Realtime Socket Streaming with Apache Spark - End-to-End Data Engineering Project

Overview

Build a real-time data streaming pipeline processing 7 million records using TCP/IP Socket, Apache Spark, OpenAI Large Language Model (LLM), Kafka, and Elasticsearch. Learn to configure TCP/IP for data transmission, stream data with Apache Spark, perform real-time sentiment analysis using OpenAI LLM (ChatGPT), set up Kafka for data ingestion and distribution, and utilize Elasticsearch for efficient indexing and search. Follow along to create a Spark Master-worker architecture with Docker, set up TCP IP Socket Source Stream, configure Apache Spark Stream, establish a Kafka Cluster on Confluent Cloud, integrate real-time sentiment analysis, deploy Elasticsearch on Elastic Cloud, and perform real-time data indexing. Gain hands-on experience in prompt engineering and test the complete pipeline to see the results of this comprehensive data engineering project.

Syllabus

Introduction
Creating Spark Master-worker architecture with Docker
Setting up the TCP IP Socket Source Stream
Setting up Apache Spark Stream
Setting up Kafka Cluster on confluent cloud
Getting Keys for Kafka cluster and Schema Registry
Realtime Sentiment Analysis with OpenAI LLM ChatGPT
Setting up Elasticsearch deployment on Elastic cloud
Realtime Data Indexing on Elasticsearch
Testing and Results
Outro