Is dplyr.snowflakedb only running on 32-bit?

[quotechltd]

I cannot install the package on my Windows 10 64-bit PC. I've got the latest version of R installed which was required to install RJDBC and rJava is loading and running without any issue on all the other packages I use with a dependency to it. Here are the results of running sessionInfo():

R version 3.6.2 (2019-12-12)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)

Matrix products: default

Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding

locale:
[1] LC_COLLATE=English_United Kingdom.1252 LC_CTYPE=English_United Kingdom.1252
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C
[5] LC_TIME=English_United Kingdom.1252

attached base packages:
[1] stats graphics grDevices utils datasets methods base

loaded via a namespace (and not attached):
[1] compiler_3.6.2 tools_3.6.2 mongolite_2.1.0 jsonlite_1.6.1

Here's the result of running Sys.getenv("JAVA_HOME"):

"C:\Program Files\Java\jdk-13.0.2"

Here's the result of running
library(rJava)
.jinit()
.jcall("java/lang/System", "S", "getProperty", "java.runtime.version")

"13.0.2+8"

However, here's the result of running devtools::install_github("snowflakedb/dplyr-snowflakedb"):

[...]
*** arch - i386
Error: package or namespace load failed for 'rJava':
.onLoad failed in loadNamespace() for 'rJava', details:
call: inDL(x, as.logical(local), as.logical(now), ...)
error: unable to load shared object 'C:/Users/[...]/R/win-library/3.6/rJava/libs/i386/rJava.dll':
LoadLibrary failure: %1 is not a valid Win32 application.
[...]

Is the package only working if you have a 32-bit version of JDK installed?

[mark-druffel]

@quotechltd did you ever figure out a solution? I'm having the same issue. I've tried installing using R 32-bit, changing my JAVA_HOME path, and a few other suggestions I found on Stackoverflow to no avail.

[quotechltd]

@mark-druffel unfortunately I didn't.

[mark-druffel]

@quotechltd I was able to use the python connector through reticulate, but it comes with some baggage because you get back lists with python data types that are painful to coerce into a data frame. Below is how I was able to get it working, but the snowflake_to_df function cannot handle those python lists I mentioned (e.g. date columns). I'm still trying to figure out how to create a generic function to solve that.

`
library(reticulate)
py_install('snowflake-connector-python')
py_install('snowflake-connector-python[pandas]')
py_install('snowflake-sqlalchemy')
snowflake.connector <- import('snowflake.connector')
con = snowflake.connector$connect(
user=,
account=,
authenticator='externalbrowser',
warehouse=,
database=,
schema=,
role=)

tables_columns <- con$cursor()$execute('Show Columns')$fetchall()
col_names <- con$cursor()$execute('Show Columns')$description
col_names <- purrr::map(col_names, function(x) purrr::pluck(x, 1)) %>% unlist()
snowflake_to_df <- function(data=NULL, column_names=NULL,keep_columns=NULL){
if(is.null(keep_columns)){keep_columns <- rep_len(T, length(column_names))}
x <- purrr::set_names(data, column_names) %>%
purrr::keep(., keep_columns)
return(x)
}
tables_columns <- purrr::map(tables_columns, snowflake_to_df, column_names = col_names) %>% dplyr::bind_rows()
`

[quotechltd]

Thanks @mark-druffel I will try that when I next try to connect to Snowflake. I had put that on hold for a while.