ApacheArrow

@ApacheArrow

Columnar In-Memory Analytics

Cacheland
Beigetreten Februar 2016

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  1. We've just welcomed Ji Liu and Liya Fan from as committers! Thank you for all your contributions.

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  2. hat retweetet

    We've addressed a number of issues with the Python wheels and thus they'll be 75% smaller in the next major release. An optional component requiring the LLVM runtime will likely be shipped in a separate wheel in the future

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  3. This was inspired by the CPython Buffer Protocol and was designed by Arrow PMC member and CPython core developer Antoine Pitrou

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  4. In 0.17.0 we have a new C Data Interface enabling zero-copy in-memory sharing of Arrow data via C FFI. It's a game changer for adding Arrow import/export to libraries without requiring any build or runtime dependencies. Read more:

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  5. We've just released 0.17.0 covering 10 weeks of dev work: 569 issues closed from 79 unique contributors. Lots of new stuff and many bug fixes, recommended upgrade for all users

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  6. hat retweetet

    New Blog Post: How we enabled to create pandas DataFrame objects faster than pandas itself (sometimes)

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  8. The 0.16.0 release of will be the last one to support Python 2.7. The Python 2.x language has served us well for nearly 20 years but it is time to say goodbye

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  9. We have released 0.16.0 with 735 issues resolved from 99 contributors. Read more about what's new since the last major release in October '19

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  10. hat retweetet
    10. Dez. 2019

    明日の夜はApache Arrow東京ミートアップ2019だよ! Apache Arrow 1.0.0がそろそろ出そうだからそろそろ使い始めたほうがいいんじゃないかな!私はApache Arrowのことを知らない人向けに最新情報を紹介するよ!

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  11. We now have Python 3.8 wheel support out of git master in , will be available from PyPI in next major release

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  12. This week we made a patch release 0.15.1 of containing over 30 critical bug fixes. Recommended upgrade for all users

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  13. hat retweetet

    This afternoon NYC 2019 (3:45 PM ET), Senior Software Engineer will demonstrate how to use 🐍 and in order to quickly read esoteric into so it can be analyzed elegantly

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  14. We noticed a deployment hiccup where JS 0.15.0 didn't 100% make its way into NPM. We're working on fixing

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  15. Do you have the need for speed? Learn more about Flight, our new framework for fast data transport

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  16. If you are using + together, please be sure to read the release notes for 0.15.0, since you must take some actions to be able to use pyarrow==0.15.0 with Spark pinned to an older Java library

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  17. We have just released 0.15.0 with 687 resolved issues from 80 distinct contributors! It concludes ~3 months of development and has many new features, bug fixes, and performance improvements Read more:

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  18. We have some big C++ Parquet optimizations coming in version 0.15.0 to improve string performance and memory use, especially on dictionary-encoded data (e.g. pandas Categorical, R factor). Read more:

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  19. Some of our Python wheels (e.g. Windows) are are risk of being broken for the upcoming 0.15.0 release as they do not currently have active maintainers. Do you depend on "pip install pyarrow"? We need your help!

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  20. We are now on CRAN! It took a village to make it possible Read files, faster Feather support, and much more. Note: we're still working out some kinks for macOS users.

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