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https://issues.apache.org/jira/browse/ARROW-10088?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17203548#comment-17203548
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Neal Richardson commented on ARROW-10088:
-----------------------------------------
Ok, it looks like there are multiple issues here, in addition to the ability to
control the downcasting behavior:
* Handling subclasses of integer64, esp. when relating to automatic downcasting
* (Not discussed here but) the ".internal.selfref" attribute from data.table is
an externalptr, which won't be valid to serialize and restore, so it needs to
be dropped (and then presumably also the data.table class too)
* The auto-downcast logic appears only to consider the first chunk of a
ChunkedArray (which you have in the feather Table you've read in, I suspect).
I've reproduced that:
{code}
diff --git a/r/tests/testthat/test-chunked-array.R
b/r/tests/testthat/test-chunked-array.R
index e5d3a68e0..3e2d2fd76 100644
--- a/r/tests/testthat/test-chunked-array.R
+++ b/r/tests/testthat/test-chunked-array.R
@@ -158,6 +158,13 @@ test_that("ChunkedArray supports POSIXct (ARROW-3716)", {
test_that("ChunkedArray supports integer64 (ARROW-3716)", {
x <- bit64::as.integer64(1:10) + MAX_INT
expect_chunked_roundtrip(list(x, x), int64())
+ # Also with a first chunk that would downcast
+ zero <- Array$create(0L)$cast(int64())
+ expect_type_equal(zero, int64())
+ ca <- ChunkedArray$create(zero, x)
+ expect_type_equal(ca, int64())
+ expect_is(as.vector(ca), "integer64")
+ expect_identical(as.vector(ca), c(bit64::as.integer64(0L), x))
})
{code}
which fails because {{as.vector(ca)}} is "integer" and the values have
overflowed.
> [R] Integer64 incorrectly read into R data.table
> ------------------------------------------------
>
> Key: ARROW-10088
> URL: https://issues.apache.org/jira/browse/ARROW-10088
> Project: Apache Arrow
> Issue Type: Bug
> Components: R
> Affects Versions: 1.0.1
> Reporter: Kyle Kavanagh
> Priority: Critical
> Fix For: 2.0.0
>
>
> I've got a proprietary dataset where one of the columns is an integer64 but
> all of the values would fit within 32bits. As I understand it, arrow/feather
> will downcast that column when the data is read back into R (not ideal IMO,
> but not an issue generally). However, I'm having some trouble with a
> specific dataset.
> When I read in the data, the column is set to the class "integer64", however
> the column type (typeof) is 'integer' and not 'double', which is the
> underlying type used by bit64. This mismatch causes R data.table to error
> out
> ([https://github.com/Rdatatable/data.table/blob/master/src/rbindlist.c#L325)]
> I do not have any issue with integer64 columns which have values > 2^32, and
> suspiciously I am also unable to recreate the issue by manually creating a
> data.table with an int64 column with small values (e.g
> data.table(col=as.integer64(c(1,2,3))) )
> I did look thru the arrow::r cpp source and couldnt find an obvious case
> where the underlying storage array would be an integer but also have the
> 'integer64' class attr assigned... A fix would either be to remove the
> integer64 class attr, or ensure that the underlying data store is a REALSXP
> instead of INTEGERSXP
> My company's network policies wont let me upload the sample dataset, hoping
> to see if this triggers an immediate thoughts. If not, I can try to figure
> our how to upload the dataset or otherwise provide details from it as
> requested.
>
> {code:java}
> > arrow::write_feather(df[,list(testCol)][1], '~/test.feather')
> > test = arrow::read_feather('~/test.feather')
> > class(test$testCol)
> [1] "integer64" "np.ulong"
> > typeof(test$testCol)
> [1] "integer"
> > str(test)
> Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 1 variable: $
> testCol:Error in as.character.integer64(object) : REAL() can only be applied
> to a 'numeric', not a 'integer'
> #In the larger original dataset, it handles most columns properly, only the
> 'testCol' breaks things. Note the difference:
> > typeof(df$goodCol)
> [1] "double"
> > class(df$goodCol)
> [1] "integer64" "np.ulong"
> > typeof(df$testCol)
> [1] "integer"
> > class(df$testCol)
> [1] "integer64" "np.ulong"
> > str(df)
> Classes ‘data.table’ and 'data.frame': 214781 obs. of 17 variables:
> $ goodCol :integer64 1599777000000604025 ...
> $ testCol :Error in as.character.integer64(object) :
> > sessionInfo()
> R version 3.6.1 (2019-07-05)Platform: x86_64-pc-linux-gnu (64-bit)Running
> under: Red Hat Enterprise Linux Server 7.7 (Maipo)
> Matrix products: defaultBLAS: /usr/lib64/libblas.so.3.4.2LAPACK:
> /usr/lib64/liblapack.so.3.4.2locale:
> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8
> LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C
> LC_TELEPHONE=C[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
> attached base packages:[1] stats graphics grDevices utils datasets
> methods baseother attached packages:[1] data.table_1.13.0 bit64_4.0.5
> bit_4.0.4loaded via a namespace (and not attached): [1] Rcpp_1.0.5
> lattice_0.20-41 arrow_1.0.1 [4] assertthat_0.2.1 rappdirs_0.3.1
> grid_3.6.1 [7] R6_2.4.1 jsonlite_1.7.1 magrittr_1.5[10]
> rlang_0.4.7 Matrix_1.2-18 vctrs_0.3.4[13]
> reticulate_1.14-9001 tools_3.6.1 glue_1.4.2[16] purrr_0.3.4
> compiler_3.6.1 tidyselect_1.1.0{code}
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