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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...

How to Write ETL Logic in Python: Sample Code to Practice

Here's an example Python code that uses the mysql-connector library to connect to a MySQL database, extract data from a table, transform it, and load it as a JSON file. Here's an example:







Python ETL Sample Code


import mysql.connector

import json


# Connect to the MySQL database

cnx = mysql.connector.connect(user='username', password='password',

                              host='localhost',

                              database='database_name')


# Define a cursor to execute SQL queries

cursor = cnx.cursor()


# Define the SQL query to extract data

query = ("SELECT column1, column2, column3 FROM table_name")


# Execute the SQL query

cursor.execute(query)


# Fetch all rows from the result set

rows = cursor.fetchall()


# Transform the rows into a list of dictionaries

result = []

for row in rows:

    result.append({'column1': row[0], 'column2': row[1], 'column3': row[2]})


# Save the result as a JSON file

with open('output.json', 'w') as outfile:

    json.dump(result, outfile)


# Close the cursor and database connection

cursor.close()

cnx.close()

In this example, you will need to replace username, password, localhost, database_name, table_name, column1, column2, and column3 with the appropriate values for your MySQL database and table. 


The code will extract the data from the specified table, transform it into a list of dictionaries, and save it as a JSON file named output.json.

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