Skip to content

ercan5535/Structured-Streaming-Flask-Kafka-PySpark-Elasticsearch-Kibana-

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

23 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Structured Streaming

In this project I created a structured streaming with common technologies.
It was a good practice to use these technologies while working together.

  • Producer:
    Simple Flask App by ordering food and beverages.
    Flask App get that data and load to Kafka topic for every order.

  • Consumer:
    Spark Session to read stream from Kafka topic.
    PySpark reads streaming from Kafka, does some data processing and writes to Elasticsearch.

  • Visualization:
    Kibana to visualize Elasticsearch data.
    Elasticsearch index and Kibana dashboard operations handled by init_db

Pipeline


Flask App

Kibana Dashboard

Starting Services

Docker versions

$ sudo docker-compose up
is fine to start all services in proper sequence.

Usage

Flask App: localhost:5000
Kibana Dashboard: localhost:5602