Edits to package management topics and test of scenarios

Author: jeannt

docs/advanced-analytics/r/create-a-local-package-repository-using-minicran.md

@@ -1,7 +1,7 @@
 ---
 title: "Create a local package repository using miniCRAN | Microsoft Docs"
 ms.custom: ""
-ms.date: "01/04/2018"
+ms.date: "02/20/2018"
 ms.reviewer: 
 ms.suite: sql
 ms.prod: machine-learning-services
@@ -21,47 +21,50 @@ ms.workload: "Inactive"
 # Create a local package repository using miniCRAN
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md-winonly](../../includes/appliesto-ss-xxxx-xxxx-xxx-md-winonly.md)]
 
-There are two ways that you can prepare R packages for installation onto a server without internet access.
+The [miniCRAN](https://cran.r-project.org/web/packages/miniCRAN/index.html)  package was created by Andre de Vries to support these common scenarios: 
 
--   [Use the miniCRAN package to create a single local repository](#bkmk_miniCRAN)
++ Analyzing package dependencies for a single package or set of packages
++ Preparing a set of R packages for installation onto a server without internet access.
 
-    The [miniCRAN](https://cran.r-project.org/web/packages/miniCRAN/index.html) creates an internally consistent repository consisting of selected packages from CRAN-like repositories. The user specifies a set of desired packages, and miniCRAN recursively reads the dependency tree for these packages, and downloads only the listed packages and their dependencies.
+The user specifies a set of desired packages, and miniCRAN recursively reads the dependency tree for these packages, and downloads only the listed packages and their dependencies from CRAN or similar repositories. 
 
-    You can then move this local repository to the server, and proceed to install the packages without using the internet.
+As an output, miniCRAN creates an internally consistent repository consisting of the selected packages and all required dependencies. You can then move this local repository to the server, and proceed to install the packages without using the internet.
 
--   [Manually download and copy packages one by one](#bkmk_manual)
+Experienced R users often look for the list of dependent packages in the DESCRIPTION file for the downloaded package. However, packages listed in **Imports** might have second-level dependencies. For this reason, we recommend use of the **miniCRAN** method.
 
-    You can find the list of dependent packages in the DESCRIPTION file for the downloaded package. 
-    
-    However, packages listed in **Imports** might have second-level dependencies. For this reason, we recommend use of the **miniCRAN** method.
-
-> [!TIP]
-> Did you know that you can use miniCRAN to prepare packages for use in Azure Machine Learning? For more information, see this blog: [Using miniCRAN in Azure ML, by Michele Usuelli](https://www.r-bloggers.com/using-minicran-in-azure-ml/) 
 
-## Prepare packages using miniCRAN
+## What is a package repository
 
-The goal of creating a local package repository is to provide a single location that a server administrator or other users in the organization can use to install new R packages on a server that does not have internet access.
+The goal of creating a local package repository is to provide a single location that a server administrator or other users in the organization can use to install new R packages on a server that does not have internet access. After creating the repository, you can modify it by adding new packages or upgrading the version of existing packages.
 
 The [miniCRAN](https://cran.r-project.org/web/packages/miniCRAN/index.html) package for R was written by [Andre de Vries](http://blog.revolutionanalytics.com/2016/05/minicran-sql-server.html) to make it easier to create a consistent, managed set of R packages for an organization. 
 
-There are many advantages to using miniCRAN to create the repository:
+Package repositories are useful in these scenarios:
 
 -   **Security**: Many R users are accustomed to downloading and installing new R packages at will, from CRAN or one of its mirror sites. However, for security reasons, production servers running [!INCLUDE[ssNoVersion_md](..\..\includes\ssnoversion-md.md)] typically do not have internet connectivity.
 
 -   **Easier offline installation**: To install package to an offline server requires that you also download all package dependencies, Using miniCRAN makes it easier to get all dependencies in the correct format.
 
 -   **Improved version management**: In a multiuser environment, there are good reasons to avoid unrestricted installation of multiple package versions on the server.
 
-After creating the repository, you can modify it by adding new packages or upgrading the version of existing packages.
+By using miniCRAN, you can avoid package dependency errors when using the CREATE EXTERNAL LIBRARY statement. 
+
+You can also use miniCRAN to prepare packages for use in Azure Machine Learning. For more information, see this blog: [Using miniCRAN in Azure ML, by Michele Usuelli](https://www.r-bloggers.com/using-minicran-in-azure-ml/) 
+
+
+## Prepare packages using miniCRAN
+
+The **miniCRAN** package itself is dependent on 18 other CRAN packages, among which is the **RCurl** package, which has a system dependency on the **curl-devel** package. Similarly, package **XML** has a dependency on **libxml2-devel**. 
+
+For these reasons, we recommend that you build your local repository initially on a machine with full Internet access, so that you can easily satisfy all these dependencies. 
 
-> [!NOTE]
-> The miniCRAN package itself is dependent on 18 other CRAN packages, among which is the RCurl package, which has a system dependency on the curl-devel package. Similarly, package XML has a dependency on libxml2-devel. We recommend, therefore, that you build your local repository initially on a machine with full Internet access, so that you can easily satisfy all these dependencies. After created, you can move the repository to a different location.
+After the repository has been created, you can move the repository to a different location.
 
 ### Step 1. Install the miniCRAN package
 
-You begin by creating a miniCRAN repository to use as a source. You should create this repository on a computer that has internet access.
+You begin by creating a **miniCRAN** repository to use as a source. You should create this repository on a computer that has internet access.
 
-1.  Install the miniCRAN package and the required **igraph** package.
+1.  Install the **miniCRAN** package and the required **igraph** package.
 
     ```R
     if(!require("miniCRAN")) install.packages("miniCRAN") if(!require("igraph"))
@@ -73,7 +76,7 @@ You begin by creating a miniCRAN repository to use as a source. You should creat
 1. Specify a mirror site to use in getting packages.
 
     ```R
-    CRAN_mirror \<- c(CRAN = "https://mran.microsoft.com/snapshot/2017-08-01")
+    CRAN_mirror <- c(CRAN = "https://mran.microsoft.com/snapshot/2017-08-01")
     ```
 
 2.  Type the name of a local folder in which to store the collected packages. 
@@ -90,13 +93,13 @@ You begin by creating a miniCRAN repository to use as a source. You should creat
 
 ### Step 3. Add packages to the repository
 
-1.  After miniCRAN is installed, create a list that specifies the additional packages you want to download.
+1.  After **miniCRAN** is installed, create a list that specifies the additional packages you want to download.
 
-    Do not add dependencies to this initial list; the **igraph** package used by miniCRAN generates the list of dependencies for you. For more information about how to use the generated dependency graph, see [Using miniCRAN to identify package
+    Do **not** add dependencies to this initial list. The **igraph** package used by **miniCRAN** generates the list of dependencies for you. For more information about how to use the generated dependency graph, see [Using miniCRAN to identify package
     dependencies](https://cran.r-project.org/web/packages/miniCRAN/vignettes/miniCRAN-dependency-graph.html).
 
-    The following R script demonstrates how to get the target packages, "zoo"
-    and "forecast".
+    The following R script adds the target packages, "zoo"
+    and "forecast" to a variable.
 
     ```R
     pkgs_needed <- c("zoo", "forecast")
@@ -135,7 +138,7 @@ Depending on the version of SQL Server, there are two options for adding new pac
 
 - Install to the instance library using the miniCRAN repository and R tools.
 
-- Upload packages to a SQL Server database and install using the CREATE EXTERNAL LIBRARY statement. This option requires SQL Server 2017. See [Install additional R packages on SQL Server](install-additional-r-packages-on-sql-server.md).
+- Upload packages to a location on the SQL Server computer, and install using the CREATE EXTERNAL LIBRARY statement. This option requires SQL Server 2017. 
 
 The following procedure describes how to install the packages using R tools.
 
@@ -160,7 +163,7 @@ The following procedure describes how to install the packages using R tools.
 
     On SQL Server, this command should return the path of the library associated with the instance, such as: "C:/Program Files/Microsoft SQL Server/MSSQL14.MSSQLSERVER/R_SERVICES/library "
 
-4.  Specify the location on the server where you copied the mininCRAN repository in `server_repo`.
+4.  Specify the location on the server where you copied the **miniCRAN** repository in `server_repo`.
 
     In this example, we assume that you copied the repository to your user folder on the server.
 
@@ -187,21 +190,18 @@ The following procedure describes how to install the packages using R tools.
     ```
 
 > [!NOTE] 
-> In SQL Server, a server administrator must install packages from the miniCRAN repository into the default library used by the instance. 
+> To use the package in SQL Server, the packages must be installed into the default library used by the instance. 
 
-## Manually download single packages
+## Manually install a single package from a zipped file
 
-If you do not want to use miniCRAN, you can also manually download the packages you need, and their dependencies. To do this requires that you are either an administrator or sole owner of a server.
+If you are installing a single package that has no dependencies, or you cannot use **miniCRAN**, you can also manually download the package you need. To do this requires that you are either an administrator or sole owner of a server.
 
 After downloading the packages, you install the R packages from the zipped file location.
 
-1. Download the packages zip files, and save them in a local folder
+1. Download the package as a zipped file, and save it in a local folder
 
 2. Copy that folder to the [!INCLUDE[ssNoVersion_md](..\..\includes\ssnoversion-md.md)] computer.
 
-3. Install the packages into the SQL Server instance library.
+3. Install the packages into the SQL Server instance library using conventional R commands. If the package has dependencies that are not already installed, and you have not included them, installation might fail. 
 
-> [!NOTE]
-> When you use R tools to install packages, they are installed for the instance as a whole. 
-> 
-> If you want to install the package into a database and share the package with users using database roles, you must upload the library using the CREATE EXTERNAL LIBRARY statement. See [Install additional R packages in SQL Server](install-additional-r-packages-on-sql-server.md)
+You can also upload individual packages into an instance of SQL Server 2017, by using the CREATE EXTERNAL LIBRARY statement. This feature requires some additional steps to prepare the server. For example, a script must be run to create database roles on the instance and on specific databases. If the package library is successfully created, you must then install the package into the R environment by calling install.packages from sp_execute_external_script. For more information, see these resources: