4 ms·

40% slower in groupbys and 4x slower in joins isn’t convincing.

• mbauman 5y ago
  Oh I agree. What's convincing to me is the momentum. The DataFrames.jl team only started focusing on performance three months ago after hitting v1.0[1] and were able to rapidly become competitive with groupbys; the performance of join is next[2]. Compare the live view with the state when grandparent's blog post was written/updated (March of this year). I expect it to continue to improve; note that it's starting to be the fastest implementation on some of the groupby benchmarks. 1. https://discourse.julialang.org/t/release-announcements-for-dataframes-jl/18258/133 https://discourse.julialang.org/t/release-announcements-for-... 2. https://discourse.julialang.org/t/the-state-of-dataframes-jl-h2o-benchmark/43081/14 https://discourse.julialang.org/t/the-state-of-dataframes-jl...
• freemint 5y ago
  This seems quiet cherry picked as there are 3 different dataset sizes. However yes, it does not beat all other packages tested in performance.
  • nojito 5y ago
    Not really cherry picked. Data.table is designed for large data sets with many groups + complex joins.