[GitHub] [arrow] jonkeane commented on pull request #10445: ARROW-9140: [R] Zero-copy Arrow to R where possible

[GitBox <gi...@apache.org>]

jonkeane commented on pull request #10445:
URL: https://github.com/apache/arrow/pull/10445#issuecomment-858983224


   Ok, I've run some benchmarks on this branch and I'm seeing a huge speed up for floats + integers with `as.vector(array)`. 🎉 
   
   It might be out of scope for this PR, but chunked arrays don't see a similar speed up (which makes sense given they call `ArrayVector__as_vector` directly rather than routing through `Array__as_vector`, so they aren't being using alt rep). I can't quite tell from the cpp if `Table__to_dataframe` would _just work_ with alt rep as well if it worked with ChunkedArrays or if we would need to more to facilitate that.
   
   
   ``` r
   library(arrow, warn.conflicts = FALSE)
   
   x <- 1:1e3+ 1L
   v <- Array$create(x)
   x1 <- v$as_vector()  
   .Internal(inspect(x1))
   #> @7f9077f5a1a8 13 INTSXP g0c0 [REF(65535)] std::shared_ptr<arrow::Array, int32, NONULL> (len=1000, ptr=0x7f90975a9a08)
   
   
   v_chunked <- ChunkedArray$create(x)
   x2 <- v_chunked$as_vector()  
   .Internal(inspect(x2))
   #> @7f908312c000 13 INTSXP g0c7 [REF(2)] (len=1000, tl=0) 2,3,4,5,6,...
   ```
   
   <sup>Created on 2021-06-10 by the [reprex package](https://reprex.tidyverse.org) (v2.0.0)</sup>
   
   arrowbench results (using the new benchmarks in https://github.com/ursacomputing/arrowbench/pull/28): 
   [zero-copy-data-conversion.html.zip](https://github.com/apache/arrow/files/6633992/zero-copy-data-conversion.html.zip)


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