learning-apache-spark and Spark-with-Python

learning-apache-spark
51
Established
Spark-with-Python
51
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 299
Forks: 186
Downloads:
Commits (30d): 0
Language: HTML
License: MIT
Stars: 362
Forks: 271
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About learning-apache-spark

MingChen0919/learning-apache-spark

Notes on Apache Spark (pyspark)

These notes help data professionals understand how to process and analyze very large datasets efficiently using Apache Spark. They cover common data manipulation and analysis tasks, showing how to transform raw data into actionable insights or cleaned datasets ready for further use. Data engineers, data scientists, and analysts working with big data will find this resource useful.

big-data-processing data-engineering data-analysis data-science large-scale-etl

About Spark-with-Python

tirthajyoti/Spark-with-Python

Fundamentals of Spark with Python (using PySpark), code examples

If you're a data professional, this project offers practical code examples and setup guidance for using Apache Spark with Python (PySpark). It helps you process vast amounts of data efficiently, providing a robust framework for big data analytics and machine learning. This is ideal for data scientists, data engineers, or machine learning engineers who need to work with large, distributed datasets.

big-data-analytics distributed-computing machine-learning-engineering data-processing data-engineering

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