fugue
nessie
fugue | nessie | |
---|---|---|
11 | 13 | |
1,880 | 834 | |
1.4% | 3.6% | |
6.4 | 9.9 | |
2 days ago | 3 days ago | |
Python | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
fugue
- FLaNK Stack Weekly 22 January 2024
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Daft: A High-Performance Distributed Dataframe Library for Multimodal Data
Please integrate it with Fugue.
https://github.com/fugue-project/fugue
- Fugue: A unified interface for distributed computing
- [Discussion] Open Source beats Google's AutoML for Time series
- Ask HN: How do you test SQL?
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Replacing Pandas with Polars. A Practical Guide
Fugue is an interesting library in this space , though I haven’t tried it
https://github.com/fugue-project/fugue
A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark, Dask and Ray without any rewrites.
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The hand-picked selection of the best Python libraries and tools of 2022
fugue — distributed computing done easy
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[P] Open data transformations in Python, no SQL required
This looks similar to fugue, am I right? How do they compare?
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What the Duck?!
I am looking forward to how Substrait could help removing this friction. It aims to provide a standardised intermediate query language (lower level than SQL) to connect frontend user interfaces like SQL or data frame libraries with backend analytical computing engines. It is linked to the Arrow ecosystem. Something like Ibis or Fugue could become the front and DuckDB the backend engine.
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Pyspark now provides a native Pandas API
There's dask-sql, but I think it is being abandoned for fugue-project. I'm actually excited for this project as it is trying to provide a backend agnostic solution, which would seem like a difficult, lofty goal. I wish them luck.
nessie
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A deep dive into the concept and world of Apache Iceberg Catalogs
Nessie is an innovative open-source catalog that extends beyond the traditional catalog capabilities in the Apache Iceberg ecosystem, introducing git-like features to data management. This catalog not only tracks table metadata but also allows users to capture commits at a holistic level, enabling advanced operations such as multi-table transactions, rollbacks, branching, and tagging. These features provide a new layer of flexibility and control over data changes, resembling version control systems in software development.
- FLaNK Stack Weekly 22 January 2024
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Why is Hive Metastore everywhere? (Especially Iceberg)
Try Nessie https://github.com/projectnessie/nessie - it recently got trino support as well ..
- What are the main things I need to know to be hired as a Java developer?
- Is learning and mastering Spring & Spring boot worth it in 2023 ?
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Which lakehouse table format do you expect your organization will be using by the end of 2023?
Project Nessie (https://projectnessie.org/) will be the catalog that eventually decouples Iceberg from Hive. At that point, I think it will be a no brainer to go Iceberg over Delta.
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5 Reasons Your Data Lakehouse should Embrace Dremio Cloud
The Dremio Sonar query engine can query your data where it exists whether it's AWS Glue, S3, Nessie Catalogs, MySQL, Postgres, RedShift and an ever growing list of sources.
- Project Nessie: Transactional Catalog for Data Lakes with Git-Like Semantics
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Introduction to The World of Data - (OLTP, OLAP, Data Warehouses, Data Lakes and more)
We will also need a catalog to track all of these tables, with the open source Project Nessie we can do just that, and also get great versioning features similar to using Git when developing applications allowing data engineers to practice "data as code" and "write-audit-publish" patterns on their data.
- DoltLab v0.2.0
What are some alternatives?
modin - Modin: Scale your Pandas workflows by changing a single line of code
git-bug - Distributed, offline-first bug tracker embedded in git, with bridges
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
dvc - 🦉 ML Experiments and Data Management with Git
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
hiveberg - Demonstration of a Hive Input Format for Iceberg
mlToolKits - learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.
dremio-oss - Dremio - the missing link in modern data
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
noms - The versioned, forkable, syncable database
xarray - N-D labeled arrays and datasets in Python
dolt - Dolt – Git for Data