PawMark: Platform For Big Data & AI

Summary

PawMark is a platform for big data and AI. It is based on Apache Spark and Kubernetes. The platform is designed to be scalable and easy to use. It provides a set of tools for data processing, machine learning, and data visualization.

Setup

Docker Compose

Details

• Start docker-compose

  docker-compose up -d

• Access platform UI

  • http://localhost:5001

• Use notebook

  • Access http://localhost:8888
  • Spark session is automatically created
    • Run spark in cell to check the spark session
  • Run the following code in the notebook to test the spark session

    spark.range(0, 5) \
      .write.format("delta").mode("overwrite").saveAsTable("test")

• Check the history server

  • Access http://localhost:18080
  • Spark application history / progress can be viewed here

• Delta tables

  • Use /opt/data/delta-table/ as the root directory for delta tables

• Schedule with Airflow

  • Access http://localhost:8090
  • Use the default username and password to login
  • Create a new DAG to schedule the spark job
  • Or use the example DAGs in the ./dags folder

MiniKube

• TODO

Examples

Basic Analysis on Static Tables

• Singapore Resale Flat Prices Analysis
  • Notebook
  • Data Source

Incremental Pipeline

• TODO

Docker Images

WebApp

• Dockerfile

Server

• Dockerfile

Spark

• Dockerfile
• Includes
  • Spark
  • Python

Notebook

• Dockerfile
• Includes
  • Jupyter Notebook
  • Spark
  • Google Cloud SDK
  • GCS Connector
  • Pyspark Startup Script
  • Notebook Save Hook Function

History Server

• Dockerfile
• Includes
  • Spark
  • GCS Connector

Airflow

• Dockerfile
• Includes
  • Python
  • Java
  • pyspark

Versions

Details

Component	Version
Scala	2.12
Java	17
Python	3.11
IPython	8.16.1
Apache Spark	3.5.0
Delta Lake	3.0.0
Airflow	2.9.1
Postgres	13
React	18.3.1

License

This project is licensed under the terms of the Apache-2.0 license.

Reference

• Running Apache Spark on Kubernetes
• spark-docker