mrd0ll4r commented on issue #39912:
URL: https://github.com/apache/arrow/issues/39912#issuecomment-2577956164
Hey all,
ran into the same issue, and I actually *can* share the dataset :) 500M
rows, spread across a bunch of gzipped CSV files, approx 5.x GB. Where do I put
them?
Query:
```r
ds_multi_follows_final = open_dataset("./multi_follows_final",
format="csv",
schema = schema(
did=arrow::utf8(),
multi_follow_id=arrow::uint64(),
follow_created_at=arrow::utf8(),
follow_subject=arrow::utf8(),
sp_list_uri=arrow::utf8(),
match_score=arrow::float64()
),
skip=1)
ds_multi_follows_final %>%
group_by(did,follow_subject) %>%
summarize() %>%
collect() %>%
write_csv("all_multifollow_edges.csv.gz")
```
Backtrace:
```r
> rlang::last_trace(drop=FALSE)
<error/rlang_error>
Error in `compute.arrow_dplyr_query()`:
! Invalid: Negative buffer resize: -2147483584
---
Backtrace:
▆
1. ├─... %>% write_csv("all_multifollow_edges.csv.gz")
2. ├─readr::write_csv(., "all_multifollow_edges.csv.gz")
3. │ └─readr::write_delim(...)
4. │ ├─base::stopifnot(is.data.frame(x))
5. │ └─base::is.data.frame(x)
6. ├─dplyr::collect(.)
7. └─arrow:::collect.arrow_dplyr_query(.)
8. └─arrow:::compute.arrow_dplyr_query(x)
9. └─base::tryCatch(...)
10. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
11. └─base (local) tryCatchOne(expr, names, parentenv,
handlers[[1L]])
12. └─value[[3L]](cond)
13. └─arrow:::augment_io_error_msg(e, call, schema = schema())
14. └─rlang::abort(msg, call = call)
```
Session info:
```r
> sessionInfo()
R version 4.4.2 (2024-10-31)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
LC_TIME=en_US.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8
LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] tidyjson_0.3.2 scales_1.3.0 stringr_1.5.1 readr_2.1.5
xtable_1.8-4 forcats_1.0.0
[7] lubridate_1.9.4 tidyr_1.3.1 ggplot2_3.5.1 arrow_18.1.0
pracma_2.4.4 dplyr_1.1.4
loaded via a namespace (and not attached):
[1] bit_4.5.0.1 jsonlite_1.8.9 gtable_0.3.6 crayon_1.5.3
compiler_4.4.2 renv_1.0.11
[7] tidyselect_1.2.1 parallel_4.4.2 assertthat_0.2.1 R6_2.5.1
labeling_0.4.3 generics_0.1.3
[13] tibble_3.2.1 munsell_0.5.1 pillar_1.10.1 tzdb_0.4.0
rlang_1.1.4 utf8_1.2.4
[19] stringi_1.8.4 bit64_4.5.2 timechange_0.3.0 cli_3.6.3
withr_3.0.2 magrittr_2.0.3
[25] grid_4.4.2 vroom_1.6.5 hms_1.1.3 lifecycle_1.0.4
vctrs_0.6.5 glue_1.8.0
[31] farver_2.1.2 colorspace_2.1-1 purrr_1.0.2 tools_4.4.2
pkgconfig_2.0.3
```
I compiled/installed arrow with `renv` like so:
```r
Sys.setenv(ARROW_WITH_ZLIB="ON")
Sys.setenv("LIBARROW_MINIMAL" = FALSE)
Sys.setenv("LIBARROW_BINARY" = FALSE)
Sys.setenv("ARROW_R_DEV" = TRUE)
Sys.setenv(MAKEFLAGS = sprintf("-j%d", parallel::detectCores()))
options(renv.config.pak.enabled = TRUE)
install.packages(c("dplyr","pracma","arrow","ggplot2","tidyr","lubridate","forcats","xtable","readr","stringr","scales","tidyjson"))
```
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