clean up branding

Author: v-thepet

articles/hdinsight/spark/apache-spark-create-cluster-cli.md

@@ -136,7 +136,7 @@ az group delete \
 
 ## Next steps
 
-In this quickstart, you learned how to create an Apache Spark cluster in Azure HDInsight using Azure CLI.  Advance to the next tutorial to learn how to use an HDInsight Spark cluster to run interactive queries on sample data.
+In this quickstart, you learned how to create an Apache Spark cluster in Azure HDInsight using Azure CLI.  Advance to the next tutorial to learn how to use an HDInsight cluster to run interactive queries on sample data.
 
 > [!div class="nextstepaction"]
 > [Run interactive queries on Apache Spark](./apache-spark-load-data-run-query.md)

articles/hdinsight/spark/apache-spark-jupyter-spark-sql-use-portal.md

@@ -1,29 +1,29 @@
 ---
 title: 'Quickstart: Create Spark cluster in HDInsight using Azure portal'
-description: This quickstart shows how to use the Azure portal to create an Apache Spark cluster in Azure HDInsight, and run a Spark SQL.
+description: This quickstart shows how to use the Azure portal to create an Apache Spark cluster in Azure HDInsight, and run a Spark SQL query.
 author: hrasheed-msft
 ms.author: hrasheed
 ms.reviewer: jasonh
 ms.service: hdinsight
 ms.topic: quickstart
 ms.date: 09/27/2019
 ms.custom: mvc
-#Customer intent: As a developer new to Apache Spark on Azure, I need to see how to create a spark cluster and query some data.
+#Customer intent: As a developer new to Apache Spark on Azure, I need to see how to create a Spark cluster and query some data.
 ---
 
 # Quickstart: Create Apache Spark cluster in Azure HDInsight using Azure portal
 
-In this quickstart, you create an HDInsight Spark cluster in the Azure portal. You then create a Jupyter notebook, and use it to run Spark SQL queries against Apache Hive tables. Azure HDInsight is a managed, full-spectrum, open-source analytics service for enterprises. The Apache Spark framework for HDInsight enables fast data analytics and cluster computing using in-memory processing. Jupyter notebook lets you interact with your data, combine code with markdown text, and do simple visualizations.
+In this quickstart, you use the Azure portal to create an Apache Spark cluster in Azure HDInsight. You then create a Jupyter notebook, and use it to run Spark SQL queries against Apache Hive tables. Azure HDInsight is a managed, full-spectrum, open-source analytics service for enterprises. The Apache Spark framework for HDInsight enables fast data analytics and cluster computing using in-memory processing. Jupyter notebook lets you interact with your data, combine code with markdown text, and do simple visualizations.
 
 [Overview: Apache Spark on Azure HDInsight](apache-spark-overview.md) | [Apache Spark](https://spark.apache.org/) | [Apache Hive](https://hive.apache.org/) | [Jupyter Notebook](https://jupyter.org/)
 
 ## Prerequisites
 
 - An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/free/?ref=microsoft.com&utm_source=microsoft.com&utm_medium=docs&utm_campaign=visualstudio).
 
-## Create an HDInsight Spark cluster
+## Create an Apache Spark cluster in HDInsight
 
-You use the Azure portal to create an HDInsight Spark cluster that uses Azure Storage Blobs as the cluster storage. For more information on using Data Lake Storage Gen2, see [Quickstart: Set up clusters in HDInsight](../../storage/data-lake-storage/quickstart-create-connect-hdi-cluster.md).
+You use the Azure portal to create an HDInsight cluster that uses Azure Storage Blobs as the cluster storage. For more information on using Data Lake Storage Gen2, see [Quickstart: Set up clusters in HDInsight](../../storage/data-lake-storage/quickstart-create-connect-hdi-cluster.md).
 
 > [!IMPORTANT]  
 > Billing for HDInsight clusters is prorated per minute, whether you are using them or not. Be sure to delete your cluster after you have finished using it. For more information, see the [Clean up resources](#clean-up-resources) section of this article.
@@ -42,15 +42,15 @@ You use the Azure portal to create an HDInsight Spark cluster that uses Azure St
     |---------|---------|
     |Subscription  | From the drop-down, select an Azure subscription used for this cluster. The subscription used for this quickstart is **Azure**. |
     |Resource group | Specify whether you want to create a new resource group or use an existing one. A resource group is a container that holds related resources for an Azure solution. The resource group name used for this quickstart is **myResourceGroup**. |
-    |Cluster name | Give a name to your HDInsight Spark cluster. The cluster name used for this quickstart is **myspark2019**.|
+    |Cluster name | Give a name to your HDInsight cluster. The cluster name used for this quickstart is **myspark2019**.|
     |Location   | Select a location for the resource group. The template uses this location for creating the cluster as well as for the default cluster storage. The location used for this quickstart is **East US**. |
     |Cluster type| Select **Spark** as the cluster type.|
     |Cluster version|This field will auto-populate with the default version once the cluster type has been selected.|
     |Cluster login username| Enter the cluster login username.  The default name is *admin*. You use this account to login in to the Jupyter notebook later in the quickstart. |
     |Cluster login password| Enter the cluster login password. |
     |Secure Shell (SSH) username| Enter the SSH username. The SSH username used for this quickstart is **sshuser**. By default, this account shares the same password as the *Cluster Login username* account. |
 
-    ![Create HDInsight Spark cluster basic configurations](./media/apache-spark-jupyter-spark-sql-use-portal/azure-portal-cluster-basics-spark.png "Create Spark cluster in HDInsight the Basic configurations")
+    ![Create HDInsight cluster basic configurations](./media/apache-spark-jupyter-spark-sql-use-portal/azure-portal-cluster-basics-spark.png "Create Spark cluster in HDInsight the Basic configurations")
 
     Select **Next: Storage >>** to continue to the **Storage** page.
 
@@ -63,13 +63,13 @@ You use the Azure portal to create an HDInsight Spark cluster that uses Azure St
     |Primary storage account|Use the auto-populated value.|
     |Container|Use the auto-populated value.|
 
-    ![Create HDInsight Spark cluster basic configurations](./media/apache-spark-jupyter-spark-sql-use-portal/azure-portal-cluster-storage.png "Create Spark cluster in HDInsight the Basic configurations")
+    ![Create HDInsight cluster basic configurations](./media/apache-spark-jupyter-spark-sql-use-portal/azure-portal-cluster-storage.png "Create Spark cluster in HDInsight the Basic configurations")
 
     Select **Review + create** to continue.
 
 1. Under **Review + create**, select **Create**. It takes about 20 minutes to create the cluster. The cluster must be created before you can proceed to the next session.
 
-If you run into an issue with creating HDInsight clusters, it could be that you do not have the right permissions to do so. For more information, see [Access control requirements](../hdinsight-hadoop-create-linux-clusters-portal.md).
+If you run into an issue with creating HDInsight clusters, it could be that you don't have the right permissions to do so. For more information, see [Access control requirements](../hdinsight-hadoop-create-linux-clusters-portal.md).
 
 ## Create a Jupyter notebook
 
@@ -91,13 +91,13 @@ Jupyter Notebook is an interactive notebook environment that supports various pr
 
    A new notebook is created and opened with the name Untitled(Untitled.pynb).
 
-## Run Spark SQL statements
+## Run Apache Spark SQL statements
 
 SQL (Structured Query Language) is the most common and widely used language for querying and defining data. Spark SQL functions as an extension to Apache Spark for processing structured data, using the familiar SQL syntax.
 
 1. Verify the kernel is ready. The kernel is ready when you see a hollow circle next to the kernel name in the notebook. Solid circle denotes that the kernel is busy.
 
-    ![Apache Hive query in HDInsight Spark1](./media/apache-spark-jupyter-spark-sql/jupyter-spark-kernel-status.png "Hive query in HDInsight Spark1")
+    ![Apache Hive query in HDInsight](./media/apache-spark-jupyter-spark-sql/jupyter-spark-kernel-status.png "Hive query in HDInsight")
 
     When you start the notebook for the first time, the kernel performs some tasks in the background. Wait for the kernel to be ready.
 
@@ -108,9 +108,9 @@ SQL (Structured Query Language) is the most common and widely used language for
     SHOW TABLES
     ```
 
-    When you use a Jupyter Notebook with your HDInsight Spark cluster, you get a preset `sqlContext` that you can use to run Hive queries using Spark SQL. `%%sql` tells Jupyter Notebook to use the preset `sqlContext` to run the Hive query. The query retrieves the top 10 rows from a Hive table (**hivesampletable**) that comes with all HDInsight clusters by default. It takes about 30 seconds to get the results. The output looks like:
+    When you use a Jupyter Notebook with your HDInsight cluster, you get a preset `sqlContext` that you can use to run Hive queries using Spark SQL. `%%sql` tells Jupyter Notebook to use the preset `sqlContext` to run the Hive query. The query retrieves the top 10 rows from a Hive table (**hivesampletable**) that comes with all HDInsight clusters by default. It takes about 30 seconds to get the results. The output looks like:
 
-    ![Apache Hive query in HDInsight Spark2](./media/apache-spark-jupyter-spark-sql/hdinsight-spark-get-started-hive-query.png "Hive query in HDInsight Spark2")
+    ![Apache Hive query in HDInsight](./media/apache-spark-jupyter-spark-sql/hdinsight-spark-get-started-hive-query.png "Hive query in HDInsight")
 
     Every time you run a query in Jupyter, your web browser window title shows a **(Busy)** status along with the notebook title. You also see a solid circle next to the **PySpark** text in the top-right corner.
 
@@ -123,7 +123,7 @@ SQL (Structured Query Language) is the most common and widely used language for
 
     The screen shall refresh to show the query output.
 
-    ![Hive query output in HDInsight Spark](./media/apache-spark-jupyter-spark-sql/hdinsight-spark-get-started-hive-query-output.png "Hive query output in HDInsight Spark")
+    ![Hive query output in HDInsight](./media/apache-spark-jupyter-spark-sql/hdinsight-spark-get-started-hive-query-output.png "Hive query output in HDInsight")
 
 1. From the **File** menu on the notebook, select **Close and Halt**. Shutting down the notebook releases the cluster resources.
 
@@ -135,11 +135,11 @@ Switch back to the Azure portal, and select **Delete**.
 
 ![Azure portal delete an HDInsight cluster](./media/apache-spark-jupyter-spark-sql/hdinsight-azure-portal-delete-cluster.png "Delete HDInsight cluster")
 
-You can also select the resource group name to open the resource group page, and then select **Delete resource group**. By deleting the resource group, you delete both the HDInsight Spark cluster, and the default storage account.
+You can also select the resource group name to open the resource group page, and then select **Delete resource group**. By deleting the resource group, you delete both the HDInsight cluster, and the default storage account.
 
 ## Next steps
 
-In this quickstart, you learned how to create an HDInsight Spark cluster and run a basic Spark SQL query. Advance to the next tutorial to learn how to use an HDInsight Spark cluster to run interactive queries on sample data.
+In this quickstart, you learned how to create an Apache Spark cluster in HDInsight and run a basic Spark SQL query. Advance to the next tutorial to learn how to use an HDInsight cluster to run interactive queries on sample data.
 
 > [!div class="nextstepaction"]
 > [Run interactive queries on Apache Spark](./apache-spark-load-data-run-query.md)