Details
-
Bug
-
Status: Resolved
-
Major
-
Resolution: Fixed
-
None
Description
A sample file is attached, showing 10 rows each of strings with consistent failures (false_na = TRUE) and consistent successes (false_na = FALSE). The strings are in the column `json_string` – if relevant, they are geojsons with min nchar of 33,229 and max nchar of 202,515.
When I read this sample file with other R CSV readers (readr and data.table shown), the files are imported correctly and there are no NAs in the json_string column.
When I read with arrow::read_csv_arrow, 50% of the sample json_string column end up as NAs. as_data_frame TRUE or FALSE does not change the behavior, so this might not be limited to the R interface, but I can't help debug much further upstream.
aaa1 <- arrow::read_csv_arrow("demo_data.csv", as_data_frame = TRUE) aaa2 <- arrow::read_csv_arrow("demo_data.csv", as_data_frame = FALSE) bbb <- data.table::fread("demo_data.csv") ccc <- readr::read_csv("demo_data.csv") mean(is.na(aaa1$json_string)) # 0.5 mean(is.na(aaa2$column(1))) # Scalar 0.5 mean(is.na(bbb$json_string)) # 0 mean(is.na(ccc$json_string)) # 0
- arrow 2.0 (latest CRAN)
- readr 1.4.0
- data.table 1.13.2
- R version 4.0.1 (2020-06-06)
- MacOS Catalina 10.15.7 / x86_64-apple-darwin17.0
Attachments
Attachments
Issue Links
- links to
