Apache Parquet

@ApacheParquet

language agnostic, open source Columnar file format for analytics

加入2013年4月

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  1. 已轉推
    5月8日

    Windows support for + will come in the upcoming parquet-cpp 1.1.0 release

  2. 已轉推
    5月23日

    Working on updating conda-forge and PyPI packages for pyarrow 0.4.0; will also include Windows support for . Stay tuned

  3. 已轉推
    5月22日

    We have just released C++ 1.1.0 including Windows support and expanded Arrow type support

  4. 已轉推
    5月16日
  5. 已轉推
    5月15日

    Plus I get to work on projects like , , , and (and contribute, too!)

  6. 已轉推
    5月4日
    回覆給

    If you are at this weekend don't miss talking about and backing pandas

  7. 已轉推
    5月4日

    Sun&Sat, I'll be at ,convince you about , show how helped us bring it to Pandas and enjoy good talks

  8. 已轉推
    4月26日

    Video of my talk at "Efficient data formats for analytics with and "

  9. 已轉推
    4月25日

    At : Efficient Columnar Storage w/ by Ranganathan Balashanmugam Join us!

  10. 已轉推
    4月25日
    回覆給

    A snapshot of some community OSS projects (pandas, , , and others) that we've gotten involved with

  11. 已轉推
    4月21日
  12. 已轉推
    4月21日

    Great breakdown on pros/cons of coumnar format for data at meetup.

  13. 已轉推
    4月19日

    At : Even Faster: When Presto Meets @ Uber by Zhenxiao Luo Join us!

  14. 已轉推
    4月7日

    If you use Dask and , other perspectives on this issue would be useful:

  15. 已轉推
    3月30日
    回覆給

    on and is mind blowing .. great analytical speeds . Great file compression

  16. 已轉推
    4月6日

    Check out the awesome schedule of I'll talk about DataFrame storage with

  17. 已轉推
    4月4日

    Bringing file support for with , and fast distributed data processing with

  18. 已轉推
    3月30日

    can be so frustrating. But when you finally write to a file, it's so satisfying.

  19. 已轉推
    3月31日

    and : Why We Needed Different Projects for Columnar Data, On Disk and In-Memory

  20. 已轉推
    3月30日

    Software I would write if I had the time: a foreign data wrapper for files.

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