శ్రీ కృష్ణాష్టోత్తర శతనామావళి

SQL (Structured Query Language) is a domain-specific language used for managing and manipulating relational databases. Here, I will provide a deep explanation of various SQL concepts, commands, and techniques.

1. Basic Concepts

1.1. Tables

• Tables are the fundamental storage objects in a relational database.
• A table is composed of rows and columns.
• Rows represent individual records.
• Columns represent the attributes of the data.

1.2. Schema

• A schema is a logical container for database objects such as tables, views, and indexes.
• It helps in organizing and grouping database objects.

1.3. Data Types

• Data types define the nature of data that can be stored in a column (e.g., INTEGER, VARCHAR, DATE).

2. Data Definition Language (DDL)

DDL commands are used to define and modify database structures.

2.1. CREATE

• CREATE is used to create new database objects.

CREATE TABLE employees ( employee_id INT PRIMARY KEY, first_name VARCHAR(50), last_name VARCHAR(50), hire_date DATE );

2.2. ALTER

• ALTER is used to modify existing database objects.

ALTER TABLE employees ADD COLUMN salary DECIMAL(10, 2);

2.3. DROP

• DROP is used to delete database objects.

DROP TABLE employees;

3. Data Manipulation Language (DML)

DML commands are used for managing data within database objects.

3.1. SELECT

• SELECT is used to retrieve data from the database.

SELECT first_name, last_name FROM employees WHERE hire_date > '2020-01-01';

3.2. INSERT

• INSERT is used to add new records to a table.

INSERT INTO employees (employee_id, first_name, last_name, hire_date) VALUES (1, 'John', 'Doe', '2021-06-15');

3.3. UPDATE

• UPDATE is used to modify existing records.

UPDATE employees SET salary = 60000 WHERE employee_id = 1;

3.4. DELETE

• DELETE is used to remove records from a table.

DELETE FROM employees WHERE employee_id = 1;

4. Data Control Language (DCL)

DCL commands are used to control access to data in the database.

4.1. GRANT

• GRANT is used to give privileges to users.

GRANT SELECT, INSERT ON employees TO user1;

4.2. REVOKE

• REVOKE is used to remove privileges from users.

REVOKE SELECT, INSERT ON employees FROM user1;

5. Transaction Control Language (TCL)

TCL commands are used to manage transactions in the database.

5.1. COMMIT

• COMMIT is used to save all changes made during the current transaction.

COMMIT;

5.2. ROLLBACK

• ROLLBACK is used to undo changes made during the current transaction.

ROLLBACK;

5.3. SAVEPOINT

• SAVEPOINT is used to set a point within a transaction to which you can later roll back.

SAVEPOINT savepoint1;

6. Advanced SQL Concepts

6.1. Joins

• Joins are used to combine rows from two or more tables based on related columns.

INNER JOIN

SELECT employees.first_name, departments.department_name FROM employees INNER JOIN departments ON employees.department_id = departments.department_id;

LEFT JOIN

SELECT employees.first_name, departments.department_name FROM employees LEFT JOIN departments ON employees.department_id = departments.department_id;

RIGHT JOIN

SELECT employees.first_name, departments.department_name FROM employees RIGHT JOIN departments ON employees.department_id = departments.department_id;

FULL JOIN

SELECT employees.first_name, departments.department_name FROM employees FULL JOIN departments ON employees.department_id = departments.department_id;

6.2. Subqueries

• Subqueries are nested queries used within another SQL query.

SELECT first_name, last_name FROM employees WHERE employee_id IN (SELECT employee_id FROM project_assignments WHERE project_id = 1);

6.3. Indexes

• Indexes are used to speed up the retrieval of rows by using a pointer.

CREATE INDEX idx_employee_last_name ON employees (last_name);

6.4. Views

• Views are virtual tables created by a query.

CREATE VIEW employee_details AS SELECT first_name, last_name, department_name FROM employees JOIN departments ON employees.department_id = departments.department_id;

6.5. Stored Procedures and Functions

• Stored procedures are SQL code that you can save and reuse.
• Functions are similar to stored procedures but can return a value.

CREATE PROCEDURE GetEmployeeDetails (IN emp_id INT) BEGIN SELECT first_name, last_name FROM employees WHERE employee_id = emp_id; END; CREATE FUNCTION CalculateBonus (salary DECIMAL) RETURNS DECIMAL BEGIN RETURN salary * 0.10; END;

7. SQL Optimization

7.1. Query Optimization

• Use indexes appropriately.
• Avoid using SELECT *; specify needed columns.
• Use joins instead of subqueries when possible.
• Analyze and update statistics.

7.2. Index Optimization

• Create indexes on columns that are frequently used in WHERE clauses, joins, and ORDER BY clauses.
• Avoid over-indexing, which can slow down DML operations.

8. SQL Standards

8.1. SQL-92

• A major revision of the SQL standard that introduced features like CASE expressions and enhanced join operations.

8.2. SQL:1999

• Introduced features like triggers, recursive queries, and user-defined types.

8.3. SQL:2003

• Added XML-related features, window functions, and more.

8.4. SQL:2011

• Introduced support for temporal databases, allowing for time-based queries.

Conclusion

SQL is a powerful language for managing and manipulating relational databases. Mastering SQL involves understanding its various commands and features, from basic data retrieval and manipulation to advanced concepts like joins, subqueries, and optimization techniques. By learning and practicing these concepts, you can efficiently work with databases to store, retrieve, and analyze data.

Let's dive even deeper into some advanced SQL topics and techniques.

9. Advanced Joins

9.1. Self Join

• A self join is a regular join, but the table is joined with itself.

SELECT a.employee_id, a.first_name, b.first_name AS manager_name FROM employees a JOIN employees b ON a.manager_id = b.employee_id;

9.2. Cross Join

• A cross join returns the Cartesian product of the two tables, combining all rows from one table with all rows from another.

SELECT a.first_name, b.department_name FROM employees a CROSS JOIN departments b;

10. Common Table Expressions (CTEs)

• CTEs are temporary result sets that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement.

WITH Sales_CTE AS ( SELECT salesperson_id, SUM(sales_amount) AS total_sales FROM sales GROUP BY salesperson_id ) SELECT salesperson_id, total_sales FROM Sales_CTE WHERE total_sales > 10000;

11. Window Functions

• Window functions perform a calculation across a set of table rows that are somehow related to the current row.

11.1. ROW_NUMBER()

• Assigns a unique number to each row in a result set.

SELECT employee_id, first_name, last_name, ROW_NUMBER() OVER (PARTITION BY department_id ORDER BY hire_date) AS row_num FROM employees;

11.2. RANK() and DENSE_RANK()

• RANK() provides the rank of rows within the partition of a result set.
• DENSE_RANK() is similar to RANK(), but it does not leave gaps in the ranking sequence.

SELECT employee_id, first_name, last_name, RANK() OVER (PARTITION BY department_id ORDER BY hire_date) AS rank FROM employees;

11.3. NTILE()

• Divides the result set into a specified number of roughly equal groups.

SELECT employee_id, first_name, last_name, NTILE(4) OVER (ORDER BY hire_date) AS quartile FROM employees;

11.4. LAG() and LEAD()

• LAG() provides access to a row at a given physical offset that comes before the current row.
• LEAD() provides access to a row at a given physical offset that comes after the current row.

SELECT employee_id, first_name, last_name, LAG(salary, 1) OVER (ORDER BY hire_date) AS previous_salary, LEAD(salary, 1) OVER (ORDER BY hire_date) AS next_salary FROM employees;

12. Advanced Subqueries

12.1. Correlated Subqueries

• A correlated subquery is a subquery that uses values from the outer query.

SELECT employee_id, first_name, salary FROM employees e1 WHERE salary > (SELECT AVG(salary) FROM employees e2 WHERE e1.department_id = e2.department_id);

12.2. EXISTS and NOT EXISTS

• EXISTS is used to test for the existence of rows in a subquery.

SELECT first_name, last_name FROM employees e WHERE EXISTS (SELECT 1 FROM sales s WHERE s.employee_id = e.employee_id);

13. Indexing Strategies

• Proper indexing is crucial for database performance.

13.1. Composite Indexes

• Composite indexes are indexes on multiple columns.

CREATE INDEX idx_emp_dept ON employees (department_id, hire_date);

13.2. Covering Indexes

• A covering index includes all the columns needed by a query, eliminating the need to access the table.

CREATE INDEX idx_covering ON employees (first_name, last_name, hire_date);

13.3. Unique Indexes

• Unique indexes ensure that the indexed columns do not have duplicate values.

CREATE UNIQUE INDEX idx_unique_email ON employees (email);

14. Full-Text Search

• Full-text search allows for searching within text columns.

14.1. Creating Full-Text Indexes

CREATE FULLTEXT INDEX ft_idx ON documents (content);

14.2. Using Full-Text Search

SELECT * FROM documents WHERE MATCH(content) AGAINST('database optimization');

15. Database Normalization and Denormalization

15.1. Normalization

• The process of organizing data to reduce redundancy.

First Normal Form (1NF): Ensure each column contains atomic values. Second Normal Form (2NF): Ensure it is in 1NF and all non-key attributes are fully functional dependent on the primary key. Third Normal Form (3NF): Ensure it is in 2NF and all the attributes are only dependent on the primary key.

15.2. Denormalization

• The process of combining tables to improve read performance.

16. Advanced Transaction Management

16.1. Isolation Levels

• Isolation levels control the visibility of changes made in a transaction to other transactions.

READ UNCOMMITTED: Transactions can read uncommitted changes from other transactions. READ COMMITTED: Transactions can only read committed changes from other transactions. REPEATABLE READ: Ensures that if a row is read twice in the same transaction, it will have the same values. SERIALIZABLE: Ensures complete isolation from other transactions.

SET TRANSACTION ISOLATION LEVEL SERIALIZABLE; BEGIN TRANSACTION; -- Your transactional SQL code here COMMIT;

17. Partitioning

• Partitioning is dividing a large table into smaller, more manageable pieces.

17.1. Horizontal Partitioning

• Dividing a table into multiple tables based on row values.

CREATE TABLE employees_2021 PARTITION OF employees FOR VALUES FROM ('2021-01-01') TO ('2021-12-31');

17.2. Vertical Partitioning

• Dividing a table into smaller tables based on column values.

CREATE TABLE employee_names AS SELECT employee_id, first_name, last_name FROM employees; CREATE TABLE employee_details AS SELECT employee_id, hire_date, salary FROM employees;

18. Recursive Queries

• Recursive queries are used to deal with hierarchical or tree-structured data.

WITH RECURSIVE EmployeeHierarchy AS ( SELECT employee_id, manager_id, first_name, last_name FROM employees WHERE manager_id IS NULL UNION ALL SELECT e.employee_id, e.manager_id, e.first_name, e.last_name FROM employees e INNER JOIN EmployeeHierarchy eh ON e.manager_id = eh.employee_id ) SELECT * FROM EmployeeHierarchy;

19. JSON in SQL

• Many modern SQL databases support JSON data types and functions.

19.1. Storing JSON Data

CREATE TABLE orders ( order_id INT PRIMARY KEY, order_data JSON );

19.2. Querying JSON Data

SELECT order_id, order_data->>'$.customer.name' AS customer_name FROM orders;

20. Error Handling in SQL

20.1. TRY...CATCH

BEGIN TRY -- SQL statements INSERT INTO employees (employee_id, first_name, last_name) VALUES (1, 'Jane', 'Doe'); END TRY BEGIN CATCH -- Error handling code PRINT 'An error occurred'; END CATCH;

Conclusion

This comprehensive overview provides a deeper understanding of SQL, covering advanced concepts such as window functions, CTEs, indexing strategies, normalization, transaction management, partitioning, recursive queries, and JSON handling. Mastery of these topics will significantly enhance your ability to manage and optimize relational databases, leading to better performance and more efficient data handling.