Week 2: Advanced PostgreSQL Queries and Data Management

Week 2: Advanced PostgreSQL Queries and Data Management (Days 8–14)

In Week 2 of your PostgreSQL learning journey, you will build upon your knowledge of basic SQL commands. This week focuses on more advanced queries, data management techniques, and understanding how PostgreSQL handles data integrity, constraints, and complex queries. By the end of this week, you’ll be ready to tackle more complex database operations with confidence.

Day 8: Complex Joins in PostgreSQL

Types of Joins:
Learn about different types of joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN.
Understand how these joins work and when to use each type in your queries.

Example:

-- INNER JOIN: Retrieve all orders with user details
SELECT users.name, orders.product 
FROM users 
INNER JOIN orders ON users.id = orders.user_id;

Multiple Joins:
Practice joining multiple tables together to create more complex queries.

Example:

-- Multiple Joins: Retrieve user, order, and payment details
SELECT users.name, orders.product, payments.amount
FROM users
INNER JOIN orders ON users.id = orders.user_id
INNER JOIN payments ON orders.id = payments.order_id;

Day 9: Subqueries

What Are Subqueries?
Learn how to use subqueries in SELECT, INSERT, UPDATE, and DELETE statements.
Understand the difference between correlated and non-correlated subqueries.

Example:

-- Subquery Example: Select users who have placed orders
SELECT name 
FROM users 
WHERE id IN (SELECT user_id FROM orders);

Using Subqueries in FROM Clause:
Learn how to use subqueries as derived tables within the FROM clause for more complex queries.

Example:

-- Subquery in FROM clause: Count orders per user
SELECT user_id, COUNT(*) AS order_count
FROM (SELECT user_id FROM orders) AS user_orders
GROUP BY user_id;

Day 10: Aggregate Functions

Understanding Aggregate Functions:
Learn about PostgreSQL aggregate functions like COUNT(), SUM(), AVG(), MIN(), and MAX().
Use aggregate functions with GROUP BY to summarize data.

Example:

-- Aggregate Function Example: Calculate total amount spent per user
SELECT user_id, SUM(amount) AS total_spent
FROM payments
GROUP BY user_id;

Using HAVING with Aggregate Functions:
Learn how to filter groups using the HAVING clause after aggregation.

Example:

-- Filter aggregated results: Users who spent more than $100
SELECT user_id, SUM(amount) AS total_spent
FROM payments
GROUP BY user_id
HAVING SUM(amount) > 100;

Day 11: Data Integrity and Constraints

Understanding Constraints:
Learn how to use constraints like NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, and CHECK to ensure data integrity in PostgreSQL.

Example:

-- Create a table with constraints: Users table with UNIQUE and PRIMARY KEY
CREATE TABLE users (
    id SERIAL PRIMARY KEY,
    name VARCHAR(100) NOT NULL UNIQUE,
    age INT CHECK (age > 18)
);

Foreign Keys and Relationships:
Learn how to define and use foreign keys to maintain relationships between tables.

Example:

-- Foreign Key Example: Link orders to users
CREATE TABLE orders (
    id SERIAL PRIMARY KEY,
    user_id INT REFERENCES users(id),
    product VARCHAR(100)
);

Day 12: Transactions and ACID Properties

What Are Transactions?
Understand transactions and their ACID properties (Atomicity, Consistency, Isolation, Durability).
Using Transactions in PostgreSQL:
Learn how to begin, commit, and roll back transactions to ensure data consistency.

Example:

-- Transaction Example: Transfer money between two users
BEGIN;

UPDATE users SET balance = balance - 100 WHERE id = 1;
UPDATE users SET balance = balance + 100 WHERE id = 2;

COMMIT;

Handling Transaction Rollbacks:
Understand how to handle errors and rollback transactions to maintain data integrity.

Example:

-- Rollback Example: Cancel changes if there's an error
BEGIN;

UPDATE users SET balance = balance - 100 WHERE id = 1;
UPDATE users SET balance = balance + 100 WHERE id = 2;

-- Simulate an error
ROLLBACK;

Day 13: Indexes in PostgreSQL

What Are Indexes?
Learn how indexes speed up query performance by providing faster lookups on large datasets.
Creating and Using Indexes:
Practice creating indexes on frequently queried columns to optimize your queries.

Example:

-- Create an index on the 'name' column of the users table
CREATE INDEX idx_users_name ON users(name);

Types of Indexes:
Learn about different index types such as B-tree, Hash, and GIN and when to use them.

Day 14: Views and Materialized Views

What Are Views?
Understand how views provide a virtual table for frequently used queries.
Creating and Using Views:
Learn how to create views to simplify complex queries.

Example:

-- Create a view for all users who placed an order
CREATE VIEW user_orders AS
SELECT users.name, orders.product
FROM users
INNER JOIN orders ON users.id = orders.user_id;

Materialized Views:
Learn how materialized views differ from regular views and how they store the query results for faster access.

Example:

-- Create a materialized view for faster access to aggregated data
CREATE MATERIALIZED VIEW user_summary AS
SELECT user_id, COUNT(*) AS order_count
FROM orders
GROUP BY user_id;

Conclusion

By the end of Week 2, you will have a strong grasp of advanced PostgreSQL concepts, including complex joins, subqueries, aggregate functions, and data integrity constraints. You’ll be able to optimize your queries with indexes and create views for simplified access to data. In the next week, you’ll deepen your understanding of PostgreSQL by learning about performance tuning, optimization, and more complex database management techniques.

Keep practicing and stay tuned for Week 3, where we’ll focus on advanced PostgreSQL features like optimization, performance analysis, and more!

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Week 2: Advanced PostgreSQL Queries and Data Management