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In the process of learning something, it is best if you can reproduce what you learnt. Keeping this mantra in mind, I have decided to share what I have learnt about SQL Fundamentals. The project is broken into modules. Each module has different topics that are covered. I am passing on all of the information so that you do not have to pay to learn. You might still need to pay for a certificate but if you are just starting out and want to get notes, this project should suffice.

You can use this project to learn SQL either on a MYSQL server or a POSTGRESQL server. The database that is used as an example is Northwinds Database. This is an example database that Microsoft created for tutorials. It is available on GitHub here.

For a POSTGRESQL server the database that can be used is the DVD Rental Database that can be found here.

A computer with an internet connection is required. I will not be diving deep into the requirements for different Operating Systems. As and when I do document loading the database on into a machine it will be RHEL8 and also I would like to document how to load the database into a container.

Pending till further notice

Basic introduction of SQL. It stands for Structured Query Language. In this module you will learn the basics of SQL. You already have learnt what the acronym stands for.

So we know now what SQL stands for, but what does it do ?? SQL lets you access and manipulate entries in databases. A database is simply put a collection of data. SQL can help you retrieve data, insert data, run queries,create tables, create databases and much more. We will be going over some of the most important abilities below as we progress.

SQL IS A STANDARD BUT

SQL became a standard of the American National Institute in 1982 and of the International Standard Organization in 1987 but there are different versions of it. However, in order to be compliant to the ANSI and ISO standards they support at least the major commands such as

• SELECT

• UPDATE

• DELETE

• INSERT

• WHERE

and some more.

RDBMS

Relational Database Management System. Now if I am not mistaken, I think it was Oracle that started this concept. Earlier there were databases but they did not talk to each other. It was at Oracle that they devised a way in which these databases could communicate with each other. I could be wrong but I think I am right. Do create a pull request if you think this information can be updated.

RDBMS is the stepping stone for SQL and for all modern databases such as Oracle, IBM DB2, MS SQL Server, POSTGRES.

The data in RDBMS is stored in database objects called tables. A table is a collection of data entries and it consists of rows and columns. Rows are horizontal lines that contain data and Columns are vertical lines that hold data. A record is also called a row and a field is also known as a column.

• Database Tables

Each Database consists of different tables. Each table is given a name for Example Customers, Orders etc. Each table consists of different rows and columns.

• SQL Statements

Most actions that need to be performed on databases are done with SQL Statements. The below statement will select all records from the "Customers" table.

	SELECT * FROM Customers;

SQL is not case sensitive. SELECT is the same as select.

Semicolons are used to differentiate multiple SQL statements.

FREQUENT SQL COMMANDS

• SELECT: Extracts data from the database

• UPDATE: Updates data in the database

• DELETE: Deletes data from a database

• INSERT INTO: Inserts new data into a database

• CREATE DATABASE: Creates a new database

• ALTER DATABASE: Modifies a database

• CREATE TABLE: Creates a table in a database

• ALTER TABLE: Modifies a table

• DROP TABLE: Deletes a table

• CREATE INDEX: Creates an index (search key)

• DROP INDEX: Deletes an index

Extracting data is the first step and is an important step in database management. We need to use the SELECT statement to extract data.

The syntax for a simple Select statement is:

	SELECT coulmn1,column2,...coulmn_N
	FROM TABLE_NAME;

Here column1, coulmn2 are the field names of the table you want to select data from. If you want to select all data from the table, then the syntax will be:

	SELECT * FROM TABLE_NAME;

At times there can be data that is duplicate in nature i.e it is repeated in the table for example, it could be the name of a country or name of a city. If that is the case and we need only the unique ( distinct ) values we need to append the word distinct to select. It is done like so

	SELECT DISTINCT Column1 FROM TABLE_NAME;

The above statement will list only the unique values from Column1. Let's have a look at the same statement for a column with Countries in it.

	SELECT DISTINCT Countries FROM Customers;

This will list the unique countries that Customers are from in the table called Customers.

What might be helpful is getting the count of the unique values. That can be achieved by the below statement.

	SELECT COUNT(DISTINCT Country) FROM Customers;

COUNT is a function and we will touch base on that a little later. Right now you can try out this example on your machine.

Diving a little deeper into SQL with filtering and sorting of results.

WHERE clause is used to filter the results. As the name suggests it will help us filter the results where our conditions are met. For example if we want names of Customers only from a certain Country or a City we could write a statement like this

	SELECT * FROM Customer
	WHERE Country='Denmark';

The above statement should give you an idea of the syntax. It goes like this:

	SELECT Col_1,Col_2,...Col_N
	FROM TABLE_NAME
	WHERE Condition;

The WHERE clause is used not only with SELECT statement but also with other statements such as UPDATE,DELETE and many other... you will see soon enough.

Also please keep in mind that when using the WHERE clause if the condition is in text you need to use ' ' quotes. If the condition is in digits no quotes are required.

You saw the operator = being used earlier in the WHERE clause. There are other operators as well that can be used. Some of them are listed below for your reference.

> :Greater Than

< :Less Than

>= :Greater Than or Equal To

<= :Less Than or Equal To

<> :Not Equal ( In some SQL Versions != is used for Not Equal )

LIKE :This operator searches for a pattern. We will look at this in detail a little later

BETWEEN :As the name suggests, between a certain range.We will look at this in detail a little later

IN :To specify multiple possible values for a column. We will look at this in detail a little later

Along with the above mentioned operators the WHERE clause can also be used with the operators "AND" "OR" "NOT".

AND: Displays a record if ALL the conditions separated by AND are true.

Usage:

	SELECT * FROM Customers
	WHERE Country='Germany' AND City='Berlin';

OR: Displays a record if ANY of the conditions separated by OR are true.

Usage:

	SELECT * FROM Customers
	WHERE Country='Germany' OR Country='Austria';

NOT: Displays a record if the condition is NOT true.

Usage:

	SELECT * FROM Customers
	WHERE NOT Country='Canada';

Sometimes there can be a need to combine these various operators to fine-tune our results. What if we wanted the list of customers from Germany but only those that are from either Berlin or Munich ? We need to use parenthesis to do that.

	SELECT * FROM Customers
	WHERE Country='Germany' AND (City='Berlin' OR City='Munic');

Another example is of combining AND and NOT

	SELECT * FROM Customers
	WHERE NOT Country='Germany' AND NOT Country='Canada';

Often it helps if the results from a query can be sorted in a particular manner. Sorting in SQL is done by using ODER BY. By default the query in SQL is sorted in an ASCENDING order. That is small to big. Should you need to specify that the result be in DESCENDING order you must write DESC at the end of the statement.

A small example:

	SELECT * Customers
	ORDER BY Country;

Another example where we ORDER BY more than one column

	SELECT * Customers
	ORDER BY Country, CustomerName;

The same example but with DESC

	SELECT * Customers
	ORDER BY Country, CustomerName DESC;

Diving still deeper into SQL with managing data in tables with insertion, deletion and updating.

If you need to insert data into a table you need to use the INSERT INTO statement.

Simple syntax for the same goes something like this

	INSERT INTO TABLE_NAME (Col_1,Col_2..Col_N)
	VALUES (Value_for_Col_1,Value_for_Col_2,Value_for_Col_N);

If you are adding values to ALL columns of the table you do not need to specify the column names BUT ensure that the values are in the same order as the columns.

	INSERT INTO TABLE_NAME
	VALUES (Value_for_Col_1,Value_for_Col_2,Value_for_Col_N);

A field with a NULL value is a field with no value. NULL value is different from a field with zero in it or with spaces. NULL value is a field that is left blank at the time of creation. For example a field which is optional.

To test for fields with NULL values we need to use the IS NULL or NOT NULL operators.

Syntax IS NULL:

	SELECT Column_name
	FROM TABLE_NAME
	WHERE Column_name IS NULL;	

Syntax NOT NULL:

	SELECT Column_name
	FROM TABLE_NAME
	WHERE Column_name IS NULL;	

Always use IS NULL to look for NULL Values

The update statement is used to modify data in existing records of tables. IMP It should be used with a condition such as WHERE clause else all records of the table will be updated.

Syntax:

	UPDATE TABLE_NAME
	SET Col_1=value1, Col_2=value2,..Col_N=valueN
	WHERE condition;

Remember that if the value is in text you must use quotes.

The delete statement is used to deleted existing records in a table. IMP It should be used with a condition such as WHERE clause else all records of the table will be updated.

Syntax:

	DELETE FROM TABLE_NAME
	WHERE condition;

To delete all records from a table without deleting the table you can use the below statement. This means that the table structure, attributes and index will remain intact.

	DELETE FROM TABLE_NAME;

We will learn a little about Methods a little bit about Functions and some more operators to make our life a little easier while going through data.

The SELECT TOP clause is used to specify the number of records to return. It is useful on large tables with thousands of records.

The syntax for this is

	SELECT TOP number|percent column_name(s)
	FROM TABLE_NAME
	WHERE condition;

Example

	SELECT TOP 3 * 
	FROM Customers
	Where Country='Germany';

Please note that not all databases accept SELECT TOP

For MYSQL LIMIT is used and the above example will look something like this

	SELECT * FROM Customers
	Where Country='Germany'
	LIMIT 3;

For ORACLE as well there will be a difference since they use ROW NUM

	SELECT * FROM Customers
	Where Country='Germany' AND ROWNUM <= 3;

Functions in SQL are basically methods of getting results such as Count, Sum, Max, Min etc. Below are some basic functions along with their syntax for your reference.

As the name suggests these functions will return the minimum or maximum value from a column. Below is the syntax for the same

	SELECT MIN(col_name)
	FROM TABLE_NAME
	WHERE Condition;


	SELECT MAX(col_name)
	FROM TABLE_NAME
	WHERE Condition;

The brackets within which the column name is mentioned are important and part of the syntax.

Again as the name suggests these functions provide the count, average and sum values of the records. An example for each for you to understand the syntax

	SELECT COUNT(CustomerID)
	FROM Customers;


	SELECT AVG(Price)
	FROM Products;


	SELECT SUM(Quantity)
	FROM OrderDetails;

NOTE:NULL VALUES ARE IGNORED

The Like operator is used with the WHERE clause to search for a particular pattern in a column. A pattern is formed by using wild cards. The most common wild cards that are used with the Like operator are % and _ The % sign represents zero,one or multiple characters. The _ represents a single character.

MSAccess uses an asterisk instead of the percent sign and a question mark in place of the underscore.

The percent sign and underscore can be used in combinations. We can also combine any number of conditions with the AND and OR operators.

Syntax for the Like operator is

	SELECT col_1,col_2...col_n
	FROM TABLE_NAME
	WHERE Column LIKE pattern;

Example

	SELECT *	
	FROM Customers
	WHERE CustomerName LIKE 'a%';

This example will return all records where CustomerNames begins with the letter a.

We can also use the Like operator with the NOT operator to use negative conditions or to eliminate options.

	SELECT *
	FROM Customers
	WHERE Country NOT LIKE 'g%';

This example will return all records where the country's name does not begin with g.

A wild card character is used to substitute one or more characters in a string. You already have gotten a small brief above. When used with the WHERE clause we can search for a specified pattern in a column.

Some commonly used wild card characters in SQL are:

[] represents any single character within the brackets. h[oa]t will search for hot and hat.

^ represents any character not within the brackets. h[^oa]t will search for all combinations except hot and hat.

- represents a range of characters. h[a-d]t will search for hat hbt hct hdt.

All wildcard characters can be used in combinations as well.

PS: If you are familiar with bash, using wildcards in SQL is like globbing and regular expression.

The IN operator allows you to specify multiple values in the WHERE clause. You can also use the NOT operator with it.

Simple Syntax:

	SELECT column_name(s)
	FROM TABLE_NAME
	WHERE column_name IN (value1, value2...);

Example:

	SELECT * FROM Customers
	WHERE Country IN ( 'Germany', 'Canada');

Slightly Advanced Syntax:

	SELECT column_name(s)
	FROM TABLE_NAME
	WHERE column_name IN ( SELECT STATEMENT);

Example:

	SELECT * FROM Customers
	WHERE Country IN ( SELECT Country FROM Suppliers);

The above exaample will select all customers that are from the same countries as the suppliers.

The BETWEEN operator will select values within a given range. The values can be numbers,text or date.

The BETWEEN operator is inclusive that means it will include the start and end values. Once again the NOT operator can be used in combination.

Syntax:

	SELECT column_name(s)
	FROM TABLE_NAME
	WHERE column_name BETWEEN value1 AND value2;

Example:

	SELECT * FROM Products
	WHERE Price BETWEEN 10 AND 20;

With NOT

	SELECT * FROM Products
	WHERE Price NOT BETWEEN 10 AND 20;

With IN

	SELECT * FROM Products
	WHERE Price BETWEEN 10 AND 20
	AND Category IN('Spices', 'Oils');

Use with Dates

	SELECT * FROM Orders
	WHERE OrderDate BETWEEN '20201-08-25' AND '2020-09-25';

Aliases are used to give a table or a column name a temporary name. Aliases can be useful when

• More than one table is used for a query
• Functions are used in the query
• Column names are very big and not readable
• Two or more columns are combined

Column Syntax:

	SELECT column_name AS alias_name
	FROM TABLE_NAME;

Table Syntax:

	SELECT column_name(s)
	FROM TABLE_NAME AS alias_name;

If the alias name contains a space it will need to be quoted.

Creating one alias for multiple columns is also possible.

As an exmaple we will create an alias called "Address" which combines four columns

SQL

	SELECT CustomerName, Address + ', ' + PostalCode + ' ' + City + ', ' + Country AS Address
	FROM Customers;

MYSQL

	SELECT Addrss, CONCAT(Address,', ',PostalCode,', ',City,', ',Country) AS Address
	FROM Customers;

Diving deeper into the rabbit hole !! We are going to learn how to use common column(s) to combine different tables. If you remember venn diagrams this will be a breeze.

The JOIN operator is used to combine rows from two or more tables based on a column which is common in both the tables.

We can use this functionality to match different data points to get better insights.

Like for example in this current databasae there are two tables. Customers and Orders.

There is a column that is common in both of them which is CutomerID.

Using JOIN operators we can create a statement which will give us the number of orders for each customer.

The INNER JOIN keyword selects records that have matching values in both the tables.

Syntax:

	SELECT column_name(s)
	FROM TABLE_1
	INNER JOIN TABLE_2
	ON TABLE_1.column_name = TABLE_2.column_name;

The INNER JOIN selects all rows from both tables as long as there is a match between the columns. If there are records in the "Orders" table that DO NOT have a match in "Customers" then those records will not be shown.

Example:

	SELECT Orders.OrderID, Customers.CustomerName
	FROM Orders
	INNER JOIN Customers ON Customers.CustomerID = Customers.CustomerID;

We can use INNER JOIN to join three tables as well if there are columns that match.

Example:

	SELECT Orders.OrderID, Customers.CustomerName, Shippers.ShipperName
	FROM (( Orders
	INNER JOIN Customers ON Orders.CustomerID = Customers.CustomerID)
	INNER JOIN Shippers ON Orders.ShipperID = Shippers.ShipperID);

The LEFT JOIN returns all records from the left table i.e TABLE 1 and the matched records from the right table i.e TABLE 2. The result is NULL from the right side, if there is no match. It will still return all records from TABLE 1.

Syntax:

	SELECT column_name(s)
	FROM TABLE_1
	LEFT JOIN TABLE_2
	ON TABLE_1.column_name = TABLE_2.column_name;

In some databases LEFT JOIN is also called as LEFT OUTER JOIN

Example:

	SELECT Customers.CustomerName, Orders.OrderID
	FROM Customers
	LEFT JOIN Orders
	ON Customers.CustomerID = Orders.CustomerID
	ORDER BY Customers.CustomerName;

In the above example we have displayed all the orders made by the customers.

The RIGHT JOIN returns all records from the right table i.e TABLE 2 and the matched records from the left table i.e TABLE 1. The result is NULL from the left side, if there is no match. It will still return all records from TABLE 2. Basically the complete opposite of LEFT JOIN

Syntax:

	SELECT column_name(s)
	FROM TABLE_1
	RIGHT JOIN TABLE_2
	ON TABLE_1.column_name = TABLE_2.column_name;

In some databases RIGHT JOIN is also called as RIGHT OUTER JOIN

Example:

	SELECT Orders.OrderID, Employees.LastName, Employees.FirstName
	FROM Orders
	RIGHT JOIN Employees ON Orders.EmployeeID = Employees.EmployeeID
	ORDER BY Orders.OrderID;	

In the above example we will be dsiplayed all employess and any orders that they might have placed.

The RIGHT JOIN will return all records from the right table i.e Employees even if there are no matches on the left table i.e Orders.

The FULL OUTER JOIN will return all records when there is a match in left i.e TABLE 1 or right i.e TABLE 2 records. This operator can return very large data sets.

In some databases FULL OUTER JOIN is called as FULL JOIN

Syntax:

	SELECT column_name(s)
	FROM TABLE_1
	FULL OUTER JOIN TABLE_2
	ON TABLE_1.column_name = TABLE_2.column_name
	WHERE condition;

Example:

	SELECT Customers.CustomerID, Orders.OrderID
	FROM Customers
	FULL OUTER JOIN Orders
	ON Customers.CustomerID = Orders.CustomerID
	ORDER BY Customers.CustomerName;

In the above example we will be displayed all orders of all customers. If a customer does not have an order a NULL value will be displayed but the record will be shown.

A SELF JOIN is a regular join where in the table is joined with itself. Alias is used to further divide the columns which will then later get matched.

Syntax:

	SELECT column_name(s)
	FROM TABLE_1 AS t1, TABLE_2 As t2
	WHERE condition;

Let us try this from the "Customers" table where in we want to find out all the customers with the same city.

	SELECT A.CustomerName AS CumstomerName1, B.CustomerName AS CustomerName2, A.City
	FROM Customers A, Customers B
	WHERE CustomerName1 <> CustomerName2
	AND A.City = B.City
	ORDER BY A.City;

The UNION operator is used to combine the result-set of two SELECT statements.

• Each SELECT statement within the UNION operator should have the same number of columns.

• The column must have similar data types

• The columns in each SELECT statement must also be in the same order.

When we use UNION operator duplicate values will not be displayed. For that we need to use the UNION ALL operator

Syntax UNION

	SELECT column_name FROM TABLE_1
	UNION
	SELECT column_name FROM TABLE_2;

Syntax UNION ALL

	SELECT column_name FROM TABLE_1
	UNION ALL
	SELECT column_name FROM TABLE_2;

The column names in the result-set are usually equal to the column names in the first SELECT statement in the union.

Example:

	SELECT City FROM Customers
	UNION
	SELECT City FROM Suppliers
	ORDER BY City;

The above example will return us a data-set of a list of cities which have Customers and Suppliers. It will display only distinct values. For all values even those that are being repeated usel UNION ALL.

UNION with WHERE

	SELECT City,Country FROM Customers
	WHERE Country = 'Germany'
	UNION 
	SELECT City,Country FROM Suppliers
	WHERE Country = 'Germany'
	ORDER BY City;

Again in the above example only distinct cities will be displayed from Germany. Use UNION ALL for repetitve values.

In this module we will go over some more methods and opertators.

As the name suggests, GROUP BY statement groups rows that have the same values into summary rows. Consider it like finding the number of customers in each city or country.

GROUP BY statement is often used with other functions such as COUNT() MAX MIN AVG to group the result-set by one or more columns.

Syntax:

SELECT column_name(s)
FROM TABLE_NAME
WHERE condition
GROUP BY column_name(s)
ORDER BY column_names(s);

Example:

SELECT COUNT(CustomerID),Country
FROM Customers
GROUP BY Country;

In the above example we will be displayed the number of customers from each country. To further fintune the example you can use ORDER BY DESC to display the number in descending order.

Example of GROUP BY with JOIN:

SELECT Shippers.ShipperName, COUNT(Orders.OrderID) AS NumberOfOrders FROM Orders
LEFT JOIN Shippers ON Orders.ShipperID = Shippers.ShipperID
GROUP BY ShipperName;

In the above example we will get the number of orders sent by each Shipper.

The HAVING clause is used in SQL was added later since the WHERE clause could not be used with aggregate functions.

Syntax:

SELECT column_name(s)
FROM TABLE_NAME
WHERE condition
GROUP BY column_name(s)
HAVING condition
ORDER BY column_names(s);

Example:

SELECT COUNT(CustomerID), Country
FROM Customers
GROUP BY Country
HAVING COUNT(CustomerID) > 5
ORDER BY COUNT(CustomerID) DESC;

In the above example we will be displayed a result-set of Countries wich have more than 5 customers and the result-set will be displayed in descending order.

Example of HAVING and JOIN

SELECT Employees.LastName, COUNT(Orders.OrderID) AS NumberOfOrders
FROM (Orders
INNER JOIN Employees ON Orders.EmployeeID = Employees.EmployeeID)
GROUP BY LastName
HAVING COUNT(Orders.OrderID) > 10;

In this example we will get a result-set of employees with more than 10 orders.

Example of HAVING with WHERE and JOIN

SELECT Employees.LastName, COUNT(Orders.OrderID) AS NumberOfOrders
FROM Orders
INNER JOIN Employees ON Orders.EmployeeID = Employees.EmployeeID
WHERE LastName = 'Davolio' OR LastName = 'Fuller'
GROUP BY LastName
HAVING COUNT(Orders.OrderID) > 25;

Here we are checking if Employee Davolio or Fuller have more than 25 orders.

The EXISTS operator is used to test for the existence of a record in a subquery. The EXISTS operator returns a TRUE value if the subquery returns one more more records.

Syntax:

SELECT column_name(s)
FROM table_name
WHERE EXISTS
(SELECT column_name FROM table_name WHERE condition);

Example:

SELECT SupplierName
FROM Suppliers
WHERE EXISTS 
(SELECT ProductName FROM Products WHERE Products.SupplierID = Suppliers.supplierID AND Price < 20);

The above statement will return TRUE and list the Suppliers who have a product whose price is less than 20.

ANY and ALL operators are used with WHERE and HAVING operators.

ANY operator returns TRUE if any of the subquery values meets the conditions.

ALL operator returns TRUE if all of the subquery values meets the conditions.

Syntax ANY:

SELECT column_name(s)
FROM table_name
WHERE column_name operator ANY
(SELECT column_name FROM table_name WHERE condition);

Syntax ALL:

SELECT column_name(s)
FROM table_name
WHERE column_name operator ALL
(SELECT column_name FROM table_name WHERE condition);

The operator mentioned in the syntax must be a standard comparison operator like < , > , = etc.

Example ANY:

SELECT ProductName
FROM Products
WHERE ProductID = ANY
(SELECT ProductID FROM OrderDetails WHERE Quantity = 10);

The above statement returns TRUE if it finds ANY record in the OrderDetails table where the Quantity is equal to 10.

Example ANY:

SELECT ProductName
FROM Products
WHERE ProductID = ANY 
(SELECT ProductID FROM OrderDetails WHERE Quantity > 99);	

Again the above statement will return TRUE if it finds ANY records in the OrderDetails table where the Quantity is greater than 99.

Example ALL:

SELECT ProductName
FROM Products
WHERE ProductID = ALL
(SELECT ProductID FROM OrderDetails WHERE Quantity = 10);

Will this statement return TRUE or FALSE ?? It will return FALSE since the ALL operator requires that all of the subquery values meet the condition. Hence zero records will be displayed.

SELECT INTO statement basically copies data from one table into a new table.

Syntax of Copying all columns into a table:

SELECT * 
INTO NewTable [External DB]
FROM OldTable
WHERE condition;

Syntax of Copying some columns into a table:

SELECT Columns_name(s)
INTO NewTable [External DB]
FROM OldTable
WHERE condition;

The new table will be created with the column-names and typed defined in the old table. Should you want to give new names to the columns in the new table use alias AS.

Example:

SELECT * INTO CustomersBackup2017
FROM Customers;

We took backup of the Customers table in the above example.

Example:

SELECT * INTO CustomersBackup2017 IN 'Backup.mdb'
FROM Customers;

In the above example we used the IN clause to copy the table into another database.

Example:

SELECT CustomerName, ContactName INTO CustomersBackup2017
FROM Customers;

Just like the previous example but here we copied only a few columns not all of them.

Example:

SELECT * INTO CustomersGermany
FROM Customers
WHERE Country = 'Germany';

Here we created a table with customers from a particular country.

Example:

SELECT Customers.CustomerName, Orders.OrderID
INTO CustomersOrderBackup2017
FROM Customers
LEFT JOIN Orders ON Customers.CustomerID = Orders.CustomerID;

In the above example we used LEFT JOIN to copy data from different tables into a new table.

Example:

SELECT * INTO newtable
FROM oldtable
WHERE 1 = 0;

This is an interesting example where in we created a new empty table using the schema of an old table. We did this by using the WHERE clause that causes to return no data.

The INSERT INTO SELECT statement copies data and inserts it into another existing table.

• INSERT INTO SELECT statement requires that data types in the source match the target table

• The existing records of the target table remain unaffected.

Syntax of Copying all columns into a table:

INSERT INTO TABLE_2 
SELECT * FROM TABLE_1
WHERE condition;

Syntax of Copying some columns into a table:

INSERT INTO TABLE_2 (column1, column2, column3, ...)
SELECT column1, column2, column3, ...
FROM TABLE_1
WHERE condition;

Example:

INSERT INTO Customers (CustomerName, City, Country)
SELECT SupplierName, City, Country 
FROM Suppliers;

The above statement copies Suppliers into Customers. Columns that do not contain data will have NULL.

Example:

INSERT INTO Customers (CustomerName, City, Country)
SELECT SupplierName, City, Country 
FROM Suppliers
WHERE Country='Germany';

The above statment is similar to the earlier example, only here we have used a condition.

The CASE statement in SQL functions like the IF-THEN-ELSE statement in other programming languages. The CASE statement will go through conditions and returns a value when the first condition is met. Once a condition is true it will stop reading and return the result. If no condition is true, it returns the value from the ELSE clause.

Syntax:

CASE
	WHEN condition1 THEN result1
	WHEN condition2 THEN result2
	WHEN conditionN THEN resultN
	ELSE result
END;

Example:

SELECT OrderID, Quantity,
CASE
	WHEN Quantity > 30 THEN 'The quantity is greater than 30'
	WHEN Quantity = 30 THEN 'The quantity is 30'
	ELSE 'The quantity is under 30'
END AS QuantityText
FROM OrderDetails;

The above statement goes through conditions and return a value when the first condition is met.

Example:

SELECT CustomerName, City, Country
FROM Customers
ORDER BY
(CASE
	WHEN City IS NULL THEN Country
	ELSE City
END);

In the above statement SQL will order by City. However if the value of City is NULL it will order by Country.

There can be times when we run a SQL statement where in the value of a column is NULL and because of that the statement will not return any record. Suppose in the Products table the column UnitsOnOrder has some null values. Here if some values are null in UnitsOnOrder the result will be null.

SELECT ProductName, UnitPrice * (UnitsInStock + UnitsOnOrder)
FROM Products;

In order to safegaurd statements from the above error Null Functions are used. Different databases use different null functions.

MySql server uses IFNULL() which allows us to return an alternative value if an expression is null.

SELECT ProductName, UnitPrice * (UnitsInStock + IFNULL(UnitsOnOrder, 0))
FROM Products;

SQL server uses ISNULL()

SELECT ProductName, UnitPrice * (UnitsInStock + ISNULL(UnitsOnOrder, 0))
FROM Products;

ORACEL server uses NVL()

SELECT ProductName, UnitPrice * (UnitsInStock + NVL(UnitsOnOrder, 0))
FROM Products;

Here we will look into Stored Procedures, how to use comments and some more operators.

A stored procedure is a prepared SQL code that is saved and can be reused repeatedly. If there is a query that we repeat often, we can save it to be executed later. Parameters can also be passed to a stored procedure, so that a stored procedure can act based on the parameter value(s) that is/are passed.

Stored Procedure Syntax:

CREATE PROCEDURE procedure_name
AS
sql_statement
GO;

Executing Stored Procedure:

EXEC procedure_name;

Example:

Creation:

CREATE PROCEDURE SelectAllCustomers
AS
SELECT * FROM Customers
GO;

Execution:

EXEC SelectAllCustomers;

Example Stored Procedure with one parameter:

Creation:

CREATE PROCEDURE SelectAllCustomers @City nvarchar(30)
AS
SELECT * FROM Customers
WHERE City = @City
GO;

Execution:

EXEC SelectAllCustomers @City='Berlin';

Example Stored Procedure with multiple parameters:

Creation:

CREATE PROCEDURE SelectAllCustomers @City nvarchar(30), @PostalCode int(6)
AS
SELECT * FROM Customers
WHERE City = @City AND PostalCode = @PostalCode
GO;

Execution:

EXEC SelectAllCustomers @City='Berlin', PostalCode=123456

As you would have noticed, while using parameters we must assign the data types as well.

Comments are used to explain certain sections of code and are not executed when the query is run.

• Single Line Comments

In SQL single line comments start with --. It will comment all the words followed by it till the end of the line.

Example:

SELECT * FROM Customers -- selects all columns of all records from the table Customers

• Multi Line Comments

In SQL multi line comments start with /* and end with */

Example:

/*Select all the columns
of all the records
in the Customers table:*/
SELECT * FROM Customers;

Congratulations on making it this far ! Well done !! We are almost there now. It's the home stretch and you can do this !!

In order to create a database the statement CREATE DATABASE is used. Users with admin access can create databases. Once created you can verify the creation with SHOW DATABASES

Syntax:

CREATE DATABASE testDB;

Verify:

SHOW DATABASES;

Deleting a database is done by the statemtn DROP DATABASE. This can be done only with admin privilege.

Syntax:

DRP DATABASE testDB;

Once deleted, the database cannot be recovered.

Backing up a database is done by the statement BACKUP DATABASE

Syntax:

BACKUP DATABASE testDB
TO DISK = 'file_path';

Best practice is to not back up the database on the same disk on which the database is.

Along with BACKUP DATABASE exists an option to backup only those parts of the database that have been modified since the last back up. That can be done by using the WITH DIFFERENTIAL option

Syntax:

BACKUP DATABASE testDB
TO DISK = 'file_path'
WITH DIFFERENTIAL;

As you know by now that within a database several tables can exist. To create a table the statement CREATE TABLE is used. When creating a table we need to specify the name of the columns and the data type of those columns.

Syntax:

CREATE TABLE test_table (
column1 data type
column2 data type
columnN data type
);

Example:

CREATE TABLE Persons (
PersonID int,
	LastName varchar(255),
	FirstName varchar(255),
	Address varchar(255),
City varchar(255)
);

The PersonID column is of type int and will hold an integer. The LastName, FirstName, Address, and City columns are of type varchar and will hold characters, and the maximum length for these fields is 255 characters.

This wil create an empty table. To populate the table we can use INSERT INTO statement.

• Creating a table from another table

We can use the CREATE TABLE to create a new table by copying an existing table.

CREATE TABLE new_table_name AS
	SELECT column1, column2,...
FROM existing_table_name
WHERE ....;

To delete a table we need to use the statement DROP TABLE. Be carefule when using this statement since it will result in complete loss of all the information stored in the table.

Syntax:

DROP TABLE test_table;

Sometimes we might not want to delete the complete table but just the content in it. In such a scenario we can use the TRUNCATE TABLE statement.

Syntax:

TRUNCATE TABLE test_table;

The ALTER TABLE statement is used to add, remove or modify existing columns in a table. It is also used to add or remove constraints on a table. When adding a column, the data type needs to be specified.

Syntax: ALTER TABLE table_name ADD column_name datatype;

In the above syntax example the option ADD can be replaced with DROP COLUMN to delete a column or can be replaced with MODIFY or ALTER depending on the type of databse to modify the column.

For SQL SERVER and MS ACCESS ALTER COLUMN is used and for MYSQL and ORACEL servers MODIFY COLUMN is used. Modification are generally used to change the data type of the column.

Example:

ALTER TABLE Persons
ALTER COLUMN DateOfBirth year;

SQL constraints are used to specify rules for the data in a table.

Constraints are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the table. If there is any violation between the constraint and the data action, the action is aborted.

Constraints can be column level or table level. Column level constraints apply to a column, and table level constraints apply to the whole table.

Constraints can be applied to a table while creating it or while modifying it.

Syntax:

CREATE TABLE table_name (
	column1 datatype constraint,
	column2 datatype constraint,
	column3 datatype constraint,
);

By default, a column can hold NULL values.

The NOT NULL constraint enforces a column to NOT accept NULL values.

This enforces a field to always contain a value, which means that you cannot insert a new record, or update a record without adding a value to this field.

Example while creating a table:

CREATE TABLE Persons (
	ID int NOT NULL,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255) NOT NULL,
	Age int
);

Example while modifying a table:

ALTER TABLE Persons
MODIFY Age int NOT NULL;

The UNIQUE constraint ensures that all values in a column are different.

Both the UNIQUE and PRIMARY KEY constraints provide a guarantee for uniqueness for a column or set of columns.

A PRIMARY KEY constraint automatically has a UNIQUE constraint.

However, you can have many UNIQUE constraints per table, but only one PRIMARY KEY constraint per table.

Example while creating table for SQL,ORACLE, MS ACCESS:

CREATE TABLE Persons (
	ID int NOT NULL UNIQUE,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int
);

For MYSQL:

CREATE TABLE Persons (
	ID int NOT NULL,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int,
UNIQUE (ID)
);

To name a UNIQUE constraint and to define it on multiple columns:

CREATE TABLE Persons (
	ID int NOT NULL,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int,
	CONSTRAINT UC_Person UNIQUE (ID,LastName)
);

In the above example we have named the constraint UC_Person and it is applicable on columns ID and LastName. Also the above example is valid for MYSQL/SQL/ORACEL/MS ACCESS servers.

Example while modifying a table for SQL,ORACEL,MS ACCESS:

ALTER TABLE Persons
ADD UNIQUE (ID);

Here we added a UNIQUE constraint on the column ID after the table was created.

If we want to name a UNIQUE constraint and to define it on multiple columns:

ALTER TABLE Persons
ADD CONSTRAINT UC_Person UNIQUE (ID,LastName);

Example of deleting UNIQUE constraint:

MYSQL:

ALTER TABLE Persons
DROP INDEX UC_Person;

ORACLE/SQL/MS ACCESS:

ALTER TABLE Persons
DROP CONSTRAINT UC_Person;

The PRIMARY KEY constraint uniquely identifies each record in a table.

Primary keys must contain UNIQUE values, and cannot contain NULL values.

A table can have only ONE primary key; and in the table, this primary key can consist of single or multiple columns (fields).

Example Create Table:

MYSQL:

CREATE TABLE Persons (
ID int NOT NULL,
LastName varchar(255) NOT NULL,
FirstName varchar(255),
Age int,
PRIMARY KEY (ID)
);

SQL Server / Oracle / MS Access:

	CREATE TABLE Persons (
		ID int NOT NULL PRIMARY KEY,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int
	);

Example Alter Table:

ALTER TABLE Persons
ADD PRIMARY KEY (ID);

Example of naming a key and assigning multiple columns while creating a table:

	CREATE TABLE Persons (
		ID int NOT NULL,
	LastName varchar(255) NOT NULL,
 	FirstName varchar(255),
		Age int,
		CONSTRAINT PK_Person PRIMARY KEY (ID,LastName)
	);

In the above example the name of the PRIMARY KEY is PK_Person and the value of the key is made up of two columns i.e ID and LastName.

The same example but while altering a table:

ALTER TABLE Persons
ADD CONSTRAINT PK_Person PRIMARY KEY (ID,LastName);

When we use ALTER TABLE to add a primary key, the columns that are to be assigned must already have been declared to not contain NULL values

Deleteing a PRIMARY KEY:

MYSQL:

ALTER TABLE Persons
DROP PRIMARY KEY;

SQL/ORACLE/MS ACCESS:

ALTER TABLE Persons
DROP CONSTRAINT PK_Person;

A FOREIGN KEY is a key used to link two tables together. A FOREIGN KEY is a field (or collection of fields) in one table that refers to the PRIMARY KEY in another table. The table containing the foreign key is called the child table, and the table containing the candidate key is called the referenced or parent table.

The FOREIGN KEY constraint is used to prevent actions that would destroy links between tables. The FOREIGN KEY constraint also prevents invalid data from being inserted into the foreign key column, because it has to be one of the values contained in the table it points to.

Syntax CREATE TABLE:

MYSQL:

CREATE TABLE Orders (
	OrderID int NOT NULL,
	OrderNumber int NOT NULL,
	PersonID int,
	PRIMARY KEY (OrderID),
	FOREIGN KEY (PersonID) REFERENCES Persons(PersonID)
);

SQL/ORACLE/MS ACCESS:

CREATE TABLE Orders (
	OrderID int NOT NULL PRIMARY KEY,
	OrderNumber int NOT NULL,
	PersonID int FOREIGN KEY REFERENCES Persons(PersonID)
);

In the above example SQL creates a FOREIGN KEY on the "PersonID" column when the "Orders" table is created

Syntax ALTER TABLE:

To create a new FOREIGN KEY

ALTER TABLE Orders
ADD FOREIGN KEY (PersonID) REFERENCES Persons(PersonID);

To allow naming of a FOREIGN KEY constraint and for defining it on multiple columns:

ALTER TABLE Orders
ADD CONSTRAINT FK_PersonOrder
FOREIGN KEY (PersonID) REFERENCES Persons(PersonID);

Deleting a FOREIGN KEY:

MYSQL:

ALTER TABLE Orders
DROP FOREIGN KEY FK_PersonOrder;

SQL/ORACLE/MS ACCESS:

ALTER TABLE Orders
DROP CONSTRAINT FK_PersonOrder;

The CHECK constraint is used to limit the value range that can be placed in a column. If we define a CHECK constraint on a single column it allows only certain values for this column. If we define a CHECK constraint on a table it can limit the values in certain columns based on values in other columns in the row.

Syntax CREATE TABLE:

MYSQL:

CREATE TABLE Persons (
ID int NOT NULL,
	LastName varchar(255) NOT NULL,
FirstName varchar(255),
Age int,
CHECK (Age>=18)
);

SQL/ORACLE/MS ACCESS:

CREATE TABLE Persons (
	ID int NOT NULL,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int CHECK (Age>=18)
);

In the above example we set up a check for the user to be of either 18 or more years of age.

To allow naming of CHECK constraint and assigning it multiple columns while creating a table:

CREATE TABLE Persons (
	ID int NOT NULL,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int,
	City varchar(255),
	CONSTRAINT CHK_Person CHECK (Age>=18 AND City='Sandnes')
);

The above format works for all databases.

Syntax ALTER TABLE:

ALTER TABLE Persons
ADD CHECK (Age>=18);

To allow naming of CHECK constraint and assigning it multiple columns while altering a table:

ALTER TABLE Persons
ADD CONSTRAINT CHK_PersonAge CHECK (Age>=18 AND City='Sandnes');

Deleting CHECK:

MYSQL:

ALTER TABLE Persons
DROP CHECK CHK_PersonAge;

SQL/ORACLE/MS ACCESS:

ALTER TABLE Persons
DROP CONSTRAINT CHK_PersonAge;	

The DEFAULT constraint is used to provide a default value for a column. The default value will be added to all new records IF no other value is specified.

Syntax CREATE TABLE:

CREATE TABLE Persons (
	ID int NOT NULL,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int,
	City varchar(255) DEFAULT 'Humpolec'
);

Here we specified the default city to be Humpolec.

It can also be used along with function like GETDATE().

CREATE TABLE Orders (
	ID int NOT NULL,
	OrderNumber int NOT NULL,
	OrderDate date DEFAULT GETDATE()
);

Syntax ALTER TABLE:

MYSQL:

ALTER TABLE Persons
ALTER City SET DEFAULT 'Humpolec';

SQL SERVER:

ALTER TABLE Persons
ADD CONSTRAINT df_City
DEFAULT 'Brno' FOR City;

MSAcess:

ALTER TABLE Persons
ALTER COLUMN City SET DEFAULT 'Pilzen';

ORACEL:

ALTER TABLE Persons
MODIFY City DEFAULT 'Ostrava';

Deleting DEFAULT:

MYSQL:

ALTER TABLE Persons
ALTER City DROP DEFAULT;

SQL/ORACLE/MS ACCESS:

ALTER TABLE Persons
ALTER COLUMN City DROP DEFAULT;

The CREATE INDEX statement is used to create indexes in tables. Indexes are used to retrieve data from the database more quickly than otherwise. The users cannot see the indexes, they are only used to speed up searches/queries.

Consider an Index like an auto-filter that can be referred to.

Updating a table with indexes takes more time than updating a table without (because the indexes also need an update). Hence it is wise to only create indexes on columns that will be frequently searched against.

There are two types of Indexes. Simple and Unique. Unique index does not allow duplicate values.

Syntax Creation:

	CREATE INDEX index_name
	ON table_name (column1, column2, ...);

Creation of Unique Index:

	CREATE UNIQUE INDEX index_name
	ON table_name (column1, column2, ...);

The syntax for creation of index varies for different databases and unfortunately I do not have all of them listed. Please check documentation before proceeding.

Example:

CREATE INDEX idx_pname
ON Persons (LastName, FirstName);	

Syntax Deletion:

MYSQL: ALTER TABLE table_name DROP INDEX index_name;

ORACLE:

DROP INDEX index_name;

SQL:

DROP INDEX table_name.index_name;

Auto-increment allows a unique number to be generated automatically when a new record is inserted into a table. Often this is the primary key field that we would like to be created automatically every time a new record is inserted.

Syntax:

MYSQL:

CREATE TABLE Persons (
	Personid int NOT NULL AUTO_INCREMENT,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int,
	PRIMARY KEY (Personid)
);

MYSQL uses the keyword AUTO_INCREMENT. The default value starting value for auto increment is 1. To change it to a custom number use the below statement.

ALTER TABLE Persons AUTO_INCREMENT=100;

Once this is done we do not have to specify the value for this column during insertion of data.

SQL SERVER:

CREATE TABLE Persons (
	Personid int IDENTITY(1,1) PRIMARY KEY,
	LastName varchar(255) NOT NULL,
	FirstName varchar(255),
	Age int
);

SQL Server uses the keyword IDENTITY to achieve the same effect. It also offers us to assign the starting value and the value by which the increment will happen. In the above example both values have been set to 1.

ORACLE:

The code for ORACLE is not so simple. We will have to create an auto-increment field with the sequence object. This sequence object will generate a number sequence.

Syntax:

CREATE SEQUENCE seq_person
MINVALUE 1
START WITH 1

I NCREMENT BY 1 CACHE 10;

The code above creates a sequence object called seq_person, that starts with 1 and will increment by 1. It will also cache up to 10 values for performance. The cache option specifies how many sequence values will be stored in memory for faster access.

To insert a new record into the "Persons" table, we will have to use the nextval function (this function retrieves the next value from seq_person sequence)

INSERT INTO Persons (Personid,FirstName,LastName)
VALUES (seq_person.nextval,'Doctype','Human');

The SQL statement above would insert a new record into the "Persons" table. The "Personid" column would be assigned the next number from the seq_person sequence. The "FirstName" column would be set to "Doctype" and the "LastName" column would be set to "Human".

The most important part about working with dates is to ensure the format of the date that we are putting in matches the format of the date column present in the database.

To keep things simple we can avoid using the time portion in the format of the column.

The basic Date Data Type format is YYYY-MM-DD

We can retrieve data then using a simple statement like this:

SELECT * FROM Orders WHERE OrderDate='2008-11-11'

In SQL, a view is a virtual table based on the result-set of an SQL statement. A view contains rows and columns, just like a real table. The fields in a view are fields from one or more real tables in the database. You can add SQL functions, WHERE , and JOIN statements to a view and present the data as if the data were coming from one single table.

Syntax CREATE VIEW:

CREATE VIEW view_name AS
SELECT column1, column2, ...
FROM table_name
WHERE condition;

Example:

CREATE VIEW [Brazil Customers] AS
SELECT CustomerName, ContactName
FROM Customers
WHERE Country = 'Brazil';

And then to query the view:

SELECT * FROM [Brazil Customers];

Another example with functions:

CREATE VIEW [Products Above Average Price] AS
SELECT ProductName, Price
FROM Products
WHERE Price > (SELECT AVG(Price) FROM Products);

And then to query the view:

SELECT * FROM [Products Above Average Price];

Syntax for updating a view:

CREATE OR REPLACE VIEW view_name AS
SELECT column1, column2, ...
FROM table_name
WHERE condition;

The key word CREATE OR REPLACE VIEW is used to update a view.

Example:

CREATE OR REPLACE VIEW [Brazil Customers] AS
SELECT CustomerName, ContactName, City
FROM Customers
WHERE Country = 'Brazil';

In the above example we updated the Brazil Customers view to add the City column.

Syntax for deleting a view:

DROP VIEW [Brazil Customers];

SQL Injection is a very common method used by hackers to poison a database. What it does is, it presents a mailicious query that forces the database to share more than necessary information.

It usually occurs when a user is requested for an input usually like a username or userid. Insted of putting the correct value, the user places a statement that forces the database engine to execute it resulting in data leaks.

In order to protect the database from these attacks we can use SQL PARAMETERS. These parameters are assigned while writing server side code using languages like PHP, ASP.NET etc.

If we need our web site to be able to store and retrieve data the web server needs to have access to database system that uses the SQL language.

The most common SQL hosting databases are MySQL, ORACLE, MS SQL and MS Access.

The data type of a column defines what value the column can hold: integer, character, money, date and time, binary, and so on.

Each column in a database table is required to have a name and a data type.

The data type is a guideline for SQL to understand what type of data is expected inside of each column, and it also identifies how SQL will interact with the stored data.

It is always wise to check the official documentation for data types since they might have different names in different databases. And even if the names are the same the size and other details might differ.

Since this list is extensive I will share a few links in the section Further Reading

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