etl-markup-toolkit
Optimus
| etl-markup-toolkit | Optimus | |
|---|---|---|
| 7 | - | |
| 5 | 1,446 | |
| - | 0.8% | |
| 0.0 | 0.6 | |
| about 3 years ago | 20 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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etl-markup-toolkit
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How do you serialize and save "transformations" in your pipeline?
I have a side project (https://github.com/leozqin/etl-markup-toolkit, if you're interested) that takes transformations as yaml files and outputs step-level logs about each step of the transformation. I've always felt that both artifacts could made searchable using an ELK stack or something... Do you have similar artifacts? Or perhaps there's a way to turn SQL into a structured or semi-structured form to aid in searchability
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Alternative tools to DBT / SQL and Python for writing business logic? Trying to prevent creating a mountain of undocumented spaghetti
My current side project (https://github.com/leozqin/etl-markup-toolkit) is a low code way to express transformations as configuration and run it on pyspark. It also supports abstraction so you can call business logic like a function and has step-level reporting you can load into a metadata table. Usual disclaimers about OSS apply, although I'm happy to answer questions and take contributions.
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How to keep track of the different Transformations done in an ETL pipeline?
Not sure if it meets your exact requirements, but I maintain an open source project that enables spark transformations as configuration, and part of that capability is reporting, including logging of columns in vs columns out, row counts, etc... It's very early stage but perhaps could be useful - https://github.com/leozqin/etl-markup-toolkit
- ETL Markup Toolkit - a spark native tool for describing etl transformations as configuration
- ETL Markup Toolkit - a Spark-native tool for expressing ETL transformations as configuration
Optimus
We haven't tracked posts mentioning Optimus yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
mara-pipelines - A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
AWS Data Wrangler - pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
PySpark-Boilerplate - A boilerplate for writing PySpark Jobs
sweetviz - Visualize and compare datasets, target values and associations, with one line of code.
quinn - pyspark methods to enhance developer productivity 📣 👯 🎉
ga-extractor - Tool for extracting Google Analytics data suitable for migrating to other platforms/databases
sparkmagic - Jupyter magics and kernels for working with remote Spark clusters
zef - Toolkit for graph-relational data across space and time
tdigest - t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
flashtext - Extract Keywords from sentence or Replace keywords in sentences.
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.