versatile-data-kit
Apache Arrow
versatile-data-kit | Apache Arrow | |
---|---|---|
52 | 75 | |
410 | 13,562 | |
1.0% | 1.4% | |
9.7 | 10.0 | |
7 days ago | 3 days ago | |
Python | C++ | |
Apache License 2.0 | Apache License 2.0 |
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versatile-data-kit
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Looking for a data blogger
Here's the project: https://github.com/vmware/versatile-data-kit
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Need advice on ETL tool
I don't really know if this would work for you because the UI is not functional yet, but a very simple REST API ingestion example here, there's one for csv too https://github.com/vmware/versatile-data-kit/wiki/Ingesting-data-from-REST-API-into-Database I can't imagine a simpler way unless it's really drag and drop.
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If dbt is the "T" part of an "ELT", what do you use for "EL"?
I work at VMware and we use one tool for the whole ELT, it was made internally as there was no good alternative at the time and now we opensourced it, here it is: https://github.com/vmware/versatile-data-kit
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Best way to fix errors in my data?
With my team we created csv ingestion plugin described here, maybe you want to try it out: https://github.com/vmware/versatile-data-kit/wiki/Ingesting-local-CSV-file-into-Database
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What Orchestration Tool do you use for batch ETL/ELT?
We use Versatile Data Kit for batch data job orchestration (https://github.com/vmware/versatile-data-kit)
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Dear, pipeline builders! Which step in your role is the most time consuming?
"suggestions on how to reduce the time spent on initially generating and adjusting the code" is using some tools that automate ELT. Here's one open-source tool I'm working on with my team: https://github.com/vmware/versatile-data-kit
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Problem definition / vibe check for a repo
here's the repo: https://github.com/vmware/versatile-data-kit
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Can we take a moment to appreciate how much of dataengineering is open source?
If you wish to contribute, projects usually have good first issues: https://github.com/vmware/versatile-data-kit/labels/good%20first%20issue If you wish to learn, check out examples: https://github.com/vmware/versatile-data-kit/tree/main/examples
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ETL question (noob)
Have you heard about versatile data kit (https://github.com/vmware/versatile-data-kit)? I think it meets your needs perfectly:
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DE Open Source
Versatile Data Kit is a framework to bBuild, run and manage your data pipelines with Python or SQL on any cloud https://github.com/vmware/versatile-data-kit here's a list of good first issues: https://github.com/vmware/versatile-data-kit/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22 Join our slack channel to connect with our team: https://cloud-native.slack.com/archives/C033PSLKCPR
Apache Arrow
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How moving from Pandas to Polars made me write better code without writing better code
In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++.
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From slow to SIMD: A Go optimization story
I learned yesterday about GoLang's assembler https://go.dev/doc/asm - after browsing how arrow is implemented for different languages (my experience is mainly C/C++) - https://github.com/apache/arrow/tree/main/go/arrow/math - there are bunch of .S ("asm" files) and I'm still not able to comprehend how these work exactly (I guess it'll take more reading) - it seems very peculiar.
The last time I've used inlined assembly was back in Turbo/Borland Pascal, then bit in Visual Studio (32-bit), until they got disabled. Then did very little gcc with their more strict specification (while the former you had to know how the ABI worked, the latter too - but it was specced out).
Anyway - I wasn't expecting to find this in "Go" :) But I guess you can always start with .go code then produce assembly (-S) then optimize it, or find/hire someone to do it.
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Time Series Analysis with Polars
One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on par with its NumPy-based features. Polars was built around Arrow from the get go. This makes it very powerful when it comes to exchanging data with other languages and reducing the number of in-memory copying operations, thus leading to better performance.
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TXR Lisp
IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/
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3D desktop Game Engine scriptable in Python
https://www.reddit.com/r/O3DE/comments/rdvxhx/why_python/ :
> Python is used for scripting the editor only, not in-game behaviors.
> For implementing entity behaviors the only out of box ways are C++, ScriptCanvas (visual scripting) or Lua. Python is currently not available for implementing game logic.
C++, Lua, and Python all implement CFFI (C Foreign Function Interface) for remote function and method calls.
"Using CFFI for embedding" https://cffi.readthedocs.io/en/latest/embedding.html :
> You can use CFFI to generate C code which exports the API of your choice to any C application that wants to link with this C code. This API, which you define yourself, ends up as the API of a .so/.dll/.dylib library—or you can statically link it within a larger application.
Apache Arrow already supports C, C++, Python, Rust, Go and has C GLib support Lua:
https://github.com/apache/arrow/tree/main/c_glib/example/lua :
> Arrow Lua example: All example codes use LGI to use Arrow GLib based bindings
pyarrow.from_numpy_dtype:
- Show HN: Udsv.js – A faster CSV parser in 5KB (min)
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Interacting with Amazon S3 using AWS Data Wrangler (awswrangler) SDK for Pandas: A Comprehensive Guide
AWS Data Wrangler is a Python library that simplifies the process of interacting with various AWS services, built on top of some useful data tools and open-source projects such as Pandas, Apache Arrow and Boto3. It offers streamlined functions to connect to, retrieve, transform, and load data from AWS services, with a strong focus on Amazon S3.
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Cap'n Proto 1.0
Worker should really adopt Apache Arrow, which has a much bigger ecosystem.
https://github.com/apache/arrow
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C++ Jobs - Q3 2023
Apache Arrow
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Wheel fails for pyarrow installation
I am aware of the fact that there are other posts about this issue but none of the ideas to solve it worked for me or sometimes none were found. The issue was discussed in the wheel git hub last December and seems to be solved but then it seems like I'm installing the wrong version? I simply used pip3 install pyarrow, is that wrong?
What are some alternatives?
data-engineering-zoomcamp - Free Data Engineering course!
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
h5py - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.
quadratic - Quadratic | Data Science Spreadsheet with Python & SQL
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
pyramid-jsonapi - Auto-build JSON API from sqlalchemy models using the pyramid framework
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
dbt-data-reliability - dbt package that is part of Elementary, the dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
hamilton - A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
ClickHouse - ClickHouse® is a free analytics DBMS for big data