From 71facd6fab1985395854c3472e442c94444c314c Mon Sep 17 00:00:00 2001 From: Aaron Simumba Date: Thu, 24 Oct 2019 14:47:20 +0200 Subject: [PATCH] Update starting.Rmd small typo --- starting.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/starting.Rmd b/starting.Rmd index 4c45231..ff9652c 100644 --- a/starting.Rmd +++ b/starting.Rmd @@ -361,7 +361,7 @@ cars <- spark_read_csv(sc, "cars.csv") In the same way that R is known for its vibrant community of package authors, at a smaller scale, many extensions for Spark and R have been written and are available to you. The Extensions chapter will introduce many interesting ones to perform advanced modeling, graph analysis, preprocess datasets for deep learning, etc. -For instance, the `sparkly.nested` extension is an R package that extends `sparklyr` to help you manage values that contain nested information. A common use case arises when dealing with JSON files which contain nested lists that require preprocessing before doing meaningful data analysis. To use this extension, we have to first install it as follows: +For instance, the `sparklyr.nested` extension is an R package that extends `sparklyr` to help you manage values that contain nested information. A common use case arises when dealing with JSON files which contain nested lists that require preprocessing before doing meaningful data analysis. To use this extension, we have to first install it as follows: ```{r eval=FALSE, exercise=TRUE} install.packages("sparklyr.nested")