This project implements a scalable web data ingestion pipeline using Apache NiFi, Kafka, and MySQL. It captures website session cookies and logs, stores the data in a MySQL database, and intelligently routes specific data subsets to designated destinations.

Before getting started, ensure that you have the following requirements installed on your system:

• Apache NiFi: Download and install Apache NiFi from https://nifi.apache.org/download.html.

• Kafka: Install Apache Kafka by following the instructions at https://kafka.apache.org/quickstart.

• Python: Ensure you have Python installed on your system. You can download it from https://www.python.org/downloads/.

• kafka-python library: Install the kafka-python library using pip: pip install kafka-python

• Zookeeper: Kafka requires ZooKeeper. You can download and install ZooKeeper from https://zookeeper.apache.org/releases.html.

• Java: Make sure you have Java (JRE or JDK) installed. You can download it from https://www.oracle.com/java/technologies/javase-downloads.html.

• MySQL: Install MySQL, and configure it as needed. You can download MySQL from https://dev.mysql.com/downloads/installer/.

1. Set Up Kafka and Zookeeper:

   • Start Zookeeper and Kafka Broker.

2. Kafka Topic and Producer:

   • Create the "cookie_logs" Kafka topic.
   • Optionally, start a Kafka Producer server for manual data production.

3. Optional: Create Kafka Consumer:

   • Optionally, create a Kafka Consumer for testing and monitoring data.

4. Start Apache NiFi:

   • Launch the Apache NiFi server for data consumption and processing.

1. Generate Website Logs:

   • Use kafka_prod.py to create synthetic website logs with Faker.

2. Initialize Kafka Producer:

   • Configure a Kafka Producer to send data as JSON to Kafka.

3. Send Data to Kafka:

   • Execute the script to send 1000 generated log entries to the "cookie-logs" Kafka topic.

1. Start MySQL Server:

   • Start MySQL server based on your system's requirements.

2. Connect to MySQL:

   • Use the mysql command to connect to the MySQL server with credentials.

3. Create Database and Table:

   • Execute SQL commands to create the cookie_logs database and define the logs table.

• Import the NiFi pipeline XML file cookie_logs.xml to set up the dataflow for processing and storing the ingested data.

These steps will help you set up and run your web data ingestion pipeline efficiently. Ensure that you have the necessary dependencies installed before proceeding.