flintrock
quinn
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flintrock
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Why Databricks Is Winning
> * AWS has a managed Spark offering called EMR
There is also my rinky-dink open source project, Flintrock [0], that will launch open source Spark clusters on AWS for you.
It's probably not the right tool for production use (and you would be right to wonder why Flintrock exists when we have EMR [1]), but I know of several companies that have used Flintrock at one point or other in production at large scale (like, 400+ node clusters).
[0]: https://github.com/nchammas/flintrock
[1]: https://github.com/nchammas/flintrock#why-build-flintrock-wh...
quinn
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Brainstorming functions to make PySpark easier
We're brainstorming functions to make PySpark easier, see this issue: https://github.com/MrPowers/quinn/issues/83
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PySpark OSS Contribution Opportunity
Adding some README documentation to the README should be quite straightforward. Here's a function that needs to be documented: https://github.com/MrPowers/quinn/issues/52 .
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Invitation to collaborate on open source PySpark projects
quinn is a library with PySpark helper functions. I need to work through all the open issues / PRs and bump all versions. I should do another release. This library gets around 600,000 monthly downloads.
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Pyspark now provides a native Pandas API
Pandas syntax is far inferior to regular PySpark in my opinion. Goes to show how much data analysts value a syntax that they're already familiar with. Pandas syntax makes it harder to reason about queries, abstract DataFrame transformations, etc. I've authored some popular PySpark libraries like quinn and chispa and am not excited to add Pandas syntax support, haha.
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Register Native Functions in PySpark
Here's how I added a create_df method to the SparkSession class: https://github.com/MrPowers/quinn/blob/main/quinn/extensions/spark_session_ext.py
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Is Spark - The Defenitive Guide outdated?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?
databricks-nutter-repos-demo - Demo of using the Nutter for testing of Databricks notebooks in the CI/CD pipeline
chispa - PySpark test helper methods with beautiful error messages
spark-snowflake - Snowflake Data Source for Apache Spark.
spark-daria - Essential Spark extensions and helper methods ✨😲
dask-gateway - A multi-tenant server for securely deploying and managing Dask clusters.
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
null - Nullable Go types that can be marshalled/unmarshalled to/from JSON.
MLflow - Open source platform for the machine learning lifecycle
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
etl-markup-toolkit - ETL Markup Toolkit is a spark-native tool for expressing ETL transformations as configuration
lowdefy - The config web stack for business apps - build internal tools, client portals, web apps, admin panels, dashboards, web sites, and CRUD apps with YAML or JSON.