soda-spark
PySpark-Boilerplate
| soda-spark | PySpark-Boilerplate | |
|---|---|---|
| 1 | 1 | |
| 60 | 391 | |
| - | - | |
| 0.0 | 2.5 | |
| almost 2 years ago | 4 months ago | |
| Python | Python | |
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
soda-spark
-
How do you test your pipelines?
Since you already have Spark setup, perhaps it would be easier to build a DataFrames by loading data from different tables and validate it in one go ? You can give soda-spark a try (disclosure: I'm one of the developers), using which you can specify your checks using YAML declaratively and run the validations in spark jobs.
PySpark-Boilerplate
What are some alternatives?
great_expectations - Always know what to expect from your data.
ibis - the portable Python dataframe library
pyspark-example-project - Implementing best practices for PySpark ETL jobs and applications.
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
monosi - Open source data observability platform
cookiecutter-django - Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly.
soda-core - :zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
etl-markup-toolkit - ETL Markup Toolkit is a spark-native tool for expressing ETL transformations as configuration
TypedPyspark - Type-annotate your spark dataframes and validate them
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.