Large data frames can be saved but not loaded

[shntnu]

Large data frames can be saved but not loaded (feather v0.3.2)

dummy <- as.data.frame(matrix(rnorm(30000000, 30000, 1000)))
feather::write_feather(dummy, "dummy.feather")
dummy <- feather::read_feather("dummy.feather")
#> Error: evaluation nested too deeply: infinite recursion / options(expressions=)?

^{Created on 2019-02-06 by the reprex package (v0.2.1)}

[jameslamb]

@shntnu it's possible you are seeing the same error as in #374 . Unfortunately feather has a dependency on tibble and you need certain combinations of tibble and feather together to get it working.

Could you try upgrading to tibble > 2.0.0 and see if you're able to reproduce this issue?

I did not have any problems running your code with this environment (from sessionInfo()):

R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods  
[7] base     

loaded via a namespace (and not attached):
 [1] compiler_3.5.0  hms_0.4.2       tools_3.5.0     pillar_1.3.1   
 [5] rstudioapi_0.7  tibble_2.0.1    yaml_2.2.0      crayon_1.3.4   
 [9] Rcpp_1.0.0.1    feather_0.3.2   pkgconfig_2.0.2 rlang_0.3.1

@hadley why does feather need the tibble dependency? I think it might make more sense to have read_feather() read up into base data frames and then to add a from_feather() or something like that to the tibble package. Curious to hear your thoughts.

[shntnu]

@jameslamb tibble 2.1.1 + feather 0.3.3 worked! Thanks for diagnosing.