Rename set-up-a-data-science-client

garyericson · garyericson · commit 1ede55bf21ad · 2021-10-05T15:16:03.000-07:00
diff --git a/.openpublishing.redirection.json b/.openpublishing.redirection.json
@@ -42560,6 +42560,11 @@
       "redirect_url": "/sql/machine-learning/r/set-up-a-data-science-client",
       "redirect_document_id": true
     },
+    {
+      "source_path": "docs/sql/machine-learning/r/set-up-a-data-science-client.md",
+      "redirect_url": "/sql/machine-learning/r/set-up-data-science-client",
+      "redirect_document_id": true
+    },
     {
       "source_path": "docs/advanced-analytics/r/sql-server-configuration-r-services.md",
       "redirect_url": "/sql/machine-learning/r/sql-server-configuration-r-services",
diff --git a/docs/machine-learning/install/sql-machine-learning-standalone-windows-install.md b/docs/machine-learning/install/sql-machine-learning-standalone-windows-install.md
@@ -217,7 +217,7 @@ On disconnected servers, extra steps are required. You must obtain the cumulativ
 
 ## Development tools
 
-A development IDE is not installed as part of setup. For more information about configuring a development environment, see [Set up R tools](../r/set-up-a-data-science-client.md) and [Set up Python tools](../python/setup-python-client-tools-sql.md).
+A development IDE is not installed as part of setup. For more information about configuring a development environment, see [Set up R tools](../r/set-up-data-science-client.md) and [Set up Python tools](../python/setup-python-client-tools-sql.md).
 
 ## Next steps
 
diff --git a/docs/machine-learning/r/r-server-standalone.md b/docs/machine-learning/r/r-server-standalone.md
@@ -63,7 +63,7 @@ Install either one of these versions:
 
 On a standalone server, it's common to work locally using a development installed on the same computer.
 
-+ [Set up R tools](set-up-a-data-science-client.md)
++ [Set up R tools](set-up-data-science-client.md)
 + [Set up Python tools](../python/setup-python-client-tools-sql.md)
 
 ### Step 3: Write your first script
diff --git a/docs/machine-learning/r/ref-r-microsoftml.md b/docs/machine-learning/r/ref-r-microsoftml.md
@@ -24,7 +24,7 @@ The **MicrosoftML** package is based on R 3.5.2 and available only when you inst
 
 + [SQL Server 2016 R Services](../install/sql-r-services-windows-install.md)
 + [SQL Server Machine Learning Services](../install/sql-machine-learning-services-windows-install.md)
-+ [Microsoft R client](set-up-a-data-science-client.md)
++ [Microsoft R client](set-up-data-science-client.md)
 
 > [!NOTE]
 > Full product release versions are Windows-only in SQL Server 2017. Both Windows and Linux are supported for **MicrosoftML** in [SQL Server 2019](../../linux/sql-server-linux-setup-machine-learning.md).
diff --git a/docs/machine-learning/r/ref-r-revoscaler.md b/docs/machine-learning/r/ref-r-revoscaler.md
@@ -31,7 +31,7 @@ The **RevoScaleR** package is based on R 3.4.3 and available only when you insta
 
 + [SQL Server 2016 R Services](../install/sql-r-services-windows-install.md)
 + [SQL Server Machine Learning Services](../install/sql-machine-learning-services-windows-install.md)
-+ [Microsoft R client](set-up-a-data-science-client.md)
++ [Microsoft R client](set-up-data-science-client.md)
 
 > [!NOTE]
 > Full product release versions are Windows-only in SQL Server 2017. Both Windows and Linux are supported for **RevoScaleR** in [SQL Server 2019](../../linux/sql-server-linux-setup-machine-learning.md).
diff --git a/docs/machine-learning/r/set-up-data-science-client.md b/docs/machine-learning/r/set-up-data-science-client.md
diff --git a/docs/machine-learning/r/sql-server-r-services.md b/docs/machine-learning/r/sql-server-r-services.md
@@ -51,7 +51,7 @@ There are two ways to execute R scripts in R Services:
 
 + The most common way is to use the T-SQL stored procedure [sp_execute_external_script](../../relational-databases/system-stored-procedures/sp-execute-external-script-transact-sql.md).
 
-+ You can also use your preferred R client and write scripts that push the execution (referred to as a *remote compute context*) to a remote SQL Server. See how to [set up a data science client R development](../r/set-up-a-data-science-client.md) for more information.
++ You can also use your preferred R client and write scripts that push the execution (referred to as a *remote compute context*) to a remote SQL Server. See how to [set up a data science client R development](../r/set-up-data-science-client.md) for more information.
 
 <a name="version"></a>
 
@@ -79,7 +79,7 @@ You can use open-source packages and frameworks, in addition to Microsoft's ente
 | [RevoScaleR](../r/ref-r-revoscaler.md) | The primary package for scalable R. Data transformations and manipulation, statistical summarization, visualization, and many forms of modeling. Additionally, functions in this package automatically distribute workloads across available cores for parallel processing. |
 | [MicrosoftML (R)](../r/ref-r-microsoftml.md) | Adds machine learning algorithms to create custom models for text analysis, image analysis, and sentiment analysis. |
 | [olapR](../r/ref-r-olapr.md) | R functions used for MDX queries against a SQL Server Analysis Services OLAP cube. |
-| [sqlrutils](../r/ref-r-sqlrutils.md) | A mechanism to use R scripts in a T-SQL stored procedure, register that stored procedure with a database, and run the stored procedure from an [R development environment](../r/set-up-a-data-science-client.md). |
+| [sqlrutils](../r/ref-r-sqlrutils.md) | A mechanism to use R scripts in a T-SQL stored procedure, register that stored procedure with a database, and run the stored procedure from an [R development environment](../r/set-up-data-science-client.md). |
 | [Microsoft R Open](https://mran.microsoft.com/rro) | Microsoft R Open (MRO) is the enhanced distribution of R from Microsoft. It is a complete open-source platform for statistical analysis and data science. It is based on and 100% compatible with R, and includes additional capabilities for improved performance and reproducibility. |
 
 ## How do I get started with R Services?
@@ -89,7 +89,7 @@ You can use open-source packages and frameworks, in addition to Microsoft's ente
 1. Configure your development tools. You can use:
 
     + [Azure Data Studio](../../azure-data-studio/what-is-azure-data-studio.md) or [SQL Server Management Studio (SSMS)](../../ssms/sql-server-management-studio-ssms.md) to use T-SQL and the stored procedure [sp_execute_external_script](../../relational-databases/system-stored-procedures/sp-execute-external-script-transact-sql.md) to execute your R script.
-    + R on your own development laptop or workstation to execute scripts. You can either pull data down locally or push the execution remotely to SQL Server with [RevoScaleR](../r/ref-r-revoscaler.md). See how to [set up a data science client R development](../r/set-up-a-data-science-client.md) for more information.
+    + R on your own development laptop or workstation to execute scripts. You can either pull data down locally or push the execution remotely to SQL Server with [RevoScaleR](../r/ref-r-revoscaler.md). See how to [set up a data science client R development](../r/set-up-data-science-client.md) for more information.
 
 1. Write your first R script
 
@@ -101,4 +101,4 @@ You can use open-source packages and frameworks, in addition to Microsoft's ente
 ## Next steps
 
 + [Install SQL Server 2016 R Services](../install/sql-r-services-windows-install.md)
-+ [Set up a data science client for R development](../r/set-up-a-data-science-client.md)
++ [Set up a data science client for R development](../r/set-up-data-science-client.md)
diff --git a/docs/machine-learning/sql-server-machine-learning-services.md b/docs/machine-learning/sql-server-machine-learning-services.md
@@ -95,7 +95,7 @@ You can use open-source packages and frameworks, in addition to Microsoft's ente
 | R | [RevoScaleR](r/ref-r-revoscaler.md) | The primary package for scalable R. Data transformations and manipulation, statistical summarization, visualization, and many forms of modeling. Additionally, functions in this package automatically distribute workloads across available cores for parallel processing. |
 | R | [MicrosoftML (R)](r/ref-r-microsoftml.md) | Adds machine learning algorithms to create custom models for text analysis, image analysis, and sentiment analysis. |
 | R | [olapR](r/ref-r-olapr.md) | R functions used for MDX queries against a SQL Server Analysis Services OLAP cube. |
-| R | [sqlrutils](r/ref-r-sqlrutils.md) | A mechanism to use R scripts in a T-SQL stored procedure, register that stored procedure with a database, and run the stored procedure from an [R development environment](r/set-up-a-data-science-client.md). |
+| R | [sqlrutils](r/ref-r-sqlrutils.md) | A mechanism to use R scripts in a T-SQL stored procedure, register that stored procedure with a database, and run the stored procedure from an [R development environment](r/set-up-data-science-client.md). |
 | R | [Microsoft R Open](https://mran.microsoft.com/rro) | Microsoft R Open (MRO) is the enhanced distribution of R from Microsoft. It is a complete open-source platform for statistical analysis and data science. It is based on and 100% compatible with R, and includes additional capabilities for improved performance and reproducibility. |
 
 For more information on which packages are installed with Machine Learning Services and how to install other packages, see:
diff --git a/docs/machine-learning/toc.yml b/docs/machine-learning/toc.yml
@@ -53,7 +53,7 @@ items:
   - name: Set up a Python client
     href: ../machine-learning/python/setup-python-client-tools-sql.md
   - name: Set up an R client
-    href: ../machine-learning/r/set-up-a-data-science-client.md
+    href: ../machine-learning/r/set-up-data-science-client.md
   - name: Install on Azure VM
     href: ../machine-learning/install/sql-machine-learning-azure-virtual-machine.md
   - name: Install standalone server
diff --git a/docs/machine-learning/tutorials/deepdive-create-sql-server-data-objects-using-rxsqlserverdata.md b/docs/machine-learning/tutorials/deepdive-create-sql-server-data-objects-using-rxsqlserverdata.md
@@ -26,7 +26,7 @@ From R, connect to SQL Server and use **RevoScaleR** functions to perform the fo
 
 Sample data is simulated credit card fraud data (the ccFraud dataset), partitioned into training and scoring datasets. The data file is included in **RevoScaleR**.
 
-Use an R IDE or **Rgui** to complete these taks. Be sure to use the R executables found at this location: C:\Program Files\Microsoft\R Client\R_SERVER\bin\x64 (either Rgui.exe if you are using that tool, or an R IDE pointing to C:\Program Files\Microsoft\R Client\R_SERVER). Having an [R client workstation](../r/set-up-a-data-science-client.md) with these executables is considered a prerequisite of this tutorial.
+Use an R IDE or **Rgui** to complete these taks. Be sure to use the R executables found at this location: C:\Program Files\Microsoft\R Client\R_SERVER\bin\x64 (either Rgui.exe if you are using that tool, or an R IDE pointing to C:\Program Files\Microsoft\R Client\R_SERVER). Having an [R client workstation](../r/set-up-data-science-client.md) with these executables is considered a prerequisite of this tutorial.
 
 ## Create the training data table
 
diff --git a/docs/machine-learning/tutorials/deepdive-custom-r-functions-using-rxexec.md b/docs/machine-learning/tutorials/deepdive-custom-r-functions-using-rxexec.md
@@ -28,7 +28,7 @@ The **rxExec** function in **RevoScaleR** provides a mechanism for running any R
   
 + [Database permissions](../security/user-permission.md) and a SQL Server database user login
 
-+ [A development workstation with the RevoScaleR libraries](../r/set-up-a-data-science-client.md)
++ [A development workstation with the RevoScaleR libraries](../r/set-up-data-science-client.md)
 
 The R distribution on the client workstation provides a built-in **Rgui** tool that you can use to run the R script in this tutorial. You can also use an IDE such as RStudio or R Tools for Visual Studio.
 
diff --git a/docs/machine-learning/tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md b/docs/machine-learning/tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md
@@ -37,7 +37,7 @@ If you need to put client and server on the same computer, be sure to install a
 + C:\Program Files\Microsoft\R Client\R_SERVER\library\RevoScaleR 
 + C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\R_SERVICES\library\RevoScaleR
 
-For instructions on client configuration, see [Set up a data science client for R development](../r/set-up-a-data-science-client.md).
+For instructions on client configuration, see [Set up a data science client for R development](../r/set-up-data-science-client.md).
 
 
 ## R development tools
@@ -50,7 +50,7 @@ R developers typically use IDEs for writing and debugging R code. Here are some
 
 - Basic R tools (R.exe, RTerm.exe, RScripts.exe) are also installed by default when you install R in SQL Server or R Client. If you do not wish to install an IDE, you can use built-in R tools to execute the code in this tutorial.
 
-Recall that **RevoScaleR** is required on both local and remote computers. You cannot complete this tutorial using a generic installation of RStudio or other environment that's missing the Microsoft R libraries. For more information, see [Set Up a Data Science Client](../r/set-up-a-data-science-client.md).
+Recall that **RevoScaleR** is required on both local and remote computers. You cannot complete this tutorial using a generic installation of RStudio or other environment that's missing the Microsoft R libraries. For more information, see [Set Up a Data Science Client](../r/set-up-data-science-client.md).
 
 ## Summary of tasks
 
diff --git a/docs/machine-learning/tutorials/walkthrough-data-science-end-to-end-walkthrough.md b/docs/machine-learning/tutorials/walkthrough-data-science-end-to-end-walkthrough.md
@@ -34,7 +34,7 @@ Because the walkthrough is designed to introduce R developers to [!INCLUDE[rsql_
 
 + An R IDE such as RStudio or the built-in RGUI tool included with R
 
-We recommend that you do this walkthrough on a client workstation. You must be able to connect, on the same network, to a [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] computer with SQL Server and the R language enabled. For instructions on workstation configuration, see [Set up a data science client for R development](../r/set-up-a-data-science-client.md).
+We recommend that you do this walkthrough on a client workstation. You must be able to connect, on the same network, to a [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] computer with SQL Server and the R language enabled. For instructions on workstation configuration, see [Set up a data science client for R development](../r/set-up-data-science-client.md).
 
 Alternatively, you can run the walkthrough on a computer that has both [!INCLUDE[ssNoVersion](../../includes/ssnoversion-md.md)] and an R development environment, but we don't recommend this configuration for a production environment. If you need to put client and server on the same computer, be sure to install a second set of Microsoft R libraries for sending R script from a "remote" client. Do not use the R libraries that are installed in the program files of the SQL Server instance. Specifically, if you are using one computer, you need the RevoScaleR library in both of these locations to support client and server operations.
 
diff --git a/docs/machine-learning/tutorials/walkthrough-view-and-summarize-data-using-r.md b/docs/machine-learning/tutorials/walkthrough-view-and-summarize-data-using-r.md
@@ -24,7 +24,7 @@ This lesson introduces you to functions in the **RevoScaleR** package and steps
 
 ## Define a SQL Server compute context
 
-Run the following R statements in an R environment on the client workstation. This section assumes a [data science workstation with Microsoft R Client](../r/set-up-a-data-science-client.md), because it includes all the RevoScaleR packages, as well as a basic, lightweight set of R tools. For example, you can use Rgui.exe to run the R script in this section.
+Run the following R statements in an R environment on the client workstation. This section assumes a [data science workstation with Microsoft R Client](../r/set-up-data-science-client.md), because it includes all the RevoScaleR packages, as well as a basic, lightweight set of R tools. For example, you can use Rgui.exe to run the R script in this section.
 
 1. If the **RevoScaleR** package is  not already loaded, run this line of R code:
 
