thisisnic commented on issue #39139:
URL: https://github.com/apache/arrow/issues/39139#issuecomment-2030030890

   I tried this locally (Ubuntu) on the copy of the NYC taxi dataset I have, 
but couldn't reproduce; I also tried it with a CSV dataset which I knew usually 
took a lot longer for `glimpse()` to work on, and found that it was slow, due 
to `dataset__Scanner__CountRows` taking a while, which makes sense when 
thinking about Parquet metadata vs. CSV's lack of metadata:
   
   
![image](https://github.com/apache/arrow/assets/13715823/8b96590b-b5a8-4cec-8e1b-259afc366a38)
   
   @AngelFelizR I don't suppose you'd mind running your example again, but 
using `profvis` to track the timing, and then sharing the flame graph like the 
one I pasted above?  Something like:
   
   ```r
   library(dplyr)
   library(arrow)
   library(profvis)
   
   NycTrips2022 <- here::here("data/trip-data/year=2022") |>
     open_dataset()
   
   profvis(glimpse(NycTrips2022))
   ```


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