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bnosac · Apr 19, 2021 · 5c38ff6 · 5c38ff6
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diff --git a/R/read_sas.R b/R/read_sas.R
@@ -6,10 +6,10 @@
 #' Mark that files on the local file system need to be specified using the full path.
 #' @param table character string with the name of the Spark table where the SAS dataset will be put into
 #' @return an object of class \code{tbl_spark}, which is a reference to a Spark DataFrame based on which
-#' dplyr functions can be executed. See \url{https://github.com/rstudio/sparklyr}
+#' dplyr functions can be executed. See \url{https://github.com/sparklyr/sparklyr}
 #' @export
 #' @seealso \code{\link[sparklyr]{spark_connect}}, \code{\link[sparklyr]{sdf_register}}
-#' @references \url{https://spark-packages.org/package/saurfang/spark-sas7bdat}, \url{https://github.com/saurfang/spark-sas7bdat}, \url{https://github.com/rstudio/sparklyr}
+#' @references \url{https://spark-packages.org/package/saurfang/spark-sas7bdat}, \url{https://github.com/saurfang/spark-sas7bdat}, \url{https://github.com/sparklyr/sparklyr}
 #' @examples
 #' \dontrun{
 #' ## If you haven't got a Spark cluster, you can install Spark locally like this

diff --git a/README.md b/README.md
@@ -1,13 +1,13 @@
 # spark.sas7bdat
 
-The  **spark.sas7bdat** package allows R users working with [Apache Spark](https://spark.apache.org) to read in [SAS](http://www.sas.com) datasets in .sas7bdat format into Spark by using the [spark-sas7bdat Spark package](https://spark-packages.org/package/saurfang/spark-sas7bdat). This allows R users to 
+The  **spark.sas7bdat** package allows R users working with [Apache Spark](https://spark.apache.org) to read in [SAS](https://www.sas.com) datasets in .sas7bdat format into Spark by using the [spark-sas7bdat Spark package](https://spark-packages.org/package/saurfang/spark-sas7bdat). This allows R users to 
 
 - load a SAS dataset in parallel into a Spark table for further processing with the [sparklyr](https://cran.r-project.org/package=sparklyr) package
 - process in parallel the full SAS dataset with dplyr statements, instead of having to import the full SAS dataset in RAM (using the foreign/haven packages) and hence avoiding RAM problems of large imports
 
 
 ## Example
-The following example reads in a file called iris.sas7bdat in a table called sas_example in Spark. Do try this with bigger data on your cluster and look at the help of the [sparklyr](https://github.com/rstudio/sparklyr) package to connect to your Spark cluster.
+The following example reads in a file called iris.sas7bdat in a table called sas_example in Spark. Do try this with bigger data on your cluster and look at the help of the [sparklyr](https://github.com/sparklyr/sparklyr) package to connect to your Spark cluster.
 
 ```r
 library(sparklyr)

diff --git a/inst/NEWS b/inst/NEWS
@@ -1,5 +1,6 @@
                 CHANGES IN spark.sas7bdat VERSION 1.4
 
+    o    Fix URL's
     o    Add rmarkdown to Suggests in DESCRIPTION
 
                 CHANGES IN spark.sas7bdat VERSION 1.3

diff --git a/man/spark_read_sas.Rd b/man/spark_read_sas.Rd
diff --git a/vignettes/spark_sas7bdat_examples.Rmd b/vignettes/spark_sas7bdat_examples.Rmd
@@ -9,18 +9,18 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-This R package allows R users to easily import large [SAS](http://www.sas.com) datasets into [Spark](https://spark.apache.org) tables in parallel.
+This R package allows R users to easily import large [SAS](https://www.sas.com) datasets into [Spark](https://spark.apache.org) tables in parallel.
 
 
-The package uses the [spark-sas7bdat Spark package](https://spark-packages.org/package/saurfang/spark-sas7bdat) in order to read a SAS dataset in Spark. That Spark package imports the data in parallel on the Spark cluster using the Parso library and this process is launched from R using the [sparklyr](https://github.com/rstudio/sparklyr) functionality. 
+The package uses the [spark-sas7bdat Spark package](https://spark-packages.org/package/saurfang/spark-sas7bdat) in order to read a SAS dataset in Spark. That Spark package imports the data in parallel on the Spark cluster using the Parso library and this process is launched from R using the [sparklyr](https://github.com/sparklyr/sparklyr) functionality. 
 
 More information about the spark-sas7bdat Spark package and sparklyr can be found at:
 
 - https://spark-packages.org/package/saurfang/spark-sas7bdat and https://github.com/saurfang/spark-sas7bdat
-- https://github.com/rstudio/sparklyr
+- https://github.com/sparklyr/sparklyr
 
 ## Example
-The following example reads in a file called iris.sas7bdat in parallel in a table called sas_example in Spark. Do try this with bigger data on your cluster and look at the help of the [sparklyr](https://github.com/rstudio/sparklyr) package to connect to your Spark cluster.
+The following example reads in a file called iris.sas7bdat in parallel in a table called sas_example in Spark. Do try this with bigger data on your cluster and look at the help of the [sparklyr](https://github.com/sparklyr/sparklyr) package to connect to your Spark cluster.
 
 ```{r, eval=FALSE}
 library(sparklyr)