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Posted to jira@arrow.apache.org by "Nicola Crane (Jira)" <ji...@apache.org> on 2022/10/27 19:16:00 UTC
[jira] [Updated] (ARROW-17597) [R][C++] Why is read_csv_arrow so much slower when using S3 path notation?
[ https://issues.apache.org/jira/browse/ARROW-17597?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Nicola Crane updated ARROW-17597:
---------------------------------
Priority: Critical (was: Minor)
> [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: Critical
>
> 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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