Apache-Spark-Guide
pyspark-example-project
| Apache-Spark-Guide | pyspark-example-project | |
|---|---|---|
| 2 | 1 | |
| 28 | 1,370 | |
| - | - | |
| 1.8 | 0.0 | |
| over 2 years ago | over 1 year ago | |
| Python | Python | |
| - | - |
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Apache-Spark-Guide
pyspark-example-project
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Learning Pyspark for a new role
https://github.com/AlexIoannides/pyspark-example-project You can use this as an example to organize your project. I have referred to this in the past.
What are some alternatives?
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
soda-spark - Soda Spark is a PySpark library that helps you with testing your data in Spark Dataframes
Traffic-Data-Analysis-with-Apache-Spark-Based-on-Mobile-Robot-Data - Mobile robot data were analyzed with Apache-Spark to extract five different statistical result such as travel time, waiting time, average speed, occupancy and density were produced.
patterns-devkit - Data pipelines from re-usable components
livyc - Apache Spark as a Service with Apache Livy Client
hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai