TypedPyspark
soda-spark
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TypedPyspark | soda-spark | |
---|---|---|
1 | 1 | |
14 | 60 | |
- | - | |
2.4 | 0.0 | |
7 months ago | almost 2 years ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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TypedPyspark
soda-spark
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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.
What are some alternatives?
pyspark-starter - Starter pyspark code with a working combination of all versions
great_expectations - Always know what to expect from your data.
pyspark-on-aws-emr - The goal of this project is to offer an AWS EMR template using Spot Fleet and On-Demand Instances that you can use quickly. Just focus on writing pyspark code.
pyspark-example-project - Implementing best practices for PySpark ETL jobs and applications.
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.
monosi - Open source data observability platform
PySpark-Boilerplate - A boilerplate for writing PySpark Jobs
ibis - the portable Python dataframe library
soda-core - :zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
data-caterer - Data generation and validation tool for any data source