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https://issues.apache.org/jira/browse/ARROW-11579?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17285072#comment-17285072
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Claymore Marshall commented on ARROW-11579:
-------------------------------------------

Noting that I was able to use set_cpu_count(2) without hanging, but have now 
noticed on bulk small feather data set reads, getting hanging behaviour again.  
Need to set to set_cpu_count(1) to avoid this.

> [R] read_feather hanging on Windows
> -----------------------------------
>
>                 Key: ARROW-11579
>                 URL: https://issues.apache.org/jira/browse/ARROW-11579
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: R
>    Affects Versions: 3.0.0
>         Environment: windows 10, R 4.0.0, arrow 3.0.0
>            Reporter: Claymore Marshall
>            Assignee: Ian Cook
>            Priority: Major
>
> On windows 10, reading large feather objects in R seems to lead to hanging on 
> a repeat read.
>  
> This issue has been reproduced on 3 different windows machines.  All running 
> win 10, R 4.0.0 (or later).
> read_feather does not hang if using version = 1, or using uncompressed with 
> version 2.
> This issue does not happen on tests on linux (Ubuntu 20.04 atleast)
>  
> Example:
>  
> library(arrow)
> m <- data.frame(x = rnorm(7e6), y = rnorm(5), b = rnorm(5), n = rnorm(5), c = 
> c("a", "n"))
> write_feather(m, "test.feather4", version = 2, compression = "lz4") # does 
> not hang with uncompressed, but does with lz4 and zstd
> for (j in 1:50){  
> y <- read_feather("test.feather4")  # hangs after an unpredictable number of 
> reads, just on windows though  
> print(paste0("feather read ", j, "..."))
> }
>  
>  
>  
>  
>  
> Interestingly, a work around is to use read_feather but call just one column 
> at a time.  This does not hang so far.
>  
> e.g. y returns the full data frame, and this doesn't hang on repeated reads:
>  
> _y <- lapply(cols, function(col) {_
> _read_feather("test.feather4", col_select = all_of(col))_
> _})_
>  



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