left

hand side of the conditional will be returned.

Unfortunately, we will not be able to show a very intuitive example of a LEFT JOIN because of

how our tables are structured. The orders table should always have a matching inventory item

and if not, that means we are in big trouble as we could be selling items we do not carry in

inventory. For good measure, here's what a LEFT JOIN would look like:

SQL Left Join:

USE mydatabase;

SELECT *

FROM orders

LEFT JOIN inventory


SQL JOIN is intended to bring together data from two tables to form a single larger table, and

often, it will paint a more detailed picture of what the data represents. By merging these two data

sets, we were able to peer into our database and ensure that each item ordered so far is in stock

and ready to be shipped to our customers.

SQL - In

SQL IN is an operator used to pull data matching a list of values. A scenario where this proves

useful would be if we wanted to retrieve customer data for two or more customers. We can use

the IN operator to specify a list of customer names, and SQL will retrieve rows reflecting every

customer in the list.


Inside the query statement itself, the word "IN" replaces the (=) operator after the WHERE

declarative and slightly alters the meaning as well. Instead of listing a single value, you may list

multiple values and SQL will retrieve the results for each value listed.

SQL In:

USE mydatabase;

SELECT *

FROM orders

WHERE customer IN ('Gerald Garner','A+Maintenance');

SQL Results:




The results provide a list of all customer orders made by each of the customer names we have

listed inside the IN clause ('Gerald Garner','A+Maintenance'). This is a great way to query for all

orders made by a handful of different customers as we can see everything these particular

customers have ordered thus far.


The real power of this condition comes to life when used with a subquery that retrieves a list of

values. Running any SELECT query returns results in list format. And as we mentioned just a

few short moments ago, this list can then be passed as a list for the IN clause using a subquery.

Let's adjust the previous example to only retrieve only the products column, as opposed to

retrieving all columns (*).

SQL In:

USE mydatabase;

SELECT product

FROM orders

WHERE customer IN ('Gerald Garner','A+Maintenance');

Results:

product

Hanging Files

19" LCD Screen

Our results represent a query run to achieve a list of products sold to two of our customers. Now

let's convert this query to a subquery and use this query as an input list to check the inventory

table to see if we have any of these items in stock.

SQL In:

USE mydatabase;

SELECT *

FROM inventory

WHERE product in

(SELECT product

FROM orders

WHERE customer IN ('Gerald Garner','A+Maintenance'));

SQL Results:

id product inventory price

1 19" LCD Screen 25 179.99


By specifying a sub query as our list of values we were able to take advantage of the relationship

our tables have with each other and create a very dynamic query. This query saves us the time of

scrolling through the entire inventory table and checking the stock of each item purchased by any

of our recent customers.

SQL - Not In

SQL NOT IN, as you may have guessed, allows the developer to eliminate a list of specific

values from the result set.

SQL Not In:

USE mydatabase;

SELECT *

FROM inventory

WHERE product NOT IN

(SELECT product

FROM orders

WHERE customer IN ('Gerald Garner','A+Maintenance'));

SQL Results:



3 Pen 78 0.99

4 Stapler 3 7.99

6 Laptop 16 499.99

SQL - Case

SQL CASE is a very unique conditional statement providing if/then/else logic for any ordinary

SQL command, such as SELECT or UPDATE. It then provides when-then-else functionality

(WHEN this condition is met THEN do_this).


This functionality provides the developer the ability to manipulate the presentation of the data

without actually updating or changing the data as it exists inside the SQL table.

SQL Select Case Code:

USE mydatabase;

SELECT product,

'Status' = CASE

WHEN quantity > 0 THEN 'in stock'

ELSE 'out of stock'

END

FROM dbo.inventory;

SQL Results:

product Status

19" LCD Screen in stock

HP Printer in stock

Pen in stock

Stapler in stock

Hanging Files in stock

Laptop in stock

Using the CASE command, we've successfully masked the actual value of the product inventory

without actually altering any data. This would be a great way to implement some feature in an

online catalog to allow users to check the status of items without disclosing the actual amount of

inventory the store currently has in stock.

SQL - Case: Real World Example

As a store owner, there might be a time when you would like to offer sale prices for products.

This is a perfect opportunity to write a CASE query and alter the inventory sale prices at the

presentation level rather than actually changing the price inside of the inventory table. CASE

provides a way for the store owner to mask the data but still present it in a useful format.


Let's back up a second and pull a listing of our recent orders and join this with the inventory

table so that the results contain both the quantity of items purchased and the price from the

inventory table. To accomplish this we will need to first write a SQL JOIN query.

SQL Join Query:

USE mydatabase;

SELECT dbo.orders.id,

dbo.orders.customer,

dbo.orders.quantity,

dbo.inventory.product,

dbo.inventory.price

FROM orders

JOIN inventory


In order to provide results that are much clearer, we've moved away from selecting every column

with (*). Instead, we've listed each column that will be of use for the next few steps. Also, let's

plan on offering a 25% off sale on these items.

SQL Results:

id customer quantity product price

1 Tizag 11 Hanging Files 14.99

2 Tizag 3 Stapler 7.99

3 A+Maintenance 14 Hanging Files 14.99

4 Gerald Garner 5 19" LCD Screen 179.99

5 Tizag 5 19" LCD Screen 179.99

6 Tizag 4 HP Printer 89.99

Next we need to look at reducing the prices of the items according to our sale price. For the

purpose of this exercise, let's offer a 25% discount on all our currently pending orders using a

SQL CASE query.

SQL Select Case Code:

USE mydatabase;





dbo.inventory.price,

'SALE_PRICE' = CASE

WHEN price > 0 THEN (price * .75)

END

FROM orders

JOIN inventory


Multiplying the current price by .75 reduces the price by approximately 25%, successfully

applying the changes we would like to see but doing so without actually changing any data.

SQL Results:

id customer quantity product price SALE_PRICE

1 Tizag 11 Hanging Files 14.99 11.2425

2 Tizag 3 Stapler 7.99 5.9925

3 A+Maintenance 14 Hanging Files 14.99 11.2425

4 Gerald Garner 5 19" LCD Screen 179.99 134.9925

5 Tizag 5 19" LCD Screen 179.99 134.9925

6 Tizag 4 HP Printer 89.99 67.4925

The results speak for themselves as the records returned indicate a new table column with the

calculated sales price now listed at the end of each row.

Since SQL CASE offers a conditional statement (price > 0), it wouldn't take much more effort to

create some conditional statements based on how many products each customer had ordered and

offer different discounts based on the volume of a customer order.

For instance, as a web-company, maybe we would like to offer an additional 10% discount to

orders totaling more than $100. We could accomplish this in a very similar fashion.

SQL Results:

USE mydatabase;





dbo.inventory.price,

'SALE_PRICE' = CASE

WHEN (orders.quantity * price) > 100 THEN (price * .65)

ELSE (price * .75)

END

FROM orders

JOIN inventory


:

id customer quantity product price SALE_PRICE

1 Tizag 11 Hanging Files 14.99 9.7435

2 Tizag 3 Stapler 7.99 5.9925

3 A+Maintenance 14 Hanging Files 14.99 9.7435

4 Gerald Garner 5 19" LCD Screen 116.9935 134.9925

5 Tizag 5 19" LCD Screen 179.99 116.9935

6 Tizag 4 HP Printer 89.99 58.4935

With this query, we have now successfully reduced all orders by 25% and also applied an

additional 10% discount to any order totaling over $100.00.

In each of the examples above, SQL CASE has been utilized to perform presentation level

adjustments on data values and its versatility provides limitless results.

SQL - Group By

SQL GROUP BY aggregates (consolidates and calculates) column values into a single record

value. GROUP BY requires a list of table columns on which to run the calculations. At first, this

behavior will resemble the SELECT DISTINCT command we toyed with earlier.


SQL Group By:


USE mydatabase;

SELECT customer

FROM orders

GROUP BY customer;

SQL Results:

customer

A+Maintenance

Gerald Garner

Tizag

Here, SQL has consolidated like values and returned those that are unique. In this case, we have

actually duplicated the behavior of SELECT DISTINCT, but you have also seen firsthand how

GROUP BY accepts a table column as a list and consolidates like customer values.

To unleash the true power of GROUP BY, it is necessary to include at least one mathematical

(aggregate) function, and to do so we will utilize the SUM() function to calculate how many total

items have been purchased by each of our customers.

SQL Code:

USE mydatabase;

SELECT customer, SUM(quantity) AS "Total Items"

FROM orders

GROUP BY customer;

SQL Results:

customer Total Items

A+Maintenance 14

Gerald Garner 5

Tizag 23

With the addition of the aggregate SUM() function, we've let SQL calculate how many products

have been ordered by each customer and returned them for viewing with a single query

statement.

Taking a look at another example, we can also figure out how many of each product was ordered

with the use of a single query statement.

SQL Code:

USE mydatabase;

SELECT product, SUM(quantity) AS "Total Items"

FROM orders

GROUP BY product;

SQL Results:

product Total Items

19" LCD Screen 10

Hanging Files 25

HP Printer 4

Stapler 3

GROUP BY would also be a great way to calculate how much total cash of our customers has

spent. Let's take a look at what that query may look like.

SQL Code:

USE mydatabase;

SELECT customer,

SUM((orders.quantity * inventory.price)) AS "COST"

FROM orders

JOIN inventory


GROUP BY customer;

SQL Results:

product COST

A+Maintenance 209.86

Gerals Garner 899.95

Tizag 1448.77

SQL - Grouping By Multiple Columns

Like the ORDER BY clause, GROUP BY can accept a list of table columns on which to group

by.

SQL Code:

USE mydatabase;

SELECT day_of_order,

product,

SUM(quantity) as "Total"

FROM orders

GROUP BY day_of_order,product


SQL Results:

day_of_order product Total

2008-07-25 00:00:00.000 19" LCD Screen 5

2008-07-25 00:00:00.000 HP Printer 4

2008-08-01 00:00:00.000 Hanging Files 11

2008-08-01 00:00:00.000 Stapler 3

2008-08-15 00:00:00.000 19" LCD Screen 5

2008-08-16 00:00:00.000 Hanging Files 14

This query will group together and sum the total number of products purchased on any given

date, regardless of what customer has purchased the item. It's a very useful query to keep in

mind.

SQL - Having

The SQL HAVING clause is "like a WHERE clause for aggregated data." It's used with

conditional statements, just like WHERE, to filter results. One thing to note is that any column

name appearing in the HAVING clause must also appear in the GROUP BY clause.

SQL Having:

USE mydatabase;

SELECT day_of_order,

product,

SUM(quantity) as "Total"

FROM orders

GROUP BY day_of_order,product,quantity

HAVING quantity > 7


SQL Results:

day_of_order product Total

2008-08-01 00:00:00.000 Hanging Files 11

2008-08-16 00:00:00.000 Hanging Files 14

The quantity column is now considered aggregated in SQL terms, because its values have been

summed together using the SUM() function. In the example above, HAVING acts as the

WHERE clause for aggregate values, filtering out results that do not meet the condition (quantity

> 7).

SQL - Views

SQL VIEWS are data objects, and like SQL Tables, they can be queried, updated, and dropped.

A SQL VIEW is a virtual table containing columns and rows except that the data contained

inside a view is generated dynamically from SQL tables and does not physically exist inside the

view itself.



SQL Create View Code:

CREATE VIEW virtualInventory

AS

SELECT * FROM inventory;

With a successful execution of this query, we have now created a view data object of the

inventory table. The virtualInventory view is considered a data object (like a table) and is now

accessible to us the developer. Views can be queried exactly like any other SQL table.

SQL View Code:

USE mydatabase;

SELECT *

FROM virtualInventory;

SQL Results:


1 19" LCD Screen 25 179.99


3 Pen 78 0.99

4 Stapler 3 7.99


6 Laptop 16 499.99

Even though a SQL VIEW is treated like a data object in SQL, no data is actually stored inside

of the view itself. The view is essentially a dynamic SELECT query, and if any changes are

made to the originating table(s), these changes will be reflected in the SQL VIEW automatically.

SQL Code:

USE mydatabase;

UPDATE inventory

SET price = '1.29'

WHERE product = 'Pen';

Execute the following query to verify the results:

SQL Verification Query Code:

USE mydatabase;

SELECT *

FROM virtualInventory

WHERE product = 'Pen';

SQL Results:


3 Pen 78 1.29

SQL - Drop View

Views can also be removed by using the DROP VIEW command.

SQL Drop View:

USE mydatabase;

DROP VIEW virtualInventory;

SQL - Dates

Date values are stored in date table columns in the form of a timestamp. A SQL timestamp is a

record containing date/time data, such as the month, day, year, hour, and minutes/seconds. It's

not much different from the standard date format.


Date Columns:

Column Type Format

time HH:MM:SS


date YYYY-MM-DD

datetime YYYY-MM-DD HH:MM:SS

Date values are stored in the form of a timestamp, and SQL offers a built-in function called

GETDATE() that returns the current date in the form of a SQL timestamp.

SQL SELECT GETDATE():

USE mydatabase;

SELECT GETDATE();

Timestamp Result:

2004-06-22 10:33:11.840

SQL expects dates to be formatted as above but does offer some flexibility when working with

dates inside query statements. For instance, date values do not necessarily need to contain the

hour, minutes, and seconds values. SQL also accepts most traditional date formats such as

"MM/DD/YY" (ex: "01/01/06").

Using a built in function, ISDATE() we can do some testing on date values to see if they meet

the formatting requirements.

SQL Code:

USE mydatabase;

SELECT

ISDATE('8/24/08') AS "MM/DD/YY",

ISDATE('2004-12-01') AS "YYYY/MM/DD";

ISDATE() returns a 1 or a 0 indicating a true or false result. In this case, both formats are

acceptable date formats as a 1 value was returned.

SQL - Month(), Day(), Year()

The Month(), Day() and Year() functions all extract corresponding values from a given date.

SQL Year():

USE mydatabase;

SELECT YEAR(GETDATE()) as "Year";

SELECT YEAR('8/14/04') as "Year";

SQL Month():

USE mydatabase;

SELECT MONTH(GETDATE()) as "Month";

SELECT MONTH('8/14/04') as "Month";

SQL Day():

USE mydatabase;

SELECT DAY(GETDATE()) as "Day";

SELECT DAY('8/14/04') as "Day";

Understanding timestamps and extracting pieces of dates is the first step in being able to perform

date calculations and work more in-depth with SQL Dates.

SQL - Datepart

DATEPART() is a SQL function used to extract all kinds of date information from timestamps,

and it is a function that is unique to Microsoft's SQL Server Application.


SQL Datepart:

USE mydatabase;

SELECT DATEPART(year, '2007-06-01') AS "Year";

SQL Results:

Year

2007

DATEPART() requires 2 parameters separated by a comma (,). The first parameter specifies

what type of date data will be extracted, and the second parameter is a timestamp value.


SQL Datepart:

USE mydatabase;

SELECT DATEPART(year, '2007-06-01') AS "Year",

DATEPART(month, '2007-06-01') AS "Month",

DATEPART(day, '2007-06-01') AS "Day",

DATEPART(dayofyear, '2007-06-01') AS "DayofYear",

DATEPART(weekday, '2007-06-01') AS "Weekday";

SQL Results:

Year Month Day DayofYear Weekday

2007 6 1 152 6

Datepart Abbreviation Chart:

DatePart Abbreviation Example

year yy, yyyy DATEPART(yy, getdate())

quarter qq, q DATEPART(qq, getdate())

month mm, m DATEPART(mm, getdate())

dayofyear dy, y DATEPART(dy, getdate())

day dd, d DATEPART(dd, getdate())

week wk, ww DATEPART(wk, getdate())

weekday dw DATEPART(dw, getdate())

hour hh DATEPART(hh, getdate())

minute mi DATEPART(mi, getdate())

second ss DATEPART(ss, getdate())

millisecond ms DATEPART(ms, getdate())

SQL - DateAdd()

DATEADD() is the SQL function used to add and increment date values. Hours, minutes,

months, and days can be added to any date value. In fact, dates can be added based on any type

of date part discussed in the SQL DATEPART() lesson.


SQL Code:

USE mydatabase;

SELECT DATEADD(year, 1, getdate()) AS "+1 Year";

SQL Results:

+1 Year

2009-06-31 00:00:00.000

This example shows how to use DATEADD() to take a specified date value and increment it by

the 'year' date part. By replacing the middle parameter with a negative value, we can utilize the

same DATEADD() function to subtract dates as well.

SQL Code:

USE mydatabase;

SELECT DATEADD(day,-1, '2006-06-01') AS "-1 Day";

SQL Results:

-1 Day

2006-05-31 00:00:00.000

In each example, SQL is able to perform a calculation on each date value based on a timestamp,

and after the calculation, a timestamp value returned. Also note that the date parameter can be

based on another SQL function or the result of a subquery.

SQL Code:



USE mydatabase;

SELECT DATEADD(day,-30, (SELECT MAX(day_of_order) FROM orders)) AS "-30

Days";

SQL Results:

-30 Days

2008-07-17 00:00:00.000

Here we have now constructed a very useful, dynamic statement pulling the most current order

(MAX) in the orders table, and we've been able to subtract one day from that value. While this

information does not directly prove useful, if we take this query one step further and place this

statement in a WHERE as a subquery, we should be more satisfied with the results.

SQL Code:

USE mydatabase;

SELECT *

FROM orders

WHERE day_of_order >

(SELECT DATEADD(day,-30, (SELECT MAX(day_of_order) FROM orders)) AS "-30

Days");

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Hanging Files 11

2 Tizag 2008-08-01 00:00:00.000 Stapler 3



5 Tizag 2008-07-25 00:00:00.000 19" LCD Screen 5

6 Tizag 2008-07-25 00:00:00.000 HP Printer 4

By placing this calculated date in the WHERE clause, we were able to pull all the records that

have happened within 30 days of the most recent order (2008-07-17 00:00:00.000). We are able

to query the orders table and request this information with a dynamic query that will yield

different results as new orders are placed and time goes by.

SQL - Delete Command(s)

In the SQL world, databases, rows, and columns all have one thing in common: once a DELETE

statement has been executed successfully against them, the data they once contained is lost

forever! Be very careful with these commands and be sure to properly backup all data before

proceeding with any type of DELETE command(s).


SQL offers several ways to tackle data deletion. Here are the differences.

SQL Delete Commands:

DELETE - Deletes any number of rows from a data object.

DROP - Removes table columns, tables, and all data objects SQL applications.

TRUNCATE - Empties out data without removing the object itself.

SQL - Delete

DELETE queries work much like UPDATE queries and like UPDATE, it is much advised to

always use a WHERE condition when running any delete query or else you risk deleting too

much data.

SQL Delete Query:

USE mydatabase;

DELETE

FROM orders

WHERE customer = 'A+Maintenance';

SQL Results:

1 Row(s) affected

SQL - Truncate


SQL TRUNCATE is the fastest way to remove all data from a SQL table, leaving nothing but an

empty shell. You might choose to use this command when all the data inside of a table needs to

be removed but you'd like the table column definitions to remain intact.

SQL Truncate Table Code:

USE mydatabase;

TRUNCATE TABLE orders;

NOTE: Executing the command above will empty your table data and you will lose this data

forever! If you plan on following along do not execute this query.

SQL - Drop

SQL DROP is another command that removes data from the data store. The DROP command

must be performed on SQL objects including databases, tables, table columns, and SQL views.

Dropping any of these objects removes them completely from your SQL application and all data

contained in any of the data objects dropped are lost forever.

SQL Drop Examples:

USE mydatabase;

DROP TABLE orders;

DROP DATABASE mydatabase;

DROP VIEW viewname;

DROP INDEX orders.indexname;

-- FOR USE WITH ALTER COMMANDS

DROP COLUMN column_name

DROP FOREIGN KEY (foreign_key_name)

The above example also includes the syntax to drop table columns and foreign keys. These items

are outlined in the SQL ALTER lesson.

SQL - Union

SQL UNION combines two separate SQL queries into one result set. A JOIN statement adds

additional table columns to a result set (horizontally), UNION combines row results from one

table with rows of another table (vertically).




In order to perform a UNION the columns of table 1 must match those of table 2. This rule

ensures that the result set is consistent as rows are fetched by SQL.

For these next exercises we suggest creating two different tables that are identical in structure but

contain unique rows of data. We challenge you to do this by reviewing the SQL Create queries

and modifying them to create two brand new employee tables.

SQL Select Union Code:

USE mydatabase;

SELECT * FROM employees

UNION

SELECT * FROM employees2;

SQL Table:

ID Lastname Firstname Title

1 Johnson David crew

2 Hively Jessica crew

9 Hicks Freddy crew

10 Harris Joel crew

11 Davis Julie manager

101 Yazzow Jim crew

102 Anderson Craig crew

103 Carlson Kevin crew

104 Maines Brad crew

The result is a complete listing of every employee from the two tables, perhaps representing a list

of employees from two different departments.

The next example shows a more practical means of using a union clause. Here we will select all

of our employees from both tables and join them with our invoices table to generate a complete

list of sales from both stores on a given day.


SQL Code:

SELECT employees.Lastname, employees.Firstname, invoices.Sale, invoices.Price

FROM employees

INNER JOIN invoices

ON employees.id = invoices.EmployeeID

UNION

SELECT employees2.Lastname, employees2.Firstname, invoices.Sale,

invoices.Price

FROM employees2

INNER JOIN invoices

ON employees2.id = invoices.EmployeeID;

SQL Table:

Lastname Firstname Sale Price

Johnson David HOT DOG 1.99

Hively Jessica LG SFT DRK 1.49

Davis Julie CK SLD 3.99

Yazzow Jim HOT DOG 1.99

Carlson Kevin LG SFT DRK 1.49

Here we combined a join query with the union clause to create one table.

SQL - Union All

UNION ALL selects all rows from each table and combines them into a single table. The

difference between UNION and UNION ALL is that UNION ALL will not eliminate duplicate

rows. Instead, it just pulls all rows from all tables fitting your query specifics and combines them

into a table.

SQL Code:

SELECT * FROM employees

UNION ALL

SELECT * FROM employees2;

SQL Table:

ID Lastname Firstname Title

1 Johnson David crew

2 Hively Jessica crew

9 Hicks Freddy crew

10 Harris Joel crew


101 Yazzow Jim crew

102 Anderson Craig crew

103 Carlson Kevin crew


104 Maines Brad crew

SQL Code:

SELECT employees.Lastname, employees.Firstname, invoices.Sale, invoices.Price

FROM employees

INNER JOIN invoices

ON employees.id = invoices.EmployeeID

UNION ALL

SELECT employees2.Lastname, employees2.Firstname, invoices.Sale,

invoices.Price

FROM employees2

INNER JOIN invoices

ON employees2.id = invoices.EmployeeID;

SQL Table:

Lastname Firstname Sale Price

Johnson David HOT DOG 1.99

Hively Jessica LG SFT DRK 1.49

Davis Julie CK SLD 3.99


Yazzow Jim HOT DOG 1.99

Carlson Kevin LG SFT DRK 1.49



SQL - Syntax - (Speaking SQL)

Syntax, by definition, means the study of linguistic rules and patterns. Every programming

language, including SQL, must follow a unique set of guidelines termed syntax. Punctuation,

spaces, mathematical operators, and special characters have special meaning when used inside of

SQL commands and query statements. For example, each and every SQL command will end

with a semi colon (;).


Executing SQL commands that do not have proper syntax and formatting will result in a syntax

error. Syntax errors might be the most common and first error messages new SQL developers

will experience.

Let's now take a look at a very simple SQL command that will be used in just about every

example contained in this tutorial from here on out.

Sample SQL Command:

use mydatabase;

This command identifies a database as a target database, meaning that any SQL command or

query executed after this line will be run against the identified database. In this case, the database

'mydatabase' will be the target database. This is a good way to prevent mistakes and avoid

potential data loss and a good reason to include this command into each and every authored SQL

query.

SQL - Syntax: Capitalization and Spacing


In some programming languages, capitalizing commands or excessive spacing may or may not

cause syntax code errors and cause the command to fail. SQL syntax is very loose when it comes

to capitalization and spacing, allowing a lot of room for the developer to decide on his/her own

preference in regards to capitalization and spacing.

Let's rewrite the same SQL command from the previous example and take advantage of SQL's

loose syntax characteristics.

Sample SQL Command:

USE

mydatabase;

The example above, though it does look different due to the capitalization and spacing, will yield

the same results as the first example.

SQL - Syntax: Building good habits

While coding in any language, it is important to develop good, consistent habits and maintain

clean code. Clean code allows another SQL developer to step right in where you have left off

without missing a beat. A developer with diligent coding habits will prevent many syntax errors

before executing his/her scripts and also will be able to detect possibly syntax problems before

they cause problems in a SQL Command.

Good habits include:

Consitency

Clean and Concise

Use of Comments (more on this later)

Scalability

Coding in any language is as much of an art form as authoring best selling novels and stories.

Take pride in doing so and always do your best to follow good coding habits.

SQL - Data Types

SQL data takes shape in several different forms, including character strings, numbers, file stores,

and dates. SQL developers call the shots as to what types of data will be stored inside each and

every table column when creating a SQL table. The developer must specify the column type of

each new SQL table column.



Column types are synonymous with data types as the column type is what designates the type of

data that will be stored inside the column. In other words, a SQL data type is a label and a

guideline for SQL to understand what type of data is expected inside of each table column and

this identifies how SQL will interact with the stored data. Below, we will give you an overview

on the types of data that can be stored within a SQL table.

SQL - Numbers, Decimals, and Dates

Data Types:

Integers - (3, -17)

Point(Decimal) - (3.23415)

Date - (2004-06-22 10:33:11.840)

Storing numbers and decimals allows the developer to collect statistical data and create reports

based on the data contained inside the table. SQL can even perform mathematical calculations

against numeric data, providing endless number-crunching abilities.

In SQL, decimals are often referred to as point or floating-point numbers. These data types are

slightly different from the normal 'integer' data types.

For the most part, date values are treated like numbers and they can even be added together and

subtracted offering the developer the option to add days, months, or years together to create new

dates (more on this later). Additionally, specific data can be extracted from date values, allowing

the developer to pull specific date information from a date value like only the month number, the

year, or the day of the week.

SQL - Boolean Data

("TRUE" / "FALSE")

( 1 / 0 )

Boolean values are true/false types of data. A Boolean table column will contain either string

values of "True" and "False" or the numeric equivalent representation, with 0 being false and 1

being true.

SQL - Character Strings

Character Strings:

VARCHAR - ('Words or numbers')

Text - ('Once upon a time...')

Strings range from a single word or character to large blocks of text including multiple

paragraphs and unique symbols. Set the table column type to VARCHAR or Text in order to

incorporate string data types into SQL tables.

SQL Server Table Column Types:

bigint Integer value (-9,223,372,036,854,775,808 -

9,223,372,036,854,775,807) 2^63

int smaller Integer value (-2,147,483,648) - (2,147,483,647) 2^31

smallint smaller Integer value (-32,768) - (32,767) 2^15

tinyint smaller Integer values 0 - 255 2^8

bit Integer data value (either 1 or 0 value) 1 or 0

decimal Decimal values from -10^38 - 10^38 10^38

numeric Decimal values from -10^38 - 10^38 10^38

money Money values (-922,337,203,685,477.5808) -

(922,337,203,685,477.5807) 2^63

smallmoney Smaller Money Values (-214,748.3648) - (214,748.3647) 2^31

datetime Date value (January 1, 1753) - (December 31, 9999)

smalldatetime Smaller Date Value (January 1, 1900) - (June 6, 2079)

timestamp Unique Number Value (updates when row is updated)

char Character String Value (max 8,000 characters)

varchar Character String Value maximum of 8,000 characters, unless otherwise

noted)

nchar Character String Value (max 4,000 characters)

nvarchar Character String Value (max 4,000 characters)

text Character String Value (max 2,147,483,647 characters) 2^31

ntext Character String Value (max 1,073,741,823 characters) 2^30

binary Binary Value (max 8,000 bytes)

varbinary Binary Value (max 8,000 bytes)

image Binary Value (max 2,147,483,647 bytes) 2^31

uniqueidentifier Global Unique ID (GUID)

SQL - Defaults and Null Values

NULL values are 'nothing' values. When a value is null, it means the value is empty and contains

no value -- not even '0'. NULLs are unique data types that are usually the default setting for all

table columns. When a SQL developer runs across a NULL value in a database, it is generally an

indication that this value is either new or has not been modified.

The SQL developer may specify to allow or disallow the NULL values eliminating the

possibility of running across 'empty' table columns when creating a SQL table. If the developer

chooses not to allow NULL values he/she may specify a custom default value instead of the

NULL (nothing) value. Primary Key table columns do not allow NULL values since this

column's sole purpose is to be the unique identifier for a table column. Having a NULL unique

identifier would be similar to having a car license plate that is blank.

By default, NULL values are allowed on all newly created table columns meaning a table

column is allowed to be 'empty', except primary key columns. A NULL value is a special type of

value that can be tested for by most programming languages including SQL and can provide the

developer a means to 'test' and see if data exists or has been modified. As a new programmer you

may not fully understand the benefits a NULL value can bring, but with experience, you will

learn to hate/appreciate them.

SQL - Expressions

SQL Expressions are the pieces of a SQL query that compare values against other values or

perform arithmetic calculations. Expressions can be found inside of any SQL command usually

in the form of a conditional statement. In the SQL world, conditional statements and

expressions test or compare values against other values.


SQL - Boolean Expressions

Boolean expressions return rows (results) when a single value is matched.

SQL Boolean Expression:

USE mydatabase;

SELECT * FROM orders WHERE id = '1';

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

SQL - Numeric Expression

Numeric Expressions return a single numeric value instead of an entire row and usually perform

calculations.


SQL Code:

USE mydatabase;

SELECT 15 + 4;

SQL Code:

USE mydatabase;

SELECT (15 / 5) * 10;

SQL Code:

USE mydatabase;

SELECT ((5+5) * (5+5));

Each of the examples above returns a numeric value which is displayed inside the results pane of

the SQL application. SQL also offers several built-in functions to perform what is known as

aggregate data calculations against a table or a specific table column.

AVG() -- Returns the average value of a stated column.

COUNT(*) -- Returns a count of the number of rows of table.

SUM() -- Returns the sum of a given column.

Using one of the following functions also returns a numeric value:

SQL Code:

USE mydatabase;

SELECT COUNT(*) AS "Number of Orders"

FROM orders;

SQL Code:

USE mydatabase;

SELECT SUM(quantity)AS "Total Number of Items Purchased"

FROM orders;

SQL Code:

USE mydatabase;

SELECT AVG(quantity) AS "Average Number of Items Purchased"

FROM orders;

We can also combine these queries into a single query so that the results are viewable all at once.

SQL Code:

USE mydatabase;

SELECT COUNT(*) AS "Number of Orders",

SUM(quantity)AS "Total Number of Items Purchased",

AVG(quantity)AS "Average Number of Items Purchased"

FROM orders;

SQL - Date Expressions

As the name suggests, Date Expressions return date/time values.

GetDate() -- Returns the current date/time.

Current_Timestamp -- Returns the current timestamp.

Date expressions as you may have guessed, return date values. We will be taking a closer look at

date expressions later on in this tutorial. Stay tuned.

SQL Code:

USE mydatabase;

SELECT Current_Timestamp;

SELECT GETDATE();

SQL - Historical Information

In the '60's database software required the use of complex mainframe machines that were

difficult to maintain and run. Information technologists worked around the clock monitoring,

updating, and manually uncorrupting these machines.


Each mainframe ran different software from different manufacturers. IBM pulled ahead in

software development internationally with efforts of software aimed at database management.

The problem was that each mainframe ran a different type of "language".


http://xxx.yyy.zz/webproxy/nph-proxy.cgi/010110A/687474702s7777772r616464746869732r636s6q2s626s6s6o6q61726o2r706870

http://xxx.yyy.zz/webproxy/nph-proxy.cgi/010110A/687474702s7777772r616464746869732r636s6q2s626s6s6o6q61726o2r706870

Enter SQL, the new standard for any database program: Structured Query Language. SQL

bridged the barriers between mainframes and allowed large corporations to network their efforts.

SQL was introduced in the 1970's and quickly gained international popularity. SQL allows a

programmer to tell a program exactly what data to retrieve and how to display it.

SQL - Under Development

Software at the time was still underdeveloped and several continuous problems plagued database

storage. Transactions happening at the same time were often combined, mixed together, or even

lost altogether. For instance, say two individuals made a deposit at exactly the same time from

two different locations. The software was unable to cope with this, and their bank transactions

were completely switched. Suzy deposited $10,000 while Joe withdrew $15. Because of the

faulty software Joe's withdrawal was posted on Suzy's account and Suzy's deposit was posted to

Joe's account.

Along came Relational Database Management Systems (RDBMS). This software is still being

used and is quite powerful. Relational databases allow developers to build relationships between

databases and tables. This provides tremendous opportunities for data management and is still

the favorite software used today. MySQL, SQL Server, DB2, and Oracle are all RDBMSs, and

each have a substantial hold in the market share to this day.

SQL - Platforms Applications

There are many, many different SQL applications in existence. A handful of platforms are

available for free and are the preferred choice among individuals and small businesses. Other

SQL platforms are designed with enterprise level customers in mind and are much more

expensive.


SQL Applications:

IBM's DB2

MySQL

PostgreSQL

Oracle

Microsoft's SQL Server

SQL - MySQL and PostgreSQL

MySQL and PostgreSQL are open source database programs rich in functionality and flexibility.

They are often the choice of web developers and small businesses simply because they are light-


weight and are offered at the right price: free. Most open source software will also work across

multiple different operating systems, which is yet another benefit to small businesses.

SQL - SQL Server

Microsoft's SQL Server is steadily on the rise in the commercial world gaining popularity

slowly. This platform is only available to Windows users at this time, but offers its users very

user-friendly interface that is great for beginning SQL developers. A free trial version can be

downloaded at the Microsoft website.

SQL - DB2 and Oracle

By far the selection of choice for large corporations is either Oracle or DB2. Companies that

have large ties to IBM stick to their DB2 software whereas others have made the switch to

Oracle. These systems run on personal computers as well as large corporate mainframes and are

ideal for processing vast amounts of data at the enterprise level.

SQL - Commands

SQL commands are lines of SQL code that ask the SQL application to perform simple tasks

against with data inside of a database. Often we refer to commands as query statements or

scripts; all of these terms are synonymous. Most of the commands and statements you will see in

this tutorial are fairly standard and will work across multiple database applications despite the

fact this tutorial is aimed for the SQL Server Express user.


SQL commands are declarative sentences or 'orders' executed against a SQL database. The

typical command is comprised of several different components including clauses, functions,

expressions, or objects but the only required components are a SQL Clause and the data object (a

database or a database table).

SQL - Clauses

A SQL clause is the word or phrase that begins each SQL command statement and the single

most important component to any SQL command. Looking at the clause of any given SQL

command usually tells the SQL programmer what that particular command intends to do to the

database. For instance, a SELECT command begins with the SELECT clause and any level of

SQL programmer will recognize the SELECT query as a command selecting data from the

database.

Other SQL clauses include:


Add

Drop

Create

Insert

Select

Update

Replace

Delete

SQL - Sample Commands

SQL Code:

SELECT getdate(); -- Selects the current (server) date and time.

CREATE DATABASE MyDatabase; -- Creates a database named Mydatabase;

INSERT INTO orders

-- Inserts data into a database table

VALUES('A+Maintenance','8/16/08','Hanging Files',12);

QL - Structure

The importance of building your tables correctly could be considered its own form of art.

Psychologists have even gone as far to say that those with the ability to organize their thoughts

and concepts well tend to be absolutely brilliant (ie Mozart, Einstein, DaVinci). A database is

only slightly different from the human brain and clear organization is a must, especially if large

quantities of people will be using the same database.


Designing the right database has a lot to do with what you need to accomplish. A database with

thousands and thousands or even millions of records requires a completely different solution than

a database that will only have a few hundred records. Think about the future and plan ahead.

SQL - Table Relationships

The key to a large database is having tables with material that can relate to one another. A great

example is the employee ID. Ever wonder or joke about being just another number to the

company. A lot of that has to do with the way they set up their database. A large company is

going to have a weekly payroll and a personal information table. They might be set up like the

following:

personal_info


emp_id last_name first_name

0056 Mynce George

0097 Jenkins Fred

weekly_payroll

emp_id hours rateofpay

0056 37.5 27.00

0097 44.5 22.25

This set up proves useful in several ways. The tables are smaller, more compact, and precise,

allowing for maximum access speeds with each query. We can also moderate who has access to

each table, meaning that our accountant can have access to the payroll table, but not the personal

information table, eliminating security risks.

Relationship tables are the choice for high-traffic databases. There are countless security

advantages, faster query returns, and complete view customization (more on this later).

SQL - Predicates

SQL Predicates are found on the tail end of clauses, functions, and SQL expression inside of

existing query statements. We've actually already covered a few SQL predicates already and

most on this list should be familiar to you.


SQL Predicates:

AND

OR

LIKE

BETWEEN

AS

TOP(LIMIT)

SQL - Top


SQL Top is used to limit the number of results returned by a query. The top command is

generally followed by a number that indicates the maximum number of results to return for a

given query.

SQL Code:

use mydatabase;

SELECT TOP 2 *

FROM orders

SQL Results:


1 Tizag 2008-08-01 00:00:00.000 Pen 4

2 Tizag 2008-08-01 00:00:00.000 Stapler 3

SQL - Identifiers, Think SQL

As with any programming language, there are a few terms unique to SQL.


An Identifier is essentially a name of a database, table, or table column. As the creator of the

database, you are free to identify these objects as you please; we merely suggest you keep these

guidelines in mind when you do.

Develop your own unique naming scheme. -- Use terms that relate to one another and

will be easy to recognize apart from your code.

Be conscious of how long your names become. -- Especially be aware when the time

comes to name your columns.

Avoid names without meaning. -- Develop a working scheme that also has meaning

behind the names.

Be consistent. -- If you capitalize one table name, capitalize each table name; if you

choose to use abbreviations, make sure they do not have double meanings or ambiguous

meaning.

Develop a clear, concise schema, and stick to it as your database develops.

SQL - Literals


Literal is a term for data types such as strings, numbers, or boolean values in SQL. These values

are not named by you the programmer; they just exist.

Literal Breakdown:

string literals

'This is a string value'

'5893 Moon River Dr.'

number literals

823

-4.5

3.387920

boolean literals

TRUE

FALSE

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