delta-rs
chispa
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delta-rs | chispa | |
---|---|---|
28 | 12 | |
1,820 | 508 | |
6.1% | - | |
9.7 | 6.7 | |
1 day ago | 7 days ago | |
Rust | Python | |
Apache License 2.0 | MIT License |
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.
delta-rs
- Delta-rs – a Rust-based implementation of deltalake
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Delta Lake vs. Parquet: A Comparison
I work at Databricks, but am pretty must just an OSS nerd, mainly focusing on Delta Rust recently: https://github.com/delta-io/delta-rs
I did some keyword research and wrote this post cause lots of folks are doing searches for Delta Lake vs Parquet. I'm just trying to share a fair summary of the tradeoffs with folks who are doing this search. It's a popular post and that's why I figured I would share it here.
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Working with Rust
Seeing a lot of great libraries coming out with python bindings in the data world e.g delta-rs Polars. I see it growing in this space as a C++ alternative
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Ideas/Suggestions around setting up a data pipeline from scratch
If I’m not misunderstanding, you could both decode the gRPC protobuf AND write to delta lake in Rust. Tonic, Delta-rs.
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Delta-rs with upserts
https://github.com/delta-io/delta-rs/issues/850 … looks like it’s on the roadmap!
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Read and filter delta files on Azure from a .net application
Microsoft talk a lot about OneLake and that the delta file format will be the standard during the build conference. Is it only me that find it strange that their marketing team talks so much about the delta format when they do not even provide a library to work with the delta format from .net? It would be easy for them to maintain bindings to https://github.com/delta-io/delta-rs but also provide a reader that support V-Order https://learn.microsoft.com/en-us/fabric/data-engineering/delta-optimization-and-v-order?tabs=sparksql
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Polars query engine 0.29.0 released
I know someone will be adding this on the python side in the coming weeks. On the rust side you can use delta-rs with polars. Though you would be compiling both arrow2 and arrow-rs, so that's quite heavy.
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Delta Lake without Databricks?
You don’t need DBX to use Delta Lake. You can use S3 as the backend and just use the Python Delta Lake library. It works great! https://github.com/delta-io/delta-rs
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Seeking Recommendations for a Master Data Management Tool
Maybe if I get some free time soon I can formalize into a working example. Been wanting an excuse to try similar concept in delta-rs and polars/duckdb vs databricks/spark vs iceberg/polars.
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Opportunity to contribute to a popular Rust data project (delta-rs)
delta-rs is a native Rust library for Delta Lake. It's a better way to store data than Parquet files and is fundamentally important library for the Rust data ecosystem. It's tightly integrated with Polars and Datafusion and there is a lot of interesting Rust work to be done.
chispa
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Testing spark applications
Unit and e2e tests using a combination of pytest and chispa (https://github.com/MrPowers/chispa). Custom library to create random test data that fits schema with optional hardcoded overrides for relevant fields to test business logic.
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Spark open source community is awesome
here's a little README fix a user pushed to chispa
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Invitation to collaborate on open source PySpark projects
chispa is a library of PySpark testing functions.
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installing pyspark on my m1 mac, getting an env error
The other approach I've used is Poetry, see the chispa project as an example. Poetry is especially nice for projects that you'd like to publish to PyPi because those commands are built-in.
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Spark: local dev environment
- All Spark transformations are tested with pytest + chispa (https://github.com/MrPowers/chispa)
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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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Show dataengineering: beavis, a library for unit testing Pandas/Dask code
I am the author of spark-fast-tests and chispa, libraries for unit testing Scala Spark / PySpark code.
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Tips for building popular open source data engineering projects
Blogging has been the main way I've been able to attract users. Someone searches "testing PySpark", they see this blog, and then they're motivated to try chispa.
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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?
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
spark-fast-tests - Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
spark-daria - Essential Spark extensions and helper methods ✨😲
materialize - The data warehouse for operational workloads.
quinn - pyspark methods to enhance developer productivity 📣 👯 🎉
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
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.
kafka-delta-ingest - A highly efficient daemon for streaming data from Kafka into Delta Lake
null - Nullable Go types that can be marshalled/unmarshalled to/from JSON.
delta-oss
dagster - An orchestration platform for the development, production, and observation of data assets.