Rezultati pretraživanja
  1. Osobe Vidi sve

  2. 25. sij 2018.

    seems worth an eval if you do time-series analysis. I've been looking into . I am interested to see if this DB is an alternative.

  3. 21. tra 2015.

    Efficient Data Storage for Analytics with Apache Parquet 2.0 by via

  4. 26. stu 2017.
  5. 6. sij 2018.
  6. 2. stu 2017.

    Channels | Parquet .NET is now better and faster than ever. tells us how:

  7. 14. stu 2019.

    We aim to make accessing your data as easy and straightforward as possible. Here's an example connecting to a storage bucket and building a table from 16 files.

  8. 19. svi 2015.
  9. 22. svi 2016.

    Keep a close watch on , it's going to be a winner !!!

  10. 22. srp 2019.
  11. 12. stu 2017.
  12. 12. srp 2015.

    how could one read files using a Linux command line tool? is there a way?

  13. 8. tra 2018.
  14. 19. stu 2017.
  15. 20. srp 2017.

    Read our blog post on on Parquet .Net, the new .NET library for reading & writing files:

  16. 22. svi 2019.

    Unstructured data is more scaleable then structured data for searching and indexing. Who knew

  17. 14. stu 2018.

    We are huge fans of trends in that support data standards. That’s why and is optimized to read from (decompression on ), and operates entirely on in GPU memory.

  18. 22. stu 2018.

    Today’s session was on data input/output , , (user-defined functions) using . Some of the 100+ attendees (mostly Business Engineers) got to present their code.

  19. Petastorm is an data access library enabling training and evaluation of deep learning models directly from multi-terabyte datasets in format.

  20. 23. svi 2017.

    and just when you're thinking about moving beyond on hdfs you come across -> yay !

  21. prije 23 sata

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