SQL Notes by Apna College (1).pdf

SQL (Notes by Apna College) What is Database? Database is a collection of interrelated data. What is DBMS? DBMS (Database Management System) is software used to create, manage, and organize databases. What is RDBMS? RDB...

SQL (Notes by Apna College) What is Database? Database is a collection of interrelated data. What is DBMS? DBMS (Database Management System) is software used to create, manage, and organize databases. What is RDBMS? RDBMS (Relational Database Management System) - is a DBMS based on the concept of tables (also called relations). Data is organized into tables (also known as relations) with rows (records) and columns (attributes). Eg - MySQL, PostgreSQL, Oracle etc. What is SQL? SQL is Structured Query Language - used to store, manipulate and retrieve data from RDBMS. (It is not a database, it is a language used to interact with database) We use SQL for CRUD Operations : CREATE - To create databases, tables, insert tuples in tables etc READ - To read data present in the database. UPDATE - Modify already inserted data. DELETE - Delete database, table or specific data point/tuple/row or multiple rows. *Note - SQL keywords are NOT case sensitive. Eg: select is the same as SELECT in SQL. SQL v/s MySQL SQL is a language used to perform CRUD operations in Relational DB, while MySQL is a RDBMS that uses SQL. SQL Data Types In SQL, data types define the kind of data that can be stored in a column or variable. To See all data types of MYSQL, visit : https://dev.mysql.com/doc/refman/8.0/en/data-types.html Here are the frequently used SQL data types: DATATYPE DESCRIPTION USAGE CHAR string(0-255), can store characters of fixed length CHAR(50) VARCHAR string(0-255), can store characters up to given length VARCHAR(50) BLOB string(0-65535), can store binary large object BLOB(1000) INT integer( -2,147,483,648 to 2,147,483,647 ) INT TINYINT integer(-128 to 127) TINYINT BIGINT integer( -9,223,372,036,854,775,808 to BIGINT 9,223,372,036,854,775,807 ) BIT can store x-bit values. x can range from 1 to 64 BIT(2) FLOAT Decimal number - with precision to 23 digits FLOAT DOUBLE Decimal number - with 24 to 53 digits DOUBLE BOOLEAN Boolean values 0 or 1 BOOLEAN DATE date in format of YYYY-MM-DD ranging from DATE 1000-01-01 to 9999-12-31 TIME HH:MM:SS TIME YEAR year in 4 digits format ranging from 1901 to 2155 YEAR *Note - CHAR is for fixed length & VARCHAR is for variable length strings. Generally, VARCHAR is better as it only occupies necessary memory & works more efficiently. We can also use UNSIGNED with datatypes when we only have positive values to add. Eg - UNSIGNED INT Types of SQL Commands:  1. DQL (Data Query Language) : Used to retrieve data from databases. (SELECT) 2. DDL (Data Definition Language) : Used to create, alter, and delete database objects like tables, indexes, etc. (CREATE, DROP, ALTER, RENAME, TRUNCATE) 3. DML (Data Manipulation Language): Used to modify the database. (INSERT, UPDATE, DELETE) 4. DCL (Data Control Language): Used to grant & revoke permissions. (GRANT, REVOKE) 5. TCL (Transaction Control Language): Used to manage transactions. (COMMIT, ROLLBACK, START TRANSACTIONS, SAVEPOINT) 1. Data Definition Language (DDL) Data Definition Language (DDL) is a subset of SQL (Structured Query Language) responsible for defining and managing the structure of databases and their objects. DDL commands enable you to create, modify, and delete database objects like tables, indexes, constraints, and more. Key DDL Commands are: CREATE TABLE: ○ Used to create a new table in the database. ○ Specifies the table name, column names, data types, constraints, and more. ○ Example: CREATE TABLE employees (id INT PRIMARY KEY, name VARCHAR(50), salary DECIMAL(10, 2)); ALTER TABLE: ○ Used to modify the structure of an existing table. ○ You can add, modify, or drop columns, constraints, and more. ○ Example: ALTER TABLE employees ADD COLUMN email VARCHAR(100); DROP TABLE: ○ Used to delete an existing table along with its data and structure. ○ Example: DROP TABLE employees;  CREATE INDEX: ○ Used to create an index on one or more columns in a table. ○ Improves query performance by enabling faster data retrieval. ○ Example: CREATE INDEX idx_employee_name ON employees (name); DROP INDEX: ○ Used to remove an existing index from a table. ○ Example: DROP INDEX idx_employee_name; CREATE CONSTRAINT: ○ Used to define constraints that ensure data integrity. ○ Constraints include PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, and CHECK. ○ Example: ALTER TABLE orders ADD CONSTRAINT fk_customer FOREIGN KEY (customer_id) REFERENCES customers(id); DROP CONSTRAINT: ○ Used to remove an existing constraint from a table. ○ Example: ALTER TABLE orders DROP CONSTRAINT fk_customer; TRUNCATE TABLE: ○ Used to delete the data inside a table, but not the table itself. ○ Syntax – TRUNCATE TABLE table_name 2. DATA QUERY/RETRIEVAL LANGUAGE (DQL or DRL) DQL (Data Query Language) is a subset of SQL focused on retrieving data from databases. The SELECT statement is the foundation of DQL and allows us to extract specific columns from a table. SELECT: The SELECT statement is used to select data from a database. Syntax: SELECT column1, column2,... FROM table_name; Here, column1, column2,... are the field names of the table. If you want to select all the fields available in the table, use the following syntax: SELECT * FROM table_name; Ex: SELECT CustomerName, City FROM Customers; WHERE: The WHERE clause is used to filter records. Syntax: SELECT column1, column2,... FROM table_name WHERE condition; Ex: SELECT * FROM Customers WHERE Country='Mexico'; Operators used in WHERE are: = : Equal > : Greater than < : Less than >= : Greater than or equal 50000; - Combining GROUP BY and ORDER BY: ○ You can use both GROUP BY and ORDER BY in the same query to control the order of grouped results. ○ Example: SELECT department, COUNT(*) FROM employees GROUP BY department ORDER BY COUNT(*) DESC; AGGREGATE FUNCTIONS These are used to perform calculations on groups of rows or entire result sets. They provide insights into data by summarising and processing information. Common Aggregate Functions: - COUNT(): Counts the number of rows in a group or result set. - SUM(): Calculates the sum of numeric values in a group or result set. - AVG():  Computes the average of numeric values in a group or result set. - MAX(): Finds the maximum value in a group or result set. - MIN(): Retrieves the minimum value in a group or result set. 3. DATA MANIPULATION LANGUAGE Data Manipulation Language (DML) in SQL encompasses commands that manipulate data within a database. DML allows you to insert, update, and delete records, ensuring the accuracy and currency of your data. INSERT: - The INSERT statement adds new records to a table. - Syntax: INSERT INTO table_name (column1, column2,...) VALUES (value1, value2,...); - Example: INSERT INTO employees (first_name, last_name, salary) VALUES ('John', 'Doe', 50000); UPDATE: - The UPDATE statement modifies existing records in a table. - Syntax: UPDATE table_name SET column1 = value1, column2 = value2,... WHERE condition; - Example: UPDATE employees SET salary = 55000 WHERE first_name = 'John'; DELETE: - The DELETE statement removes records from a table. - Syntax: DELETE FROM table_name WHERE condition; - Example: DELETE FROM employees WHERE last_name = 'Doe'; 4. Data Control Language (DCL) Data Control Language focuses on the management of access rights, permissions, and security-related aspects of a database system. DCL commands are used to control who can access the data, modify the data, or perform administrative tasks within a database. DCL is an important aspect of database security, ensuring that data remains protected and only authorised users have the necessary privileges. There are two main DCL commands in SQL: GRANT and REVOKE. 1. GRANT: The GRANT command is used to provide specific privileges or permissions to users or roles. Privileges can include the ability to perform various actions on tables, views, procedures, and other database objects. Syntax: GRANT privilege_type ON object_name TO user_or_role; In this syntax: privilege_type refers to the specific privilege or permission being granted (e.g., SELECT, INSERT, UPDATE, DELETE). object_name is the name of the database object (e.g., table, view) to which the privilege is being granted. user_or_role is the name of the user or role that is being granted the privilege. Example: Granting SELECT privilege on a table named "Employees" to a user named "Analyst": GRANT SELECT ON Employees TO Analyst; 2. REVOKE: The REVOKE command is used to remove or revoke specific privileges or permissions that have been previously granted to users or roles. Syntax: REVOKE privilege_type ON object_name FROM user_or_role; In this syntax: privilege_type is the privilege or permission being revoked. object_name is the name of the database object from which the privilege is being revoked. user_or_role is the name of the user or role from which the privilege is being revoked. Example: Revoking the SELECT privilege on the "Employees" table from the "Analyst" user: REVOKE SELECT ON Employees FROM Analyst; DCL and Database Security: DCL plays a crucial role in ensuring the security and integrity of a database system. By controlling access and permissions, DCL helps prevent unauthorised users from tampering with or accessing sensitive data. Proper use of GRANT and REVOKE commands ensures that only users who require specific privileges can perform certain actions on database objects. 5. Transaction Control Language (TCL) Transaction Control Language (TCL) deals with the management of transactions within a database. TCL commands are used to control the initiation, execution, and termination of transactions, which are sequences of one or more SQL statements that are executed as a single unit of work. Transactions ensure data consistency, integrity, and reliability in a database by grouping related operations together and either committing or rolling back changes based on the success or failure of those operations. There are three main TCL commands in SQL: COMMIT, ROLLBACK, and SAVEPOINT. 1. COMMIT: The COMMIT command is used to permanently save the changes made during a transaction. It makes all the changes applied to the database since the last COMMIT or ROLLBACK command permanent. Once a COMMIT is executed, the transaction is considered successful, and the changes are made permanent. Example: Committing changes made during a transaction: UPDATE Employees SET Salary = Salary * 1.10 WHERE Department = 'Sales'; COMMIT; 2. ROLLBACK: The ROLLBACK command is used to undo changes made during a transaction. It reverts all the changes applied to the database since the transaction began. ROLLBACK is typically used when an error occurs during the execution of a transaction, ensuring that the database remains in a consistent state. Example: Rolling back changes due to an error during a transaction: BEGIN; UPDATE Inventory SET Quantity = Quantity - 10 WHERE ProductID = 101; -- An error occurs here ROLLBACK; 3. SAVEPOINT: The SAVEPOINT command creates a named point within a transaction, allowing you to set a point to which you can later ROLLBACK if needed. SAVEPOINTs are useful when you want to undo part of a transaction while preserving other changes. Syntax: SAVEPOINT savepoint_name; Example: Using SAVEPOINT to create a point within a transaction: BEGIN; UPDATE Accounts SET Balance = Balance - 100 WHERE AccountID = 123; SAVEPOINT before_withdrawal; UPDATE Accounts SET Balance = Balance + 100 WHERE AccountID = 456; -- An error occurs here ROLLBACK TO before_withdrawal; -- The first update is still applied COMMIT; TCL and Transaction Management: Transaction Control Language (TCL) commands are vital for managing the integrity and consistency of a database's data. They allow you to group related changes into transactions, and in the event of errors, either commit those changes or roll them back to maintain data integrity. TCL commands are used in combination with Data Manipulation Language (DML) and other SQL commands to ensure that the database remains in a reliable state despite unforeseen errors or issues. JOINS In a DBMS, a join is an operation that combines rows from two or more tables based on a related column between them. Joins are used to retrieve data from multiple tables by linking them together using a common key or column. Types of Joins:  1. Inner Join 2. Outer Join 3. Cross Join 4. Self Join 1) Inner Join An inner join combines data from two or more tables based on a specified condition, known as the join condition. The result of an inner join includes only the rows where the join condition is met in all participating tables. It essentially filters out non-matching rows and returns only the rows that have matching values in both tables. Syntax: SELECT columns FROM table1 INNER JOIN table2 ON table1.column = table2.column; Here: columns refers to the specific columns you want to retrieve from the tables. table1 and table2 are the names of the tables you are joining. column is the common column used to match rows between the tables. The ON clause specifies the join condition, where you define how the tables are related. Example: Consider two tables: Customers and Orders. Customers Table: CustomerID CustomerName 1 Alice 2 Bob 3 Carol Orders Table: OrderID CustomerID Product  101 1 Laptop 102 3 Smartphone 103 2 Headphones Inner Join Query: SELECT Customers.CustomerName, Orders.Product FROM Customers INNER JOIN Orders ON Customers.CustomerID = Orders.CustomerID; Result: CustomerName Product Alice Laptop Bob Headphones Carol Smartphone 2) Outer Join Outer joins combine data from two or more tables based on a specified condition, just like inner joins. However, unlike inner joins, outer joins also include rows that do not have matching values in both tables. Outer joins are particularly useful when you want to include data from one table even if there is no corresponding match in the other table. Types: There are three types of outer joins: left outer join, right outer join, and full outer join. 1. Left Outer Join (Left Join): A left outer join returns all the rows from the left table and the matching rows from the right table. If there is no match in the right table, the result will still include the left table's row with NULL values in the right table's columns. Example: SELECT Customers.CustomerName, Orders.Product FROM Customers LEFT JOIN Orders ON Customers.CustomerID = Orders.CustomerID; Result: CustomerName Product Alice Laptop Bob Headphones Carol Smartphone NULL Monitor In this example, the left outer join includes all rows from the Customers table. Since there is no matching customer for the order with OrderID 103 (Monitor), the result includes a row with NULL values in the CustomerName column. 2. Right Outer Join (Right Join): A right outer join is similar to a left outer join, but it returns all rows from the right table and the matching rows from the left table. If there is no match in the left table, the result will still include the right table's row with NULL values in the left table's columns. Example: Using the same Customers and Orders tables. SELECT Customers.CustomerName, Orders.Product FROM Customers RIGHT JOIN Orders ON Customers.CustomerID = Orders.CustomerID; Result:  CustomerName Product Alice Laptop Carol Smartphone Bob Headphones NULL Keyboard Here, the right outer join includes all rows from the Orders table. Since there is no matching order for the customer with CustomerID 4, the result includes a row with NULL values in the CustomerName column. 3. Full Outer Join (Full Join): A full outer join returns all rows from both the left and right tables, including matches and non-matches. If there's no match, NULL values appear in columns from the table where there's no corresponding value. Example: Using the same Customers and Orders tables. SELECT Customers.CustomerName, Orders.Product FROM Customers FULL OUTER JOIN Orders ON Customers.CustomerID = Orders.CustomerID; Result: CustomerName Product Alice Laptop Bob Headphones Carol Smartphone  NULL Monitor NULL Keyboard In this full outer join example, all rows from both tables are included in the result. Both non-matching rows from the Customers and Orders tables are represented with NULL values. 3) Cross Join A cross join, also known as a Cartesian product, is a type of join operation in a Database Management System (DBMS) that combines every row from one table with every row from another table. Unlike other join types, a cross join does not require a specific condition to match rows between the tables. Instead, it generates a result set that contains all possible combinations of rows from both tables. Cross joins can lead to a large result set, especially when the participating tables have many rows. Syntax: SELECT columns FROM table1 CROSS JOIN table2; In this syntax: columns refers to the specific columns you want to retrieve from the cross-joined tables. table1 and table2 are the names of the tables you want to combine using a cross join. Example: Consider two tables: Students and Courses. Students Table: StudentID StudentName 1 Alice  2 Bob Courses Table: CourseID CourseName 101 Maths 102 Science Cross Join Query: SELECT Students.StudentName, Courses.CourseName FROM Students CROSS JOIN Courses; Result: StudentName CourseName Alice Maths Alice Science Bob Maths Bob Science In this example, the cross join between the Students and Courses tables generates all possible combinations of rows from both tables. As a result, each student is paired with each course, leading to a total of four rows in the result set. 4) Self Join A self join involves joining a table with itself. This technique is useful when a table contains hierarchical or related data and you need to compare or analyse rows within the same table. Self joins are commonly used to find relationships, hierarchies, or patterns within a single table. In a self join, you treat the table as if it were two separate tables, referring to them with different aliases. Syntax: The syntax for performing a self join in SQL is as follows: SELECT columns FROM table1 AS alias1 JOIN table1 AS alias2 ON alias1.column = alias2.column; In this syntax: columns refers to the specific columns you want to retrieve from the self-joined table. table1 is the name of the table you're joining with itself. alias1 and alias2 are aliases you assign to the table instances for differentiation. column is the column you use as the join condition to link rows from the same table. Example: Consider an Employees table that contains information about employees and their managers. Employees Table: EmployeeID EmployeeName ManagerID 1 Alice 3 2 Bob 3 3 Carol NULL 4 David 1 Self Join Query: SELECT e1.EmployeeName AS Employee, e2.EmployeeName AS Manager FROM Employees AS e1 JOIN Employees AS e2 ON e1.ManagerID = e2.EmployeeID; Result: Employee Manager  Alice Carol Bob Carol David Alice In this example, the self join is performed on the Employees table to find the relationship between employees and their managers. The join condition connects the ManagerID column in the e1 alias (representing employees) with the EmployeeID column in the e2 alias (representing managers). SET OPERATIONS Set operations in SQL are used to combine or manipulate the result sets of multiple SELECT queries. They allow you to perform operations similar to those in set theory, such as union, intersection, and difference, on the data retrieved from different tables or queries. Set operations provide powerful tools for managing and manipulating data, enabling you to analyse and combine information in various ways. There are four primary set operations in SQL: UNION INTERSECT EXCEPT (or MINUS) UNION ALL 1. UNION: The UNION operator combines the result sets of two or more SELECT queries into a single result set. It removes duplicates by default, meaning that if there are identical rows in the result sets, only one instance of each row will appear in the final result. Example: Assume we have two tables: Customers and Suppliers. Customers Table: CustomerID CustomerName 1 Alice 2 Bob Suppliers Table: SupplierID SupplierName 101 SupplierA 102 SupplierB UNION Query: SELECT CustomerName FROM Customers UNION SELECT SupplierName FROM Suppliers; Result: CustomerName Alice Bob SupplierA SupplierB 2. INTERSECT: The INTERSECT operator returns the common rows that exist in the result sets of two or more SELECT queries. It only returns distinct rows that appear in all result sets. Example: Using the same tables as before. SELECT CustomerName FROM Customers INTERSECT SELECT SupplierName FROM Suppliers; Result: CustomerName In this example, there are no common names between customers and suppliers, so the result is an empty set. 3. EXCEPT (or MINUS): The EXCEPT operator (also known as MINUS in some databases) returns the distinct rows that are present in the result set of the first SELECT query but not in the result set of the second SELECT query. Example: Using the same tables as before. SELECT CustomerName FROM Customers EXCEPT SELECT SupplierName FROM Suppliers; Result: CustomerName Alice Bob In this example, the names "Alice" and "Bob" are customers but not suppliers, so they appear in the result set. 4. UNION ALL: The UNION ALL operator performs the same function as the UNION operator but does not remove duplicates from the result set. It simply concatenates all rows from the different result sets. Example: Using the same tables as before. SELECT CustomerName FROM Customers UNION ALL SELECT SupplierName FROM Suppliers; Result: CustomerName Alice Bob SupplierA SupplierB Difference between Set Operations and Joins Aspect Set Operations Joins Combine data from related Manipulate result sets based on Purpose tables based on specified set theory principles. conditions.  Tables that are related by Data Source Result sets of SELECT queries. common columns. Combine rows from different Combine rows from different Combining Rows result sets. May remove tables based on specified duplicates. conditions. Require the SELECT queries to Can combine columns from have the same number of output Output Columns different tables, regardless of columns and compatible data data types or column numbers. types. Common UNION, INTERSECT, EXCEPT INNER JOIN, LEFT JOIN, RIGHT Operations (MINUS). JOIN, FULL JOIN. Conditional No specific join conditions are Require specified join conditions Requirements required. for combining data. Joins do not inherently handle Handling UNION removes duplicates by duplicates; it depends on the join Duplicates default. type and data.  Useful for combining and Used to retrieve and relate data Usage Scenarios analysing related data from from different tables based on different queries or tables. their relationships. Result sets may have different Result sets can have different Result Set column names, but data types and column names, data types, and Structure counts must match. counts. Joins can be more complex and Performance Generally faster and less complex resource-intensive, especially for Considerations than joins. larger datasets. SUB QUERIES Subqueries, also known as nested queries or inner queries, allow you to use the result of one query (the inner query) as the input for another query (the outer query). Subqueries are often used to retrieve data that will be used for filtering, comparison, or calculation within the context of a larger query. They are a way to break down complex tasks into smaller, manageable steps. Syntax: SELECT columns FROM table WHERE column OPERATOR (SELECT column FROM table WHERE condition); In this syntax: columns refers to the specific columns you want to retrieve from the outer query. table is the name of the table you're querying. column is the column you're applying the operator to in the outer query. OPERATOR is a comparison operator such as =, >, (SELECT AVG(Price) FROM Products); Result: ProductName Quantity Laptop 2 Differences Between Subqueries and Joins: Aspect Subqueries Joins Retrieve data for filtering, comparison, or calculation Combine data from related tables Purpose within the context of a larger based on specified conditions. query. Result of one query used as Data Source Data from multiple related tables. input for another query. Not used for combining rows; Combines rows from different tables Combining Rows used to filter or evaluate data. based on specified join conditions. Subqueries return scalar Result Set Joins return multi-column result values, single-column results, Structure sets. or small result sets. Subqueries can be slower and Performance Joins can be more efficient for less efficient, especially when Considerations combining data from multiple tables. dealing with large datasets. Joins can become complex, but are Subqueries can be easier to more suited for handling large-scale Complexity understand for simple tasks or data retrieval and combination smaller datasets. tasks. Subqueries can be used in Joins are primarily used in the Versatility various clauses: WHERE, FROM clause for combining tables. FROM, HAVING, etc.