Warning: <JDBCConnection> uses an old dbplyr interface

[nviraj]

Hi,
Thank you for the excellent package. Very useful and much appreciated.

I am using “pool” with “RJDBC” and “dbplyr” packages to connect to Athena tables.
However I see the following warning.

Warning: <JDBCConnection> uses an old dbplyr interface
ℹ Please install a newer version of the package or contact the maintainer

Initially I thought it had something to do with RJDBC but it does not seem to be the case, as seen here.

I don't have a reproducible example due to the private nature of the databases I am connecting to, but the issue might be originating from Pool instead.
Interestingly the example at the end of this reference page has the same warning, which is how I tracked it in spite of the misleading warning.

#> Warning: <Pool> uses an old dbplyr interface
#> ℹ Please install a newer version of the package or contact the maintainer
#> This warning is displayed once every 8 hours.

Please let me know if you need any further details. Thanks!

[hadley]

That was fixed in the last version of pool; you might need to upgrade.

[nviraj]

Thanks for your response Hadley. I am already using pool 1.0.1.

Managed to get a reprex using PostgreSQL Docker and JDBC. Please let me know if I am doing something incorrectly or need to report this elsewhere.

Steps to reproduce:

1. Create docker image to connect to using the official image:
docker run --network=host --name postgresdb_reprex -e POSTGRES_PASSWORD=mysecretpassword -e POSTGRES_USER=postgres -d postgres

2. Download JAR file from here
Alternatively you can use the attached Project which contains the script and the JAR file for Windows.
pool_issue.zip

3. Run reprex code
reprex.R contains the actual code. Running through
reprex::reprex(input = "reprex.R", venue = "gh", session_info = TRUE)

Reprex Content:

library(DBI)
#> Warning: package 'DBI' was built under R version 4.3.1
library(pool)
#> Warning: package 'pool' was built under R version 4.3.1
library(dplyr)
#> Warning: package 'dplyr' was built under R version 4.3.1
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(RJDBC)
#> Warning: package 'RJDBC' was built under R version 4.3.1
#> Loading required package: rJava

# Connection details for docker image of postgres
connection_url <- "jdbc:postgresql://localhost:5432/postgres"
username <- "postgres"
password <- "mysecretpassword"
# Where is the JAR file stored
# JDBC downloaded through https://jdbc.postgresql.org/download/
jdbc_path <- "postgresql-42.6.0.jar"

# Create a JDBC driver
driver <-
  RJDBC::JDBC(
    driverClass = "org.postgresql.Driver",
    classPath = jdbc_path,
    identifier.quote = "'"
  )

# Establish connection through DBI
conn <- DBI::dbConnect(driver, connection_url,
  user = username,
  password = password
)
# Write table to database using DBI
if (!DBI::dbExistsTable(conn, "mtcars")) {
  DBI::dbWriteTable(conn, "mtcars", mtcars)
} else {
  base::message("Table already exists!")
}

# Create a Pool connection
con <- pool::dbPool(
  drv = driver, url = connection_url,
  user = username,
  password = password
)

# Connect to table
mtcars_db <- dplyr::tbl(con, "mtcars")
#> Warning: <JDBCConnection> uses an old dbplyr interface
#> ℹ Please install a newer version of the package or contact the maintainer
#> This warning is displayed once every 8 hours.

# Run sample query
mtcars_db %>%
  dplyr::filter(cyl == 8) %>%
  utils::head()
#> # Source:   SQL [6 x 11]
#> # Database: JDBCConnection
#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#> 2  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#> 3  16.4     8  276.   180  3.07  4.07  17.4     0     0     3     3
#> 4  17.3     8  276.   180  3.07  3.73  17.6     0     0     3     3
#> 5  15.2     8  276.   180  3.07  3.78  18       0     0     3     3
#> 6  10.4     8  472    205  2.93  5.25  18.0     0     0     3     4

^{Created on 2023-09-04 with reprex v2.0.2}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.3.0 (2023-04-21 ucrt)
#>  os       Windows 11 x64 (build 22621)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language (EN)
#>  collate  English_India.utf8
#>  ctype    English_India.utf8
#>  tz       Asia/Calcutta
#>  date     2023-09-04
#>  pandoc   3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  ! package     * version date (UTC) lib source
#>    blob          1.2.4   2023-03-17 [1] CRAN (R 4.3.1)
#>    cli           3.6.1   2023-03-23 [1] CRAN (R 4.3.1)
#>    DBI         * 1.1.3   2022-06-18 [1] CRAN (R 4.3.1)
#>    dbplyr        2.3.3   2023-07-07 [1] CRAN (R 4.3.1)
#>    digest        0.6.33  2023-07-07 [1] CRAN (R 4.3.1)
#>    dplyr       * 1.1.2   2023-04-20 [1] CRAN (R 4.3.1)
#>    evaluate      0.21    2023-05-05 [1] CRAN (R 4.3.1)
#>    fansi         1.0.4   2023-01-22 [1] CRAN (R 4.3.1)
#>    fastmap       1.1.1   2023-02-24 [1] CRAN (R 4.3.1)
#>    fs            1.6.3   2023-07-20 [1] CRAN (R 4.3.1)
#>    generics      0.1.3   2022-07-05 [1] CRAN (R 4.3.1)
#>    glue          1.6.2   2022-02-24 [1] CRAN (R 4.3.1)
#>    htmltools     0.5.6   2023-08-10 [1] CRAN (R 4.3.1)
#>    knitr         1.43    2023-05-25 [1] CRAN (R 4.3.1)
#>    later         1.3.1   2023-05-02 [1] CRAN (R 4.3.1)
#>    lifecycle     1.0.3   2022-10-07 [1] CRAN (R 4.3.1)
#>    magrittr      2.0.3   2022-03-30 [1] CRAN (R 4.3.1)
#>    pillar        1.9.0   2023-03-22 [1] CRAN (R 4.3.1)
#>    pkgconfig     2.0.3   2019-09-22 [1] CRAN (R 4.3.1)
#>    pool        * 1.0.1   2023-02-21 [1] CRAN (R 4.3.1)
#>    purrr         1.0.2   2023-08-10 [1] CRAN (R 4.3.1)
#>    R.cache       0.16.0  2022-07-21 [1] CRAN (R 4.3.1)
#>    R.methodsS3   1.8.2   2022-06-13 [1] CRAN (R 4.3.0)
#>    R.oo          1.25.0  2022-06-12 [1] CRAN (R 4.3.0)
#>    R.utils       2.12.2  2022-11-11 [1] CRAN (R 4.3.1)
#>    R6            2.5.1   2021-08-19 [1] CRAN (R 4.3.1)
#>    Rcpp          1.0.11  2023-07-06 [1] CRAN (R 4.3.1)
#>    reprex        2.0.2   2022-08-17 [1] CRAN (R 4.3.1)
#>  D rJava       * 1.0-6   2021-12-10 [1] CRAN (R 4.3.0)
#>    RJDBC       * 0.2-10  2022-03-24 [1] CRAN (R 4.3.1)
#>    rlang         1.1.1   2023-04-28 [1] CRAN (R 4.3.1)
#>    rmarkdown     2.24    2023-08-14 [1] CRAN (R 4.3.1)
#>    rstudioapi    0.15.0  2023-07-07 [1] CRAN (R 4.3.1)
#>    sessioninfo   1.2.2   2021-12-06 [1] CRAN (R 4.3.1)
#>    styler        1.10.2  2023-08-29 [1] CRAN (R 4.3.1)
#>    tibble        3.2.1   2023-03-20 [1] CRAN (R 4.3.1)
#>    tidyselect    1.2.0   2022-10-10 [1] CRAN (R 4.3.1)
#>    utf8          1.2.3   2023-01-31 [1] CRAN (R 4.3.1)
#>    vctrs         0.6.3   2023-06-14 [1] CRAN (R 4.3.1)
#>    withr         2.5.0   2022-03-03 [1] CRAN (R 4.3.1)
#>    xfun          0.40    2023-08-09 [1] CRAN (R 4.3.1)
#>    yaml          2.3.7   2023-01-23 [1] CRAN (R 4.3.0)
#> 
#>  [1] C:/Users/viraj/AppData/Local/R/win-library/4.3
#>  [2] C:/Program Files/R/R-4.3.0/library
#> 
#>  D ── DLL MD5 mismatch, broken installation.
#> 
#> ──────────────────────────────────────────────────────────────────────────────

4. Stop and remove Docker image

docker stop postgresdb_reprex
docker rm -f postgresdb_reprex

[hadley]

Can you confirm that you don't see the error if you connect directly without using pool? It's possible that this is a dbplyr bug.

Also, have you tried using RPostgres instead? That's likely to be faster, easier to set up, and less error prone.

[nviraj]

My use case is with Athena tables. It was easier to generate a reprex with PostgreSQL to test RJDBC + pool + dbplyr and rule out anything with the Database JDBC as well.
RAthena exists but has other Python dependencies which I'd like to avoid.

You are right! I just ran the above tbl + filter code using the DBI connection instead of pool and it shows the same warning.

[hadley]

In that case, can you please file a reprex at https://github.com/tidyverse/dbplyr/issues. Thanks for continuing to investigate this!