Bringing even with master.

Author: v-anpasi

.openpublishing.redirection.json

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docs/advanced-analytics/python/architecture-overview-sql-server-python.md

@@ -1,7 +1,7 @@
 ---
 title: "Architecture | Microsoft Docs"
 ms.custom: ""
-ms.date: "04/18/2017"
+ms.date: "07/11/2017"
 ms.prod: "sql-server-2016"
 ms.reviewer: ""
 ms.suite: ""
@@ -13,21 +13,20 @@ author: "jeannt"
 ms.author: "jeannt"
 manager: "jhubbard"
 ---
-
-# Architecture Overview - Machine Learning Services with Python
+# Architecture overview for Machine Learning Services with Python
 
 This topic provides an overview of how Python is integrated with SQL Server, including the security model, the components in the database engine that support external script execution, and new components that enable interoperability of Python with SQL Server. For details see the linked topics.
 
 > [!IMPORTANT]
-> Support for Python is available beginning with SQL Server 2017. This is a pre-release feature and subject to change.
+> Support for Python is available beginning with SQL Server 2017 CTP 2.0. This is a pre-release feature and subject to change.
 
-## Python Interoperability
+## Python interoperability
 
-SQL Server Machine Learning Services (In-Database) installs the Anaconda distribution of Python, and the Python 3.5 runtime and interpreter. This ensure near-complete compatibility with standard Python solutions. Python runs in a separate process from SQL Server, to ensure that database operations are not compromised.
+SQL Server Machine Learning Services (In-Database) installs the Anaconda distribution of Python, and the Python 3.5 runtime and interpreter. This ensures near-complete compatibility with standard Python solutions. Python runs in a separate process from SQL Server, to guarantee that database operations are not compromised.
 
-For more information about the interaction of SQL Server with Python, see [Python Interoperability](/python-interoperability.md)
+For more information about the interaction of SQL Server with Python, see [Python interoperability](/python-interoperability.md)
 
-## New Components that Support Python Integration
+## Components that support Python integration
 
 The extensibility framework introduced in SQL Server 2016 now supports execution of Python script, through the addition of new language-specific components. These components improve data exchange speed and compression, while providing a secure, high-performance platform for running external scripts.
 
@@ -41,12 +40,12 @@ All tasks are secured by Windows job objects or SQL Server security. Data is kep
 
 For details, see [Security for Python](../../advanced-analytics/python/security-overview-sql-server-python-services.md)
 
-## Resource Governance
+## Resource governance
 
 In SQL Server Enterprise Edition, you can use Resource Governor to manage and monitor resource use of external script operations, including R script and Python scripts.
 
 For more information, see [Resource Governance for R](../../advanced-analytics/r/resource-governance-for-r-services.md).
 
-## See Also
+## Next steps
 
-[Run Python using T-SQl](../tutorials/run-python-using-t-sql.md)
+[Run Python using T-SQL](../tutorials/run-python-using-t-sql.md)

docs/advanced-analytics/python/media/remote-sqlcc-from-python2.png

@@ -1,5 +1,5 @@
 ---
-title: "New Components for Python Integration | Microsoft Docs"
+title: "Components for Python integration with SQL Server | Microsoft Docs"
 ms.custom: ""
 ms.date: "03/30/2017"
 ms.prod: "sql-server-2016"
@@ -13,13 +13,13 @@ author: "jeannt"
 ms.author: "jeannt"
 manager: "jhubbard"
 ---
-# New components in SQL Server to Support Python Integration
+# Components in SQL Server to support Python integration
 
-Beginning in SQL Server 2017, Machine Learning Services supports Python as an external language that can be executed from T-SQL, or executed remotely using SQL Server as the compute context. 
+Beginning in SQL Server 2017, Machine Learning Services supports Python as an external language that can be executed from T-SQL, or executed remotely using SQL Server as the compute context.
 
 This topic describes the components in SQL Server 2017 that support extensibility in general and the Python language specifically.
 
-## SQL Server Components and Providers
+## SQL Server components and providers
 
 To configure SQL Server 2017 to allow Python script execution is a multi-step process.
 
@@ -29,29 +29,34 @@ To configure SQL Server 2017 to allow Python script execution is a multi-step pr
 
 Additional steps might be required to support remote script execution.
 
-For more information, see [Set up Machine LEarnign Services](setup-python-machine-learning-services.md)
+For more information, see [Set up Machine Learning Services](setup-python-machine-learning-services.md)
 
-### **Launchpad**
+### Launchpad
 
 The SQL Server Trusted Launchpad is a service introduced in SQL Server 2016 that manages and executes external scripts, similar to the way that the full-text indexing and query service launches a separate host for processing full-text queries.
 
-The Launchpad service will start only trusted launchers that are published by Microsoft, or that have been certified by Microsoft as meeting requirements for performance and resource management.
+The Launchpad service can start only trusted launchers that are published by Microsoft, or that have been certified by Microsoft as meeting requirements for performance and resource management.
+
 + SQL Server 2016 supports R
 + SQL Server 2017 supports R and Python 3.5
 
 The [!INCLUDE[rsql_launchpad_md](../../includes/rsql-launchpad-md.md)] service runs under its own user account.
 
+> [!TIP]
+> If you change the account that runs Launchpad, be sure to do so using SQL Server Configuration Manager, to ensure that changes are written to related files.
+
 To execute tasks in a specific supported language, the Launchpad gets a secured worker account from the pool, and starts a satellite process to manage the external runtime:
+
 + RLauncher.dll for the R language
 + Pythonlauncher.dll for Python 3.5
 
 Each satellite process inherits the user account of the Launchpad and uses that worker account for the duration of script execution. If the Python script uses parallel processes, they are created under the same, single worker account.
 
 For more information about the security context of the Launchpad, see [Security](security-overview-sql-server-python-services.md).
 
-### **BxlServer and SQL Satellite**
+### BxlServer and SQL Satellite
 
-If you run Process Explorer while a Python job is running, you might see one or multiple instances of BxlServer.
+If you run [Process Explorer](https://technet.microsoft.com/sysinternals/processexplorer.aspx) while a Python job is running, you might see one or multiple instances of BxlServer.
 
 **BxlServer** is an executable provided by Microsoft that manages communication between [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] and Python (or R). It creates the Windows job objects that are used to contain external script sessions, provisions secure working folders for each external script job, and uses SQL Satellite to manage data transfer between the external runtime and [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)].
 
@@ -72,28 +77,29 @@ SQL Satellite uses a custom data format that is optimized for fast data transfer
 
 The SQL Satellite can be monitored by using windows extended events (xEvents). For more information, see [Extended Events for R](../../advanced-analytics/r/extended-events-for-sql-server-r-services.md).
 
-
-## Communication Channels Between Components
+## Communication channels between components
 
 + **TCP/IP**
+
   By default, internal communications between [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] and the SQL Satellite use TCP/IP.
 
 + **Named Pipes**
 
   Internal data transport between the BxlServer and [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] through SQL Satellite uses a proprietary, compressed data format to enhance performance. Data is exchanged between Python and BxlServer in BXL format, using Named Pipes.
 
 + **ODBC**
+
   Communications between external data science clients and the [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] instance use ODBC. The account that sends the script jobs to [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] must have both permissions to connect to the instance and to run external scripts.
 
   Additionally, depending on the task, the account might need these permissions:
+
   + Read data used by the job
   + Write data to tables: for example, when saving results to a table
   + Create database objects: for example, if saving external script as part of a new stored procedure.
 
   When [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] is used as the compute context for Python script executed from a remote client, and the Python executable must retrieve data from an external source, ODBC is used for writeback. [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] will map the identity of the user issuing the remote command to the identity of the user on the current instance, and run the ODBC command using that user's credentials. The connection string needed to perform this ODBC call is obtained from the client code.
 
-
-## Interaction of Components
+## Interaction of components
 
 The following diagrams depict the interaction of SQL Server components with the Python runtime in each of the supported scenarios: running script in-database, and remote execution from a Python terminal, using a SQL Server compute context.
 
@@ -111,27 +117,29 @@ After the script has been embedded in the stored procedure, any application that
 4. BxlServer coordinates with the Python runtime to manage exchanges of data, and storage of working results.
 5. SQL Satellite manages communications about related tasks and processes with [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)].
 6. BxlServer uses SQL Satellite to communicate status and results to [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)].
-7. [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] gets results and closes related tasks and processes. 
-
+7. [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] gets results and closes related tasks and processes.
 
 ### Python scripts executed from a remote client
 
 You can run Python scripts from a remote computer, such as a laptop, and have them execute in the context of the SQl Server computer, if these conditions are met:
+
 + You design the scripts appropriately
-+ The remote computer has installed the extensibility libraries that are used by Machine Learning Services. 
++ The remote computer has installed the extensibility libraries that are used by Machine Learning Services
 
 The following diagram summarizes the overall workflow when scripts are sent from a remote computer.
 
-![remote-sqlcc-from-python](../../advanced-analytics/python/media/remote-sqlcc-from-python.png)
+![remote-sqlcc-from-python](../../advanced-analytics/python/media/remote-sqlcc-from-python2.png)
 
-1. For function that are supported in RevoScalePy functions, the Python runtime calls a linking function, which in turn calls BxlServer.
-2. BxlServer is included with machine Learning Services (In-Database) and runs in a separate process from the Python runtime.
+1. For functions that are supported in **revoscalepy**, the Python runtime calls a linking function, which in turn calls BxlServer.
+2. BxlServer is included with Machine Learning Services (In-Database) and runs in a separate process from the Python runtime.
 3. BxlServer determines the connection target and initiates a connection using ODBC, passing credentials supplied as part of the connection string in the Python script.
 4. BxlServer opens a connection to the [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] instance.
-5. When an external script runtime is called, the Launchpad service is invoked, which is turn starts the appropriate launcher: in this case, PythonLauncher.dll. Thereafter, processing of Python code is handled in a workflow similar to that when Python code is invoked from a stored procedure in T-SQL.
+5. When an external script runtime is called, the Launchpad service is invoked, which in turn starts the appropriate launcher: in this case, PythonLauncher.dll. Thereafter, processing of Python code is handled in a workflow similar to that when Python code is invoked from a stored procedure in T-SQL.
 6. PythonLauncher makes a call to the instance of the Python that is installed on the [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] computer.
 7. Results are returned to BxlServer.
 8. SQL Satellite manages communication with [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] and cleanup of related job objects.
 9. [!INCLUDE[ssNoVersion_md](../../includes/ssnoversion-md.md)] passes results back to the client.
 
+## Next steps
 
+[Architecture overview for Python in SQL Server](architecture-overview-sql-server-python.md)

docs/advanced-analytics/python/new-components-in-sql-server-to-support-python-integration.md

@@ -1,7 +1,7 @@
 ---
 title: "Architecture Overview (SQL Server R Services) | Microsoft Docs"
 ms.custom: ""
-ms.date: "04/18/2017"
+ms.date: "07/11/2017"
 ms.prod: "sql-server-2016"
 ms.reviewer: ""
 ms.suite: ""
@@ -15,27 +15,27 @@ author: "jeannt"
 ms.author: "jeannt"
 manager: "jhubbard"
 ---
-# Architecture Overview (SQL Server R Services)
+# Architecture overview for R in SQL Server
 
-This section provides an overview of the architecture of SQL Server 2016 R Services, and SQL Server 2017 Machine Learning Services.
+This section provides an overview of the architecture of SQL Server 2016 R Services, and of SQL Server 2017 Machine Learning Services.
 
 The architecture for the extensibility architecture is the same or very similar for the SQL Server 2016 and SQL Server 2017 releases, and similar also for R and Python. However, to simplify the discussion, this topic discusses only the R components, including new components added in the SQL Server database engine to support external script execution, security, R libraries, and interoperability with open source R.
 
 Additional details are provided in the links for each section.
 
-## R Interoperability
+## R interoperability
 
-Both SQL Server 2016 R Services and SQL Server Machine Learning Services (In-Database) install an open source distribution of R, as well as packages provided by Microsoft that support distributed and/or parallel processing.
+Both SQL Server 2016 R Services and SQL Server 2017 Machine Learning Services (In-Database) install an open source distribution of R, as well as packages provided by Microsoft that support distributed and/or parallel processing.
 
-The architecture is designed such that external scripts using R or Python run in a separate process from SQL Server. Current users of R should be able to port their R code and execute it in T-SQL with relatively minor modifications.
+The architecture is designed such that external scripts using R run in a separate process from SQL Server. Current users of R should be able to port their R code and execute it in T-SQL with relatively minor modifications.
 
-To scale your solution or use parallel processing, we recommend that you use the RevoScaleR package. If you do not use the distributed computing capabilities provided by these libraries, you can still get some performance improvements by running your R code in the context of SQL Server.
+To scale your solution or use parallel processing, we recommend that you use the [RevoScaleR](https://docs.microsoft.com/r-server/r-reference/revoscaler/revoscaler) package or the [MicrosoftML](https://docs.microsoft.com/r-server/r-reference/microsoftml/microsoftml-package) package. If you do not use the distributed computing capabilities provided by these libraries, you can still get some performance improvements by running your R code in the context of SQL Server.
 
 For more information about the external scripting components that are installed, or the interaction of SQL Server with R, see [R Interoperability](../../advanced-analytics/r/r-interoperability-in-sql-server.md)
 
-## New Components to Support R Integration
+## Components to support R integration
 
-The extensibility framework introduced in SQL Server 2016 is continued in SQL Server 2017. The extensibility components are used by SQL Server to start the external runtime for R, pass data between R and the database engine, and coordinate parallel tasks needed for an R job.
+The extensibility framework introduced in SQL Server 2016 is continued in SQL Server 2017. The extensibility components are used by SQL Server to start the external runtime for R, to pass data between R and the database engine, and to coordinate parallel tasks needed for an R job.
 
 The role of these additional components is to improve data exchange speed and compression, while providing a secure, high-performance platform for running external scripts.
 
@@ -47,12 +47,12 @@ When you run R code using Machine Learning Services or SQL Server R Services, al
 
 SQL Server intercepts all job requests, secures the task and its data using Windows job objects, and maintains security over data using SQL Server user accounts and database roles.
 
-Data is kept within the compliance boundary by enforcing SQL Server security at the table, database, and instance level. The database administrator can control who has the ability to run R jobs, and who has the ability to install or share R packages. The administrator can also monitor the use of R scripts by either rremote or  local users, and monitor and manage the resources consumed.
+Data is kept within the compliance boundary by enforcing SQL Server security at the table, database, and instance level. The database administrator can control who has the ability to run R jobs, and who has the ability to install or share R packages. The administrator can also monitor the use of R scripts by either remote or  local users, and monitor and manage the resources consumed.
 
-For details, see [Security for R](../../advanced-analytics/r/security-overview-sql-server-r.md)
+## Next steps
 
+[Components that support R integration](new-components-in-sql-server-to-support-r.md)
 
-## See Also
-
-[Machine Learning Tutorials](../../advanced-analytics/tutorials/machine-learning-services-tutorials.md)
+[R interoperability](r-interoperability-in-sql-server.md)
 
+[Security overview](security-overview-sql-server-r.md)