diff --git a/R/partition.R b/R/partition.R index fe85ecf..473e7a3 100644 --- a/R/partition.R +++ b/R/partition.R @@ -38,7 +38,7 @@ #' #' @return A list of copy jobs for the sharded tables that will be copied to one partitioned table #' -#' @seealso \href{Partitioned Tables Help}{https://cloud.google.com/bigquery/docs/creating-partitioned-tables} +#' @seealso \href{https://cloud.google.com/bigquery/docs/creating-partitioned-tables}{Partitioned Tables Help} #' @export #' @importFrom stats setNames bqr_partition <- function(sharded, diff --git a/man/bqr_partition.Rd b/man/bqr_partition.Rd index e5fce3e..e5ba347 100644 --- a/man/bqr_partition.Rd +++ b/man/bqr_partition.Rd @@ -52,5 +52,5 @@ Daily tables, however, have several disadvantages. You must manually, or program } \seealso{ -\href{Partitioned Tables Help}{https://cloud.google.com/bigquery/docs/creating-partitioned-tables} +\href{https://cloud.google.com/bigquery/docs/creating-partitioned-tables}{Partitioned Tables Help} } diff --git a/vignettes/bigQueryR.Rmd b/vignettes/bigQueryR.Rmd index 9b8d0b5..5ce9fba 100644 --- a/vignettes/bigQueryR.Rmd +++ b/vignettes/bigQueryR.Rmd @@ -21,8 +21,6 @@ This package is here as it uses [googleAuthR](https://github.com/MarkEdmondson12 It also has support for data extracts to Google Cloud Storage, meaning you can download data and make the download URL available to a user via their Google email. If you do a query normally with over 100000 results it hangs and errors. -An example of a BigQuery Shiny app running OAuth2 is here, the [BigQuery Visualiser](https://mark.shinyapps.io/bigquery-viz/) - ## Authentication Authentication is as used in other `googleAuthR` libraries: diff --git a/vignettes/bigQueryR.html b/vignettes/bigQueryR.html index 46d62e0..908963f 100644 --- a/vignettes/bigQueryR.html +++ b/vignettes/bigQueryR.html @@ -13,7 +13,7 @@ - +
This package is here as it uses googleAuthR as backend, so has Shiny support, and compatibility with other googleAuthR dependent packages.
It also has support for data extracts to Google Cloud Storage, meaning you can download data and make the download URL available to a user via their Google email. If you do a query normally with over 100000 results it hangs and errors.
-An example of a BigQuery Shiny app running OAuth2 is here, the BigQuery Visualiser