Merge pull request #112692 from dagiro/freshness_c45

PRMerger6 · web-flow · commit b6cbe5d48d33 · 2020-04-24T13:04:22.000-07:00
freshness_c45
diff --git a/articles/hdinsight/hdinsight-hadoop-create-linux-clusters-adf.md b/articles/hdinsight/hdinsight-hadoop-create-linux-clusters-adf.md
@@ -6,15 +6,15 @@ ms.author: hrasheed
 ms.reviewer: jasonh
 ms.service: hdinsight
 ms.topic: tutorial
-ms.date: 03/18/2020
+ms.date: 04/24/2020
 #Customer intent: As a data worker, I need to create a Hadoop cluster and run Hive jobs on demand
 ---
 
 # Tutorial: Create on-demand Apache Hadoop clusters in HDInsight using Azure Data Factory
 
 [!INCLUDE [selector](../../includes/hdinsight-create-linux-cluster-selector.md)]
 
-In this tutorial, you learn how to create an [Apache Hadoop](./hadoop/apache-hadoop-introduction.md) cluster, on demand, in Azure HDInsight using Azure Data Factory. You then use data pipelines in Azure Data Factory to run Hive jobs and delete the cluster. By the end of this tutorial, you learn how to operationalize a big data job run where cluster creation, job run, and cluster deletion are performed on a schedule.
+In this tutorial, you learn how to create an [Apache Hadoop](./hadoop/apache-hadoop-introduction.md) cluster, on demand, in Azure HDInsight using Azure Data Factory. You then use data pipelines in Azure Data Factory to run Hive jobs and delete the cluster. By the end of this tutorial, you learn how to `operationalize` a big data job run where cluster creation, job run, and cluster deletion are done on a schedule.
 
 This tutorial covers the following tasks:
 
@@ -38,9 +38,9 @@ If you don't have an Azure subscription, [create a free account](https://azure.m
 
 ## Create preliminary Azure objects
 
-In this section, you create various objects that will be used for the HDInsight cluster you create on-demand. The created storage account will contain the sample [HiveQL](https://cwiki.apache.org/confluence/display/Hive/LanguageManual) script, `partitionweblogs.hql`, that you use to simulate a sample Apache Hive job that runs on the cluster.
+In this section, you create various objects that will be used for the HDInsight cluster you create on-demand. The created storage account will contain the sample HiveQL script, `partitionweblogs.hql`, that you use to simulate a sample Apache Hive job that runs on the cluster.
 
-This section uses an Azure PowerShell script to create the storage account and copy over the required files within the storage account. The Azure PowerShell sample script in this section performs the following tasks:
+This section uses an Azure PowerShell script to create the storage account and copy over the required files within the storage account. The Azure PowerShell sample script in this section does the following tasks:
 
 1. Signs in to Azure.
 2. Creates an Azure resource group.
@@ -154,7 +154,7 @@ Write-host "`nScript completed" -ForegroundColor Green
 1. Select the resource group name you created in your PowerShell script. Use the filter if you have too many resource groups listed.
 1. From the **Overview** view, you see one resource listed unless you share the resource group with other projects. That resource is the storage account with the name you specified earlier. Select the storage account name.
 1. Select the **Containers** tile.
-1. Select the **adfgetstarted** container. You see a folder called **hivescripts**.
+1. Select the **adfgetstarted** container. You see a folder called **`hivescripts`**.
 1. Open the folder and make sure it contains the sample script file, **partitionweblogs.hql**.
 
 ## Understand the Azure Data Factory activity
@@ -170,7 +170,7 @@ In this article, you configure the Hive activity to create an on-demand HDInsigh
 
 1. An HDInsight Hadoop cluster is automatically created for you just-in-time to process the slice.
 
-2. The input data is processed by running a HiveQL script on the cluster. In this tutorial, the HiveQL script associated with the hive activity performs the following actions:
+2. The input data is processed by running a HiveQL script on the cluster. In this tutorial, the HiveQL script associated with the hive activity does the following actions:
 
     * Uses the existing table (*hivesampletable*) to create another table **HiveSampleOut**.
     * Populates the **HiveSampleOut** table with only specific columns from the original *hivesampletable*.
@@ -181,7 +181,7 @@ In this article, you configure the Hive activity to create an on-demand HDInsigh
 
 1. Sign in to the [Azure portal](https://portal.azure.com/).
 
-2. From the left menu, navigate to **+ Create a resource** > **Analytics** > **Data Factory**.
+2. From the left menu, navigate to **`+ Create a resource`** > **Analytics** > **Data Factory**.
 
     ![Azure Data Factory on the portal](./media/hdinsight-hadoop-create-linux-clusters-adf/data-factory-azure-portal.png "Azure Data Factory on the portal")
 
@@ -260,7 +260,7 @@ In this section, you author two linked services within your data factory.
     | Time to live | Provide the duration for which you want the HDInsight cluster to be available before being automatically deleted.|
     | Service principal ID | Provide the application ID of the Azure Active Directory service principal you created as part of the prerequisites. |
     | Service principal key | Provide the authentication key for the Azure Active Directory service principal. |
-    | Cluster name prefix | Provide a value that will be prefixed to all the cluster types that are created by the data factory. |
+    | Cluster name prefix | Provide a value that will be prefixed to all the cluster types created by the data factory. |
     |Subscription |Select your subscription from the drop-down list.|
     | Select resource group | Select the resource group you created as part of the PowerShell script you used earlier.|
     | OS type/Cluster SSH user name | Enter an SSH user name, commonly `sshuser`. |
@@ -282,7 +282,7 @@ In this section, you author two linked services within your data factory.
 
     ![Add activities to Data Factory pipeline](./media/hdinsight-hadoop-create-linux-clusters-adf/hdinsight-data-factory-add-hive-pipeline.png "Add activities to Data Factory pipeline")
 
-1. Make sure you have the Hive activity selected, select the **HDI Cluster** tab, and from the **HDInsight Linked Service** drop-down list, select the linked service you created earlier, **HDInsightLinkedService**, for HDInsight.
+1. Make sure you have the Hive activity selected, select the **HDI Cluster** tab. And from the **HDInsight Linked Service** drop-down list, select the linked service you created earlier, **HDInsightLinkedService**, for HDInsight.
 
     ![Provide HDInsight cluster details for the pipeline](./media/hdinsight-hadoop-create-linux-clusters-adf/hdinsight-hive-activity-select-hdinsight-linked-service.png "Provide HDInsight cluster details for the pipeline")
 
@@ -294,9 +294,9 @@ In this section, you author two linked services within your data factory.
 
         ![Provide Hive script details for the pipeline](./media/hdinsight-hadoop-create-linux-clusters-adf/hdinsight-data-factory-provide-script-path.png "Provide Hive script details for the pipeline")
 
-    1. Under **Advanced** > **Parameters**, select **Auto-fill from script**. This option looks for any parameters in the Hive script that require values at runtime.
+    1. Under **Advanced** > **Parameters**, select **`Auto-fill from script`**. This option looks for any parameters in the Hive script that require values at runtime.
 
-    1. In the **value** text box, add the existing folder in the format `wasbs://adfgetstarted@<StorageAccount>.blob.core.windows.net/outputfolder/`. The path is case-sensitive. This is the path where the output of the script will be stored. The `wasbs` schema is necessary because storage accounts now have secure transfer required enabled by default.
+    1. In the **value** text box, add the existing folder in the format `wasbs://adfgetstarted@<StorageAccount>.blob.core.windows.net/outputfolder/`. The path is case-sensitive. This  path is where the output of the script will be stored. The `wasbs` schema is necessary because storage accounts now have secure transfer required enabled by default.
 
         ![Provide parameters for the Hive script](./media/hdinsight-hadoop-create-linux-clusters-adf/hdinsight-data-factory-provide-script-parameters.png "Provide parameters for the Hive script")
 
@@ -342,9 +342,9 @@ In this section, you author two linked services within your data factory.
 
 ## Clean up resources
 
-With the on-demand HDInsight cluster creation, you don't need to explicitly delete the HDInsight cluster. The cluster is deleted based on the configuration you provided while creating the pipeline. However, even after the cluster is deleted, the storage accounts associated with the cluster continue to exist. This behavior is by design so that you can keep your data intact. However, if you don't want to persist the data, you may delete the storage account you created.
+With the on-demand HDInsight cluster creation, you don't need to explicitly delete the HDInsight cluster. The cluster is deleted based on the configuration you provided while creating the pipeline. Even after the cluster is deleted, the storage accounts associated with the cluster continue to exist. This behavior is by design so that you can keep your data intact. However, if you don't want to persist the data, you may delete the storage account you created.
 
-Alternatively, you can delete the entire resource group that you created for this tutorial. This deletes the storage account and the Azure Data Factory that you created.
+Or, you can delete the entire resource group that you created for this tutorial. This process deletes the storage account and the Azure Data Factory that you created.
 
 ### Delete the resource group
 
@@ -354,13 +354,13 @@ Alternatively, you can delete the entire resource group that you created for thi
 1. On the **Resources** tile, you shall have the default storage account and the data factory listed unless you share the resource group with other projects.
 1. Select **Delete resource group**. Doing so deletes the storage account and the data stored in the storage account.
 
-    ![Azure portal delete resource group](./media/hdinsight-hadoop-create-linux-clusters-adf/delete-resource-group.png "Delete resource group")
+    ![`Azure portal delete resource group`](./media/hdinsight-hadoop-create-linux-clusters-adf/delete-resource-group.png "Delete resource group")
 
 1. Enter the resource group name to confirm deletion, and then select **Delete**.
 
 ## Next steps
 
-In this article, you learned how to use Azure Data Factory to create on-demand HDInsight cluster and run [Apache Hive](https://hive.apache.org/) jobs. Advance to the next article to learn how to create HDInsight clusters with custom configuration.
+In this article, you learned how to use Azure Data Factory to create on-demand HDInsight cluster and run Apache Hive jobs. Advance to the next article to learn how to create HDInsight clusters with custom configuration.
 
 > [!div class="nextstepaction"]
 > [Create Azure HDInsight clusters with custom configuration](hdinsight-hadoop-provision-linux-clusters.md)
