Top all-time · #7021
Ursa Labs
Company blog · ursalabs.org/blogdataprogramming
Ursa Labs is the company blog at ursalabs.org, writing about data and programming. Since 2018, 11 different Hacker News readers have linked it 11 times, most often “Columnar File Performance Check-In for Python and R: Parquet, Feather, and FST”. The last post was in 2021, but the archive is still widely read.
Too few sampled comments (6) to say how often HN recommends it.?
Why HN links it
HN readers link Ursa Labs posts on Apache Arrow, the columnar data format and interchange project, and related data tooling. Commenters cite them as background on Arrow's goals and history.
Summarised by Claude from a sample of 6 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Most-linked posts?
- Columnar File Performance Check-In for Python and R: Parquet, Feather, and FST3 people · 3 mentions · first linked 2019-10-07
- Toward an Arrow-native world: the next stage of the Ursa journey2 people · 2 mentions · first linked 2020-12-10
What Hacker News says?
DuckDB looks very interesting and I'm quite excited to examine it more closely in the next few days! I just wanted to add to the discussion that an unchanging file format, or at least a backwards compatible one, is a key feature of sqlite. See for example Richard Hipp's comments here [1] (I think he also mentioned earlier in the talk that the file format has become a limiting factor now in terms of some of the refac…
Comment linking /blog/2020-feather-v2/
on “DuckDB – An embeddable SQL database like SQLite, but supports Postgres features”Submitted Columnar File Performance Check-In for Python and R: Parquet, Feather, and FST as a story · 2 points
HN discussionAgreed! Thank you Arrow community for such a great project. It's a long road but it opens up tremendous potential for efficient data systems that talk to one another. The future looks bright with so many vendors backing Arrow independently and Wes McKinney founding Ursa Labs and now Ursa Computing. https://ursalabs.org/blog/ursa-computing/
Comment linking /blog/ursa-computing/
on “Apache Arrow 3.0”Submitted Conbench as a story · 1 points
HN discussionDask groupby example: https://examples.dask.org/dataframes/02-groupby.html > Generally speaking, Dask.dataframe groupby-aggregations are roughly same performance as Pandas groupby-aggregations, just more scalable. The dask.distributed scheduler can also run on one high-RAM instance (with threads or processes) https://docs.dask.org/en/latest/setup.html Pandas docs > Ecosystem > Out-of-core: https://pandas.pydata.org/…
Comment linking /blog/2019-10-columnar-perf/
on “A lot of complex “scalable” systems can be done with a simple, single C++ server”Submitted Toward an Arrow-native world: the next stage of the Ursa journey as a story · 1 points
HN discussionI may be wrong. It happens a lot! But I think Arrow's vision encompasses compute, not just a data format and data interface. https://www.slideshare.net/wesm/pycon-colombia-2020-python-f... Slide 43: The "Arrow C++ Platform" encompasses a "Multi-core Work Scheduler" and a "Query Engine" Slide 38: "It would be more productive (long-term) to have a reusable computational foundation for data frames" Again, I agree that,…
Comment linking /tech/
on “What's bad about Julia?”Submitted Columnar file reading benchmarks in Python and R as a story · 1 points
HN discussionHow does RStudio have little interest in interoperability with other languages? They produce the reticulate package[1] to allow calling Python code for R, they have added support for Python to RMarkdown and RStudio[2], they let you host Python apps on their RStudio Connect product[3], they sponsor Ursa Labs to work on the Arrow project for easy data interchange[4]. 1) https://rstudio.github.io/reticulate/ 2) https:/…
Comment linking /
on “Introduction to Pluto.jl”Submitted Ursa Labs: Shared Infrastructure for Data Science as a story · 1 points
HN discussionI hit a roadblock with trying to read Stata files into Pandas a few months ago. I discovered that not all versions of Stata file formats are supported by Pandas in Python. R has much better support for Stata files. With the help of Feather, which was written over Arrow, I was able to read Stata files into R, write the dataframe out to Feather and read the Feather file into a Pandas dataframe with no manipulation. Wi…
Comment linking /
on “The Origin and History of Apache Arrow”
