Hi dear arrow developers. I tested inner_join with arrow R package but R crashed, this is my example with toy dataset iris:
data(iris)
write.csv(iris, "iris.csv") # write csv file
write parket file with write_chunk_data function (below)
walk("C:/Users/Stats/Desktop/ejemplo_join/iris.csv",
write_chunk_data, "C:/Users/Stats/Desktop/ejemplo_join/parquet", chunk_size = 50)
iris_arrow <- open_dataset("parquet")
df1_arrow <- iris_arrow %>% select(...1, Sepal.Length, Sepal.Width, Petal.Length)
df2_arrow <- iris_arrow %>% select(...1, Petal.Width, Species,) d
df <- tabla1_arrow %>% inner_join(tabla2_arrow, by = "...1") %>%
group_by(Species) %>% summarise(prom = mean(Sepal.Length)) %>% collect()
print(df)
Run this function to write parquet files in this example please
write_chunk_data <- function(data_path, output_dir, chunk_size = 1000000) {
#If the output_dir do not exist, it is created
if (!fs::dir_exists(output_dir)) fs::dir_create(output_dir)
#It gets the name of the file
data_name <- fs::path_ext_remove(fs::path_file(data_path))
#It sets the chunk_num to 0
chunk_num <- 0
#Read the file using vroom
data_chunk <- vroom::vroom(data_path)
#It gets the variable names
data_names <- names(data_chunk)
#It gets the number of rows
rows<-nrow(data_chunk)
#The following loop creates a parquet file for every [chunk_size] rows
repeat{
#It checks if we are over the max rows
if(rows>(chunk_num+1)*chunk_size)
{ arrow::write_parquet(data_chunk[(chunk_num*chunk_size+1):((chunk_num+1)*chunk_size),], fs::path(output_dir, glue::glue("
{data_name}
-{chunk_num}.parquet")))
}
else
{ arrow::write_parquet(data_chunk[(chunk_num*chunk_size+1):rows,], fs::path(output_dir, glue::glue("
{data_name}
-{chunk_num}.parquet")))
break
}
chunk_num <- chunk_num + 1
}
#This is to recover some memory and space in the disk
rm(data_chunk)
tmp_file <- tempdir()
files <- list.files(tmp_file, full.names = T, pattern = "^vroom")
file.remove(files)
}
Reporter: José F
Related issues:
Note: This issue was originally created as ARROW-15397. Please see the migration documentation for further details.
Hi dear arrow developers. I tested inner_join with arrow R package but R crashed, this is my example with toy dataset iris:
data(iris)
write.csv(iris, "iris.csv") # write csv file
write parket file with write_chunk_data function (below)
walk("C:/Users/Stats/Desktop/ejemplo_join/iris.csv",
write_chunk_data, "C:/Users/Stats/Desktop/ejemplo_join/parquet", chunk_size = 50)
iris_arrow <- open_dataset("parquet")
df1_arrow <- iris_arrow %>% select(
...1, Sepal.Length, Sepal.Width, Petal.Length)df2_arrow <- iris_arrow %>% select(
...1, Petal.Width, Species,) ddf <- tabla1_arrow %>% inner_join(tabla2_arrow, by = "...1") %>%
group_by(Species) %>% summarise(prom = mean(Sepal.Length)) %>% collect()
print(df)
Run this function to write parquet files in this example please
write_chunk_data <- function(data_path, output_dir, chunk_size = 1000000) {
#If the output_dir do not exist, it is created
if (!fs::dir_exists(output_dir)) fs::dir_create(output_dir)
#It gets the name of the file
data_name <- fs::path_ext_remove(fs::path_file(data_path))
#It sets the chunk_num to 0
chunk_num <- 0
#Read the file using vroom
data_chunk <- vroom::vroom(data_path)
#It gets the variable names
data_names <- names(data_chunk)
#It gets the number of rows
rows<-nrow(data_chunk)
#The following loop creates a parquet file for every [chunk_size] rows
repeat{
#It checks if we are over the max rows
if(rows>(chunk_num+1)*chunk_size)
{ arrow::write_parquet(data_chunk[(chunk_num*chunk_size+1):((chunk_num+1)*chunk_size),], fs::path(output_dir, glue::glue("
{data_name}
-{chunk_num}.parquet")))
}
else
{ arrow::write_parquet(data_chunk[(chunk_num*chunk_size+1):rows,], fs::path(output_dir, glue::glue("
{data_name}
-{chunk_num}.parquet")))
break
}
chunk_num <- chunk_num + 1
}
#This is to recover some memory and space in the disk
rm(data_chunk)
tmp_file <- tempdir()
files <- list.files(tmp_file, full.names = T, pattern = "^vroom")
file.remove(files)
}
Reporter: José F
Related issues:
Note: This issue was originally created as ARROW-15397. Please see the migration documentation for further details.