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https://issues.apache.org/jira/browse/ARROW-11841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17565408#comment-17565408
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Antoine Pitrou commented on ARROW-11841:
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Also it would be worth taking a look how it's done in Python currently:
https://github.com/apache/arrow/blob/2519230121b9be3ecac01ac3ed2b610382dbca48/python/pyarrow/error.pxi
and the C++ APIs that it relies on:
https://github.com/apache/arrow/blob/2519230121b9be3ecac01ac3ed2b610382dbca48/cpp/src/arrow/util/cancel.h
They allow to automatically cancel a StopToken from a set of received signals.
It should in turn interrupt whatever primitive is checking for StopToken
cancellations (such as CSV reading).
> [R][C++] Allow cancelling long-running commands
> -----------------------------------------------
>
> Key: ARROW-11841
> URL: https://issues.apache.org/jira/browse/ARROW-11841
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++, R
> Reporter: Antoine Pitrou
> Priority: Major
> Fix For: 10.0.0
>
>
> When calling a long-running task (for example reading a CSV file) from the R
> prompt, users may want to interrupt with Ctrl-C.
> Allowing this will require integrating R's user interruption facility with
> the cancellation API that's going to be exposed in C++ (see ARROW-8732).
> Below some information I've gathered on the topic:
> There is some hairy discussion of how to interrupt C++ code from R at
> https://stackoverflow.com/questions/40563522/r-how-to-write-interruptible-c-function-and-recover-partial-results
> and https://stat.ethz.ch/pipermail/r-devel/2011-April/060714.html .
> It seems it may involve polling cpp11::check_user_interrupt() and catching
> any cpp11::unwind_exception that may signal an interruption. A complication
> is that apparently R APIs should only be called from the main thread. There's
> also a small library which claims to make writing all this easier:
> https://github.com/tnagler/RcppThread/blob/master/inst/include/RcppThread/RMonitor.hpp
> But since user interruptions will only be noticed by the R main thread, the
> solution may be to launch heavy computations (e.g. CSV reading) in a separate
> thread and have the main R thread periodically poll for interrupts while
> waiting for the separate thread. This is what this dedicated thread class
> does in its join method:
> https://github.com/tnagler/RcppThread/blob/master/inst/include/RcppThread/Thread.hpp#L79
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