[jira] [Created] (ARROW-14736) [C++][R]Opening a multi-file dataset and writing a re-partitioned version of it fails

["Dragoș Moldovan-Grünfeld (Jira)" <ji...@apache.org>]

Dragoș Moldovan-Grünfeld created ARROW-14736:
------------------------------------------------

             Summary: [C++][R]Opening a multi-file dataset and writing a re-partitioned version of it fails
                 Key: ARROW-14736
                 URL: https://issues.apache.org/jira/browse/ARROW-14736
             Project: Apache Arrow
          Issue Type: Bug
          Components: C++, R
    Affects Versions: 6.0.0
         Environment: M1 Mac, macOS Monterey 12.0.1, 16Gb RAM
R 4.1.1, arrow R package 6.0.0.2
            Reporter: Dragoș Moldovan-Grünfeld


Attempting to open a multi-file dataset and write a re-partitioned version of it fails as it seems there is an attempt to collect data into memory first. This happens both for wide and long data.

Steps to reproduce the issue:
1. Create a large dataset (100k columns, 300k rows) and write it to disk and create 20 copies of it. Each file will have a footprint of roughly 7.5GB. 
{code:r}
library(arrow)
library(dplyr)
library(fs)

rows <- 300000
cols <- 100000
partitions <- 20

wide_df <- as.data.frame(
  matrix(
    sample(1:32767, rows * cols / partitions, replace = TRUE), 
    ncol = cols)
)

schem <- sapply(colnames(wide_df), function(nm) {int16()})
schem <- do.call(schema, schem)

wide_tab <- Table$create(wide_df, schema = schem)

write_parquet(wide_tab, "~/Documents/arrow_playground/wide.parquet")

fs::dir_create("~/Documents/arrow_playground/wide_ds")
for (i in seq_len(partitions)) {
  file.copy("~/Documents/arrow_playground/wide.parquet", 
            glue::glue("~/Documents/arrow_playground/wide_ds/wide-{i-1}.parquet"))
}

ds_wide <- open_dataset("~/Documents/arrow_playground/wide_ds/")
{code}
All the following steps fail:

2. Creating and writing a partitioned version of {{{}ds_wide{}}}.
{code:r}
system.time({
  ds_wide %>%
    mutate(grouper = round(V1 / 1024)) %>%
    write_dataset("~/Documents/arrow_playground/partitioned", 
                   partitioning = "grouper",
                   format = "parquet")
})
{code}
3. Writing a non-partitioned dataset:
{code:r}
system.time({
  ds_wide %>%
    write_dataset("~/Documents/arrow_playground/partitioned", 
                  format = "parquet")
})
{code}
4. Creating the partitioning variable first and then attempting to write:
{code:r}
system.time({
  ds2 <- ds_wide %>% 
    mutate(grouper = round(V1 / 1024))
})

system.time({
  ds2 %>% 
    write_dataset("~/Documents/arrow_playground/partitioned", 
                  partitioning = "grouper", 
                  format = "parquet")  
})
{code}
None of the failures seem to originate in R code and they all result in a similar behaviour: the R sessions consume increasing amounts of RAM until they crash.



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