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PawMark is a platform for developers to build, schedule and monitor data pipelines.

License: Apache License 2.0

Shell 4.78% Python 42.16% Dockerfile 1.79% HTML 0.65% JavaScript 50.27% CSS 0.34%

jupyter-notebook mlflow spark gcp kubernetes delta-lake data-engineering data-platform orchestration workflow

pawmark's Introduction

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

pawmark's People

Contributors

Stargazers

Watchers

pawmark's Issues

Support Notebook Scheduling

Add Pyspark Example for submit-spark

Persist Notebooks

Fix Spark UI for Jar Application

Spark UI Service per jar application
Auto delete service after application completed

Correct the Sample Dataset Upload Path

Integrate Notebook Pyspark to Cluster

Submit Spark application to GKE cluster
Easily create Spark session without manually providing the k8s address
Save notebook files to GCS

Create event-log Dir for History Server

Add Incremental Pipeline Example

Support MLFlow

Support PySpark application Scheduling

Support History Server in docker-compose

Update Application Source Data Folder

Create specific sub-folder for application source data.

Better Docker Build Flow

Support Hugging Face

Add Badges

Auto Create SparkSession Upon Notebook Launch

Add Wiki about Spark Jar Application

Optimize all-spark-notebook Image Tag Management

Add Sample Dataset

Support Spark Jar Scheduling

Add HDFS to docker-compose

Enable event-logs and persist to correct location for Notebook

Add SparkML + Mlflow Notebook Example

Release v0.2.0-alpha

Add Jupyter Notebook Support

Auto Load Notebooks from GCS

Add Wiki about Notebook

Start-up script
Notebook persistance
Event log

Fix Spark UI for Notebook

Add Sklearn + Mlflow Notebook Example

Create ConfigMap for Better Env Management

Add docker-compose for local test

Make Bucket name var in gcs_save_hook.py

Support Jar application Scheduling

Spark Web UI not Auto-deleted after Application Completion

Add Notebook Template

Update README

Add Notebook Samples

Better Management of Notebook Persistence to GCS

More self-explained GCS path

Add Wiki about History Server

Add Wiki link in Readme

Add Delta Lake Support

Support Python script Scheduling

Support Spark Resource Configuration in Notebook

Support notebook Spark UI Link

Fix Notebook Rename but Save as new file to GCS Issue

Try using gsutil rsync

Add History Server

Avoid Variable Hardcoding in Notebook startup.py

service_name
namespace

Add Spark Worker Node in docker-compose

Release v0.3.0-alpha

Fix README Badge

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