DataGristle
spark-daria
| DataGristle | spark-daria | |
|---|---|---|
| 5 | 4 | |
| 137 | 742 | |
| - | - | |
| 0.0 | 0.0 | |
| 3 months ago | about 2 years ago | |
| Python | Scala | |
| GNU General Public License v3.0 or later | MIT License |
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DataGristle
- What are your weekend side projects?
- Instant data model from 1000s of unique files?
- Using Hashing to detect data changes in ELT
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How do you sort a CSV file with several million rows?
DataGristle: this one contains some more unusual csv utilities, and what's in master includes the ability to sort by field names rather than offsets: https://github.com/kenfar/DataGristle
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Open source contributions for a Data Engineer?
DataGristle by u/kenfar who influenced many of us in this sub.
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Is Spark - The Defenitive Guide outdated?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?
Skytrax-Data-Warehouse - A full data warehouse infrastructure with ETL pipelines running inside docker on Apache Airflow for data orchestration, AWS Redshift for cloud data warehouse and Metabase to serve the needs of data visualizations such as analytical dashboards.
chispa - PySpark test helper methods with beautiful error messages
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
quinn - pyspark methods to enhance developer productivity 📣 👯 🎉
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
Task - A task runner / simpler Make alternative written in Go
sqlfluff - A modular SQL linter and auto-formatter with support for multiple dialects and templated code.
didact-engine - The REST API and execution engine for the Didact Platform.
spark-fast-tests - Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
dagster - An orchestration platform for the development, production, and observation of data assets.