[jira] [Commented] (ARROW-17597) [R][C++] Why is read_csv_arrow so much slower when using S3 path notation?

["Nicola Crane (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-17597?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17600742#comment-17600742 ] 

Nicola Crane commented on ARROW-17597:
--------------------------------------

I had a look into this in terms of profiling it to see where the issue lies, and it appears to be in the C++ where we call the {{Read}} method of the TableReader object.

[~apitrou] - any ideas what this could be?

> [R][C++] Why is read_csv_arrow so much slower when using S3 path notation?
> --------------------------------------------------------------------------
>
>                 Key: ARROW-17597
>                 URL: https://issues.apache.org/jira/browse/ARROW-17597
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: C++, R
>            Reporter: Carl Boettiger
>            Priority: Minor
>
> Consider these two mechanisms for reading from a public bucket.  I was struck to see that using S3 path notation was consistently over 20 times slower than using the https address directly.  I could imagine a small overhead for using S3, but compared to other operations this seems something weird is going on here:
> {code:java}
> library(arrow)
> targe <- s3_bucket("neon4cast-targets", endpoint_override="data.ecoforecast.org", anonymous=TRUE)
> bench::bench_time({ # 58.6 seconds
>   ex1 <- read_csv_arrow(targe$path("terrestrial_30min/terrestrial_30min-targets.csv.gz"))
> })
> bench::bench_time({ # 2.7 sec
>   ex2 <- read_csv_arrow("https://data.ecoforecast.org/neon4cast-targets/terrestrial_30min/terrestrial_30min-targets.csv.gz")
> })
>  {code}



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