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Update README.md
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339 changes: 339 additions & 0 deletions Postgre_SQL/postGre_tutorial.txt
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🚀 Phase 1: Introduction to PostgreSQL
✅ What is PostgreSQL?
PostgreSQL is a powerful, open-source, object-relational database system. It supports:

ACID compliance
1. Complex queries
2. Joins
3. Transactions
4. Custom functions
5. JSON, Arrays, Triggers, and much more


🔹 Step 1: Create a Database Table
Paste the following in the Schema SQL box on DB Fiddle:

CREATE TABLE students (
id SERIAL PRIMARY KEY,
name VARCHAR(100) NOT NULL,
age INT CHECK (age > 0),
enrolled_on DATE DEFAULT CURRENT_DATE
);

🔹 Step 2: Insert Data
In the SQL Query box, enter:

INSERT INTO students (name, age) VALUES
('Alice', 20),
('Bob', 22),
('Charlie', 19);


🧠 Explanation

SQL Command Purpose
CREATE TABLE Creates a new table
SERIAL Auto-incrementing integer
PRIMARY KEY Uniquely identifies rows
VARCHAR(100) Text with max 100 chars
NOT NULL Field cannot be empty
CHECK Validates input


| Clause | Use |
| ------------ | --------------------------------------------- |
| WHERE | Filters rows |
| `BETWEEN` | Checks value in a range |
| `IN` | Matches any value in a list |
| `LIKE/ILIKE` | Pattern matching (case sensitive/insensitive) |
| `ORDER BY` | Sort results |
| `LIMIT` | Restrict number of results |
| `OFFSET` | Skip rows |
| `AS` | Rename columns |



* DATATYPES
-------------

| Category | Data Type | Example |
| -------------- | -------------------- | ----------------------------- |
| Integer | `INT`, `SERIAL` | `age INT = 25` |
| Floating Point | `NUMERIC(p,s)` | `salary NUMERIC(8,2)` |
| Text | `VARCHAR(n)`, `TEXT` | `name VARCHAR(100)` |
| Date/Time | `DATE`, `TIMESTAMP` | `join_date DATE` |
| Boolean | `BOOLEAN` | `active BOOLEAN = TRUE` |
| JSON/Array | `JSON`, `TEXT[]` | `details JSON`, `tags TEXT[]` |

* CONSTRAINTS
---------------

| Constraint | Purpose |
| ------------- | -------------------------------------------- |
| `NOT NULL` | Column must have a value |
| `UNIQUE` | All values must be different |
| `PRIMARY KEY` | Uniquely identifies rows (NOT NULL + UNIQUE) |
| `FOREIGN KEY` | Links to primary key in another table |
| `CHECK` | Ensures condition is true |
| `DEFAULT` | Sets default value |


OPERATORS
-------------

You can use operators like:

1) (=, !=, >, <, >=, <=)

2) (AND, OR, NOT)


Functions and Expression
-----------------------------

Function Description

COUNT(*) Counts the number of all rows.
COUNT(column_name) Counts the number of non-NULL values in a column.
COUNT(DISTINCT column_name) Counts the number of unique, non-NULL values in a column.
SUM(column_name) Calculates the sum of a set of numbers.
AVG(column_name) Calculates the average of a set of numbers.
MAX(column_name) Finds the maximum value in a set of values.
MIN(column_name) Finds the minimum value in a set of values.
ARRAY_AGG(column_name) Aggregates all input values (including NULLs) into an array.
STRING_AGG(column_name, delimiter) Concatenates non-NULL input values into a string, separated by a specified delimiter.
BOOL_AND(column_name) Returns true if all input values are true.
BOOL_OR(column_name) Returns true if at least one input value is true.
EVERY(column_name) Equivalent to BOOL_AND().

Export to Sheets

Statistical Aggregate Functions
Function Description
CORR(Y, X) Calculates the correlation coefficient between two sets of numbers.
COVAR_POP(Y, X) Calculates the population covariance.
COVAR_SAMP(Y, X) Calculates the sample covariance.
REGR_SLOPE(Y, X) Calculates the slope of the least-squares-fit linear equation.
REGR_INTERCEPT(Y, X) Calculates the y-intercept of the least-squares-fit linear equation.
REGR_COUNT(Y, X) Counts the number of non-NULL input pairs.

Export to Sheets
JSON/XML Aggregate Functions
Function Description
JSON_AGG(value) Aggregates values as a JSON array.
JSONB_AGG(value) Aggregates values as a JSONB array.
JSON_OBJECT_AGG(name, value) Aggregates name/value pairs into a JSON object.
JSONB_OBJECT_AGG(name, value) Aggregates name/value pairs into a JSONB object.
XMLAGG(value) Concatenates non-NULL XML values.

CONDITIONALS
---------------
_____________________________________________
|SELECT title, |
| CASE |
| WHEN price >= 500 THEN 'Expensive'|
| WHEN price >= 300 THEN 'Moderate' |
| ELSE 'Cheap' |
| END AS price_category |
|FROM books; |
----------------------------------------------

JOIN
------

Joins
├── INNER JOIN
│ └── Returns matching rows from both tables
│
├── OUTER JOIN
│ ├── LEFT JOIN
│ │ └── All from LEFT + matched from RIGHT
│ ├── RIGHT JOIN
│ │ └── All from RIGHT + matched from LEFT
│ └── FULL JOIN
│ └── All from BOTH sides, matched where possible
│
└── CROSS JOIN
└── Cartesian product: every row of A × every row of B


Inner-join
_______________________________
|SELECT * FROM A |
|INNER JOIN B ON A.id = B.a_id;|
--------------------------------

Left-Join
______________________________
|SELECT * FROM A |
|LEFT JOIN B ON A.id = B.a_id;|
------------------------------

Right-Join
______________________________
|SELECT * FROM A |
|RIGHT JOIN B ON A.id = B.a_id;|
-------------------------------

Full-Join
_______________________________________________________
|SELECT b.title, a.name AS authorFROM books b |
|FULL OUTER JOIN authors a ON b.author_id = a.author_id;|
---------------------------------------------------------

Cross-Join
_____________________________________
|SELECT a.name, b.titleFROM authors a |
|CROSS JOIN books b; |
--------------------------------------

SUBQUERIES
------------
A subquery is a query nested inside another query.

Scalar Subquery
->Returns one single value.
_____________________________________________
|SELECT name, price FROM books |
|WHERE price > (SELECT AVG(price) FROM books);|
----------------------------------------------

Table Subquery
->Acts like a table.
_______________________________________________________
|SELECT * FROM (SELECT * FROM books WHERE price > 500) |
|AS expensive_books; |
--------------------------------------------------------

Correlated Subquery
->Refers to the outer query.
_______________________________________________________________________________________
|SELECT nameFROM authors a |
|WHERE EXISTS (SELECT 1 FROM books b WHERE b.author_id = a.author_id AND b.price > 600);|
----------------------------------------------------------------------------------------

Set Operations
These operations combine rows from two or more queries.

🔸 A. UNION
Combines results and removes duplicates.
_______________________________
|SELECT name FROM authors UNION |
|SELECT title FROM books; |
---------------------------------

🔸 B. UNION ALL
Same as UNION but keeps duplicates.
___________________________________
|SELECT name FROM authors UNION ALL |
|SELECT title FROM books; |
-------------------------------------

🔸 C. INTERSECT
Returns rows common to both queries.
____________________________________
|SELECT author_id FROM booksINTERSECT|
|SELECT author_id FROM authors; |
------------------------------------
🔸 D. EXCEPT
____________________________________
|SELECT author_id FROM authorsEXCEPT |
|SELECT author_id FROM books; |
--------------------------------------
Data Modeling

Data modeling is the process of organizing and structuring your database tables to:

Avoid redundancy
1)Ensure data integrity
2)Support efficient querying


| Relationship | Description | Example |
| ---------------- | ------------------------------ | ------------------ |
| One-to-One | One row in A matches one in B | Person ↔ Passport |
| One-to-Many | One row in A maps to many in B | Author → Books |
| Many-to-Many | Multiple rows in A relate to B | Students ↔ Courses |


Database Normalization : Normalization reduces redundancy and improves consistency.

->First Normal Form (1NF)

-Eliminate repeating groups and arrays.
-Use separate rows instead.
_____________________________________
| Bad (not 1NF) |
|name: "John" |
|hobbies: "Reading, Swimming, Coding" |
| |
| Good (1NF) |
|name: "John", hobby: "Reading" |
|name: "John", hobby: "Swimming" |
---------------------------------------

📦 Second Normal Form (2NF)
-Remove partial dependencies (when a column depends only on part of a composite key).

📦 Third Normal Form (3NF)
-Remove transitive dependencies (columns depending on other non-key columns).
___________________________________________________
| Bad |
|employees(emp_id, name, dept_name, dept_location) |
| |
| Better (3NF) |
|departments(dept_id, dept_name, dept_location) |
|employees(emp_id, name, dept_id) |
---------------------------------------------------


Views, Indexes, and Materialized Views
-----------------------------------------
These features help with:

-Simplifying complex queries (Views)
-Improving performance (Indexes)
-Storing query results like a snapshot (Materialized Views)


VIEWS
_______________________________
|CREATE VIEW expensive_books AS |
|SELECT title, price FROM books |
|WHERE price > 500; |
---------------------------------
_______________________________
|SELECT * FROM expensive_books; |
--------------------------------

INDEXES

An index is like a table of contents — it speeds up searches on large tables.
_____________________________________________
|CREATE INDEX idx_books_price ON books(price);|
----------------------------------------------
_______________________________________________________________
|CREATE INDEX idx_books_price_author ON books(price, author_id);|
-----------------------------------------------------------------

Materialized Views
A materialized view stores the result of a query physically (like a snapshot).

______________________________________
|CREATE MATERIALIZED VIEW top_books AS |
|SELECT * FROM books WHERE price > 600;|
----------------------------------------

Transactions

A transaction is a group of operations that are executed as a single unit.
Either all operations succeed, or none do.
______________________________________________________________________
| Property | Description |
| --------------- | -------------------------------------------------- |
| **Atomicity** | All operations in a transaction succeed or none do |
| **Consistency** | DB moves from one valid state to another |
| **Isolation** | Concurrent transactions don’t interfere |
| **Durability** | Once committed, changes persist even after crashes |
-----------------------------------------------------------------------

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