Merge pull request #13614 from MicrosoftDocs/master

1/27 PM Publish

Author: huypub

docs/advanced-analytics/toc.yml

@@ -61,9 +61,9 @@
     items:
     - name: Create R scripts
       href: ../advanced-analytics/tutorials/quickstart-r-create-script.md
-    - name: Handle data types and objects
+    - name: Data types and objects
       href: ../advanced-analytics/tutorials/quickstart-r-data-types-and-objects.md
-    - name: Write R functions
+    - name: R functions
       href: ../advanced-analytics/tutorials/quickstart-r-functions.md
     - name: Train and score a model
       href: ../advanced-analytics/tutorials/quickstart-r-train-score-model.md

docs/advanced-analytics/tutorials/quickstart-python-create-script.md

@@ -3,7 +3,7 @@ title: "Quickstart: Run Python scripts"
 description: Run a set of simple Python scripts using SQL Server Machine Learning Services. Learn how to use the stored procedure sp_execute_external_script to execute the script in a SQL Server instance.
 ms.prod: sql
 ms.technology: machine-learning
-ms.date: 01/21/2020
+ms.date: 01/27/2020
 ms.topic: quickstart
 author: garyericson
 ms.author: garye

docs/advanced-analytics/tutorials/quickstart-python-data-structures.md

@@ -3,7 +3,7 @@ title: "Quickstart: Python data structures"
 description: In this quickstart, learn how to work with data structures and data objects in Python and SQL Server Machine Learning Services.
 ms.prod: sql
 ms.technology: machine-learning
-ms.date: 01/22/2019  
+ms.date: 01/27/2020
 ms.topic: quickstart
 author: garyericson
 ms.author: garye

docs/advanced-analytics/tutorials/quickstart-python-functions.md

@@ -1,10 +1,9 @@
 ---
-title: "Quickstart: Write Python functions"
-description: In this quickstart, learn how to write a Python function for advanced statistical computation with SQL Server Machine Learning Services.
+title: "Quickstart: Python functions"
+description: In this quickstart, you'll learn how to use Python mathematical and utility functions with SQL Server Machine Learning Services.
 ms.prod: sql
 ms.technology: machine-learning
-
-ms.date: 10/04/2019  
+ms.date: 01/27/2020
 ms.topic: quickstart
 author: garyericson
 ms.author: garye
@@ -13,10 +12,10 @@ ms.custom: seo-lt-2019
 monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15||=sqlallproducts-allversions"
 ---
 
-# Quickstart: Write advanced Python functions with SQL Server Machine Learning Services
+# Quickstart: Python functions with SQL Server Machine Learning Services
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]
 
-This quickstart describes how to embed Python mathematical and utility functions in a SQL stored procedure with SQL Server Machine Learning Services. Advanced statistical functions that are complicated to implement in T-SQL can be done in Python with only a single line of code.
+In this quickstart, you'll learn how to use Python mathematical and utility functions with SQL Server Machine Learning Services. Statistical functions are often complicated to implement in T-SQL, but can be done in Python with only a few lines of code.
 
 ## Prerequisites
 

docs/advanced-analytics/tutorials/quickstart-python-train-score-model.md

@@ -1,10 +1,9 @@
 ---
 title: "Quickstart: Train a model in Python"
-description: Create a simple predictive model in Python using SQL Server Machine Learning Services, then predict a result using new data.
+description: In this quickstart, you'll create and train a predictive model using Python. You'll save the model to a table in your SQL Server instance, and then use the model to predict values from new data using SQL Server Machine Learning Services.
 ms.prod: sql
 ms.technology: machine-learning
-
-ms.date: 10/14/2019  
+ms.date: 01/27/2020  
 ms.topic: quickstart
 author: garyericson
 ms.author: garye
@@ -16,7 +15,7 @@ monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15||=sqlallproducts-allv
 # Quickstart: Create and score a predictive model in Python with SQL Server Machine Learning Services
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]
 
-In this quickstart, you'll create and train a predictive model using Python, save the model to a table in your SQL Server instance, then use the model to predict values from new data using [SQL Server Machine Learning Services](../what-is-sql-server-machine-learning.md).
+In this quickstart, you'll create and train a predictive model using Python. You'll save the model to a table in your SQL Server instance, and then use the model to predict values from new data using [SQL Server Machine Learning Services](../what-is-sql-server-machine-learning.md).
 
 You'll create and execute two stored procedures running in SQL. The first one uses the classic Iris flower data set and generates a Naïve Bayes model to predict an Iris species based on flower characteristics. The second procedure is for scoring - it calls the model generated in the first procedure to output a set of predictions based on new data. By placing Python code in a SQL stored procedure, operations are contained in SQL, are reusable, and can be called by other stored procedures and client applications.
 

docs/advanced-analytics/tutorials/quickstart-r-create-script.md

@@ -1,10 +1,9 @@
 ---
-title: "Quickstart: Create R scripts"
-description: Create and run simple R scripts in a SQL Server instance with SQL Server Machine Learning Services.
+title: "Quickstart: Run R scripts"
+description: Run a set of simple R scripts using SQL Server Machine Learning Services. Learn how to use the stored procedure sp_execute_external_script to execute the script in a SQL Server instance.
 ms.prod: sql
 ms.technology: machine-learning
-
-ms.date: 10/04/2019  
+ms.date: 01/27/2020  
 ms.topic: quickstart
 author: garyericson
 ms.author: garye
@@ -13,10 +12,10 @@ ms.custom: seo-lt-2019
 monikerRange: ">=sql-server-2016||>=sql-server-linux-ver15||=sqlallproducts-allversions"
 ---
 
-# Quickstart: Create and run simple R scripts with SQL Server Machine Learning Services
+# Quickstart: Run simple R scripts with SQL Server Machine Learning Services
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]
 
-In this quickstart, you'll create and run a set of simple R scripts using [SQL Server Machine Learning Services](../what-is-sql-server-machine-learning.md). You'll learn how to wrap a well-formed R script in the stored procedure [sp_execute_external_script](../../relational-databases/system-stored-procedures/sp-execute-external-script-transact-sql.md) and execute the script in a SQL Server instance.
+In this quickstart, you'll run a set of simple R scripts using [SQL Server Machine Learning Services](../what-is-sql-server-machine-learning.md). You'll learn how to use the stored procedure [sp_execute_external_script](../../relational-databases/system-stored-procedures/sp-execute-external-script-transact-sql.md) to execute the script in a SQL Server instance.
 
 ## Prerequisites
 

docs/advanced-analytics/tutorials/quickstart-r-data-types-and-objects.md

@@ -1,10 +1,9 @@
 ---
-title: "Quickstart: R data types"
-description: In this quickstart, learn how to work with data types and data objects in R and SQL Server with SQL Server Machine Learning Services.
+title: "Quickstart: R data structures, data types, and objects"
+description: In this quickstart, you'll learn how to use data structures, data types, and objects when using R in SQL Server Machine Learning Services. You'll learn about moving data between R and SQL Server, and the common issues that might occur.
 ms.prod: sql
 ms.technology: machine-learning
-
-ms.date: 10/04/2019  
+ms.date: 01/27/2019  
 ms.topic: quickstart
 author: garyericson
 ms.author: garye
@@ -13,10 +12,10 @@ ms.custom: seo-lt-2019
 monikerRange: ">=sql-server-2016||>=sql-server-linux-ver15||=sqlallproducts-allversions"
 ---
 
-# Quickstart: Handle data types and objects using R in SQL Server Machine Learning Services
+# Quickstart: Data structures, data types, and objects using R in SQL Server Machine Learning Services
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]
 
-In this quickstart, you'll learn about common issues that occur when moving data between R and SQL Server. The experience you gain through this exercise provides essential background when working with data in your own script.
+In this quickstart, you'll learn how to use data structures and data types when using R in SQL Server Machine Learning Services. You'll learn about moving data between R and SQL Server, and the common issues that might occur.
 
 Common issues to know up front include:
 

docs/advanced-analytics/tutorials/quickstart-r-functions.md

@@ -1,10 +1,9 @@
 ---
-title: "Quickstart: Write R functions"
-description: In this quickstart, learn how to write an R function for advanced statistical computation with SQL Server Machine Learning Services.
+title: "Quickstart: R functions"
+description: In this quickstart, you'll learn how to use R mathematical and utility functions with SQL Server Machine Learning Services. 
 ms.prod: sql
 ms.technology: machine-learning
-
-ms.date: 10/04/2019  
+ms.date: 01/27/2020  
 ms.topic: quickstart
 author: garyericson
 ms.author: garye
@@ -13,10 +12,10 @@ ms.custom: seo-lt-2019
 monikerRange: ">=sql-server-2016||>=sql-server-linux-ver15||=sqlallproducts-allversions"
 ---
 
-# Quickstart: Write advanced R functions with SQL Server Machine Learning Services
+# Quickstart: R functions with SQL Server Machine Learning Services
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]
 
-This quickstart describes how to embed R mathematical and utility functions in a SQL stored procedure with SQL Server Machine Learning Services. Advanced statistical functions that are complicated to implement in T-SQL can be done in R with only a single line of code.
+In this quickstart, you'll learn how to use R mathematical and utility functions with SQL Server Machine Learning Services. Statistical functions are often complicated to implement in T-SQL, but can be done in R with only a few lines of code.
 
 ## Prerequisites
 

docs/advanced-analytics/tutorials/quickstart-r-train-score-model.md

@@ -1,10 +1,9 @@
 ---
 title: "Quickstart: Train a model in R"
-description: Create a simple predictive model in R using SQL Server Machine Learning Services, then predict a result using new data.
+description: In this quickstart, you'll create and train a predictive model using T. You'll save the model to a table in your SQL Server instance, and then use the model to predict values from new data using SQL Server Machine Learning Services.
 ms.prod: sql
 ms.technology: machine-learning
-
-ms.date: 10/04/2019  
+ms.date: 01/27/2020  
 ms.topic: quickstart
 author: garyericson
 ms.author: garye
@@ -16,7 +15,7 @@ monikerRange: ">=sql-server-2016||>=sql-server-linux-ver15||=sqlallproducts-allv
 # Quickstart: Create and score a predictive model in R with SQL Server Machine Learning Services
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]
 
-In this quickstart, you'll create and train a predictive model using R, save the model to a table in your SQL Server instance, then use the model to predict values from new data using [SQL Server Machine Learning Services](../what-is-sql-server-machine-learning.md).
+In this quickstart, you'll create and train a predictive model using T. You'll save the model to a table in your SQL Server instance, and then use the model to predict values from new data using [SQL Server Machine Learning Services](../what-is-sql-server-machine-learning.md).
 
 You'll create and execute two stored procedures running in SQL. The first one uses the **mtcars** dataset included with R and generates a simple generalized linear model (GLM) that predicts the probability that a vehicle has been fitted with a manual transmission. The second procedure is for scoring - it calls the model generated in the first procedure to output a set of predictions based on new data. By placing R code in a SQL stored procedure, operations are contained in SQL, are reusable, and can be called by other stored procedures and client applications.
 

docs/database-engine/availability-groups/windows/prereqs-restrictions-recommendations-always-on-availability.md

@@ -151,10 +151,7 @@ ms.author: mathoma
     -   If a given thread is idle for a while, it is released back into the general [!INCLUDE[ssNoVersion](../../../includes/ssnoversion-md.md)] thread pool. Normally, an inactive thread is released after ~15 seconds of inactivity. However, depending on the last activity, an idle thread might be retained longer.  
 
     -   A SQL Server instance uses up to 100 threads for parallel redo for secondary replicas. Each database uses up to one-half of the total number of CPU cores, but not more than 16 threads per database. If the total number of required threads for a single instance exceeds 100, SQL Server uses a single redo thread for every remaining database. Serial Redo threads are released after ~15 seconds of inactivity. 
-    
-    > [!NOTE]
-    > Databases are chosen to go single-threaded based on their ascending database ID. As such, the database creation order should be considered for SQL Server instances that host more availability group databases than available worker threads. For example, on a system with 32 or more CPU cores, the first six databases (ordered by database ID) in an availability group or groups will use parallel redo mode, and all subsequent databases will use single redo mode.
-  
+     
 -   In addition, availability groups use unshared threads, as follows:  
   
     -   Each primary replica uses 1 Log Capture thread for each primary database. In addition, it uses 1 Log Send thread for each secondary database. Log send threads are released after ~15 seconds of inactivity.