bigdata

Hello,
Considering your amazing efficiency on pandas, numpy, and more, it would seem to make sense for your module to work with even bigger data, such as Audio (for example .mp3 and .wav). This is something that would help a lot considering the nature audio (ie. where one of the lowest and most common sampling rates is still 44,100 samples/sec). For a use case, I would consider vaex.open('Hu

Dear all,
Since the tools were updated in github action CI machines, all existing PRs blocked due to CI failed. We have fixed it in volcano-sh/volcano#1595. You can rebase from master branch and submit PRs again. THX.

This is to track implementation of the ML-Features: https://spark.apache.org/docs/latest/ml-features

Bucketizer has been implemented in dotnet/spark#378 but there are more features that should be implemented.

• Feature Extractors
  • TF-IDF
  • Word2Vec (dotnet/spark#491)
  • CountVectorizer (https://github.com/dotnet/spark/p

• empty
• notEmpty
• length
• lengthUTF8
• char_length, CHAR_LENGTH
• character_length, CHARACTER_LENGTH
• lower, lcase
• upper, ucase
• lowerUTF8
• upperUTF8
• isValidUTF8
• toValidUTF8
• CopytoValidUTF8(input_string)
• repeat
• reverse
• reverseUTF8
• format(pattern, s0, s1, …)
• concat
• concatA