Skytrax-Data-Warehouse
spark-daria
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| Skytrax-Data-Warehouse | spark-daria | |
|---|---|---|
| 1 | 4 | |
| 131 | 742 | |
| - | - | |
| 0.0 | 0.0 | |
| about 4 years ago | about 2 years ago | |
| Python | Scala | |
| MIT License | MIT License |
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Skytrax-Data-Warehouse
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Open source contributions for a Data Engineer?
Always open to accept contributions to my project (Skytrax Data Warehouse). If you are into data stuff support my work at youtube as well (One Developer Pirate), I mostly make data-oriented videos. These days I'm making a SQL course from a data analysis perspective that is expected to release in next week.
spark-daria
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Lakehouse architecture in Azure Synapse without Databricks?
I was a Databricks user for 5 years and spent 95% of my time developing Spark code in IDEs. See the spark-daria and spark-fast-tests projects as Scala examples. I developed internal libraries with all the business logic. The Databricks notebooks would consist of a few lines of code that would invoke a function in the proprietary Spark codebase. The proprietary Spark codebase would depend on the OSS libraries I developed in parallel.
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Is Spark - The Defenitive Guide outdated?
They spent a lot of effort improving the catalyst engine under the hood too and making it easier to extend and improve it in the future. Making it easy to add your own native code to Spark itself. Shameless plug of a blog post I wrote on this subject which basically reiterates what Matthew Powers, author of Spark Daria and quinn, wrote here.
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Ask HN: What are some tools / libraries you built yourself?
I built daria (https://github.com/MrPowers/spark-daria) to make it easier to write Spark and spark-fast-tests (https://github.com/MrPowers/spark-fast-tests) to provide a good testing workflow.
quinn (https://github.com/MrPowers/quinn) and chispa (https://github.com/MrPowers/chispa) are the PySpark equivalents.
Built bebe (https://github.com/MrPowers/bebe) to expose the Spark Catalyst expressions that aren't exposed to the Scala / Python APIs.
Also build spark-sbt.g8 to create a Spark project with a single command: https://github.com/MrPowers/spark-sbt.g8
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Open source contributions for a Data Engineer?
I've built popular PySpark (quinn, chispa) and Scala Spark (spark-daria, spark-fast-tests) libraries.
What are some alternatives?
dbd - dbd is a database prototyping tool that enables data analysts and engineers to quickly load and transform data in SQL databases.
chispa - PySpark test helper methods with beautiful error messages
sqlfluff - A modular SQL linter and auto-formatter with support for multiple dialects and templated code.
quinn - pyspark methods to enhance developer productivity 📣 👯 🎉
jaydebeapi - JayDeBeApi module allows you to connect from Python code to databases using Java JDBC. It provides a Python DB-API v2.0 to that database.
Task - A task runner / simpler Make alternative written in Go
dbt-spotify-analytics - Containerized end-to-end analytics of Spotify data using Python, dbt, Postgres, and Metabase
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
airflow-api-tests - This is a collection of Pytest for the 2.0 Stable Rest Apis for Apache Airflow. I have another repo where you could setup airflow locally and play around with these. I am used to RestAssured, but trying out pytest here.
spark-fast-tests - Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)
dagster - An orchestration platform for the development, production, and observation of data assets.