Merge branch 'master' of https://github.com/MicrosoftDocs/azure-docs-pr into tamram-0415a

Author: tamram

articles/cosmos-db/create-sql-api-java-changefeed.md

@@ -84,6 +84,7 @@ mvn clean package
 
     Press enter. Now the following block of code will execute and initialize the Change Feed processor on another thread: 
 
+   # [Java SDK 4.0](#tab/v4sdk)
 
     **Java SDK 4.0**
     ```java
@@ -98,6 +99,8 @@ mvn clean package
     while (!isProcessorRunning.get()); //Wait for Change Feed processor start
     ```
 
+   # [Java SDK 3.7.0](#tab/v3sdk)
+
     **Java SDK 3.7.0**
     ```java
     changeFeedProcessorInstance = getChangeFeedProcessor("SampleHost_1", feedContainer, leaseContainer);
@@ -110,7 +113,8 @@ mvn clean package
 
     while (!isProcessorRunning.get()); //Wait for Change Feed processor start    
     ```
-
+   ---
+   
     ```"SampleHost_1"``` is the name of the Change Feed processor worker. ```changeFeedProcessorInstance.start()``` is what actually starts the Change Feed processor.
 
     Return to the Azure Portal Data Explorer in your browser. Under the **InventoryContainer-leases** container, click **items** to see its contents. You will see that Change Feed Processor has populated the lease container, i.e. the processor has assigned the ```SampleHost_1``` worker a lease on some partitions of the **InventoryContainer**.
@@ -119,6 +123,8 @@ mvn clean package
 
 1. Press enter again in the terminal. This will trigger 10 documents to be inserted into **InventoryContainer**. Each document insertion appears in the Change Feed as JSON; the following callback code handles these events by mirroring the JSON documents into a materialized view:
 
+   # [Java SDK 4.0](#tab/v4sdk)
+
     **Java SDK 4.0**
     ```java
     public static ChangeFeedProcessor getChangeFeedProcessor(String hostName, CosmosAsyncContainer feedContainer, CosmosAsyncContainer leaseContainer) {
@@ -145,6 +151,8 @@ mvn clean package
     }
     ```
 
+   # [Java SDK 3.7.0](#tab/v3sdk)
+
     **Java SDK 3.7.0**
     ```java
     public static ChangeFeedProcessor getChangeFeedProcessor(String hostName, CosmosContainer feedContainer, CosmosContainer leaseContainer) {
@@ -170,6 +178,7 @@ mvn clean package
         typeContainer.upsertItem(document).subscribe();
     }    
     ```
+   ---
 
 1. Allow the code to run 5-10sec. Then return to the Azure Portal Data Explorer and navigate to **InventoryContainer > items**. You should see that items are being inserted into the inventory container; note the partition key (```id```).
 
@@ -185,6 +194,8 @@ mvn clean package
 
     Hit enter again to call the function ```deleteDocument()``` in the example code. This function, shown below, upserts a new version of the document with ```/ttl == 5```, which sets document Time-To-Live (TTL) to 5sec. 
     
+   # [Java SDK 4.0](#tab/v4sdk)
+
     **Java SDK 4.0**
     ```java
     public static void deleteDocument() {
@@ -212,6 +223,7 @@ mvn clean package
         feedContainer.upsertItem(document,new CosmosItemRequestOptions()).block();
     }    
     ```
+   # [Java SDK 3.7.0](#tab/v3sdk)
 
     **Java SDK 3.7.0**
     ```java
@@ -240,6 +252,7 @@ mvn clean package
         feedContainer.upsertItem(document,new CosmosItemRequestOptions()).block();
     }    
     ```
+   ---
 
     The Change Feed ```feedPollDelay``` is set to 100ms; therefore, Change Feed responds to this update almost instantly and calls ```updateInventoryTypeMaterializedView()``` shown above. That last function call will upsert the new document with TTL of 5sec into **InventoryContainer-pktype**.
 

articles/cosmos-db/create-sql-api-java.md

@@ -76,6 +76,9 @@ git clone https://github.com/Azure-Samples/azure-cosmos-java-getting-started.git
 This step is optional. If you're interested in learning how the database resources are created in the code, you can review the following snippets. Otherwise, you can skip ahead to [Run the app
 ](#run-the-app). 
 
+
+# [Sync API](#tab/sync)
+
 ### Managing database resources using the synchronous (sync) API
 
 * `CosmosClient` initialization. The `CosmosClient` provides client-side logical representation for the Azure Cosmos database service. This client is used to configure and execute requests against the service.
@@ -102,6 +105,8 @@ This step is optional. If you're interested in learning how the database resourc
 
     [!code-java[](~/azure-cosmosdb-java-v4-getting-started/src/main/java/com/azure/cosmos/sample/sync/SyncMain.java?name=QueryItems)]
 
+# [Async API](#tab/async)
+
 ### Managing database resources using the asynchronous (async) API
 
 * Async API calls return immediately, without waiting for a response from the server. In light of this, the following code snippets show proper design patterns for accomplishing all of the preceding management tasks using async API.
@@ -130,6 +135,8 @@ This step is optional. If you're interested in learning how the database resourc
 
     [!code-java[](~/azure-cosmosdb-java-v4-getting-started/src/main/java/com/azure/cosmos/sample/async/AsyncMain.java?name=QueryItems)]
 
+---
+
 ## Run the app
 
 Now go back to the Azure portal to get your connection string information and launch the app with your endpoint information. This enables your app to communicate with your hosted database.

articles/machine-learning/how-to-move-data-in-out-of-pipelines.md

@@ -9,14 +9,15 @@ ms.topic: conceptual
 ms.author: laobri
 author: lobrien
 ms.date: 04/01/2020
+ms.custom: contperfq4
 # As a data scientist using Python, I want to get data into my pipeline and flowing between steps
 ---
 
 # Moving data into and between ML pipeline steps (Python)
 
 [!INCLUDE [applies-to-skus](../../includes/aml-applies-to-basic-enterprise-sku.md)]
 
-Data is central to machine learning pipelines. This article provides code for importing, transforming, and moving data between steps in an Azure Machine Learning pipeline. For an overview of how data works in Azure Machine Learning, see [Access data in Azure storage services](how-to-access-data.md). For the benefits and structure of Azure Machine Learning pipelines, see [What are Azure Machine Learning pipelines?](concept-ml-pipelines.md).
+This article provides code for importing, transforming, and moving data between steps in an Azure Machine Learning pipeline. For an overview of how data works in Azure Machine Learning, see [Access data in Azure storage services](how-to-access-data.md). For the benefits and structure of Azure Machine Learning pipelines, see [What are Azure Machine Learning pipelines?](concept-ml-pipelines.md).
 
 This article will show you how to:
 

articles/machine-learning/how-to-trigger-published-pipeline.md

@@ -10,6 +10,7 @@ ms.subservice: core
 ms.workload: data-services
 ms.topic: conceptual
 ms.date: 02/07/2020
+ms.custom: contperfq4
 
 ---
 # Trigger a run of a Machine Learning pipeline from a Logic App

articles/machine-learning/tutorial-pipeline-batch-scoring-classification.md

@@ -10,6 +10,7 @@ author: trevorbye
 ms.author: trbye
 ms.reviewer: laobri
 ms.date: 03/11/2020
+ms.custom: contperfq4 
 ---
 
 # Tutorial: Build an Azure Machine Learning pipeline for batch scoring

articles/machine-learning/tutorial-train-deploy-image-classification-model-vscode.md

@@ -9,6 +9,8 @@ ms.topic: tutorial
 author: luisquintanilla
 ms.author: luquinta
 ms.date: 04/13/2020
+ms.custom: contperfq4 
+
 #Customer intent: As a professional data scientist, I want to learn how to train and deploy an image classification model using TensorFlow and the Azure Machine Learning Visual Studio Code Extension.
 ---