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https://issues.apache.org/jira/browse/ARROW-17597?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17600811#comment-17600811
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Nicola Crane edited comment on ARROW-17597 at 9/6/22 2:51 PM:
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Hmm, that's a point; is accessing data via the S3 URI going to be inherently
slower than accessing it via https? I tried googling this but didn't find the
answer.
In terms of handling the https URL, there's a function in the R code that
creates a FileSystem object by calling fs___FileSystemFromUri, and then (as
it's compressed) makes it into a CompressedInputStream object.
One difference I can see is that in the first example, the stream object is a
RandomAccessFile object, and in the second example it's an InputStream, so I
guess those examples are using [completely different
interfaces|https://arrow.apache.org/docs/cpp/io.html] for reading the data?
was (Author: thisisnic):
Hmm, that's a point; is accessing data via the S3 URI going to be inherently
slower than accessing it via https? I tried googling this but didn't find the
answer.
In terms of handling the https URL, there's a function in the R code that
creates a FileSystem object by calling fs___FileSystemFromUri, and then (as
it's compressed) makes it into a CompressedInputStream object.
One difference I can see is that in the first example, the stream object is a
RandomAccessFile object, and in the second example it's an InputStream, so I
guess those examples are using completely different interfaces for reading the
data?
> [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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