Fix images

Author: JasonWHowell

articles/hdinsight/hadoop/apache-hadoop-linux-tutorial-get-started.md

@@ -60,7 +60,7 @@ Two Azure resources are defined in the template:
     > [!NOTE]  
     > The values you provide must be unique and should follow the naming guidelines. The template does not perform validation checks. If the values you provide are already in use, or do not follow the guidelines, you get an error after you have submitted the template.  
 
-    ![HDInsight Linux gets started Resource Manager template on portal](./media/apache-hadoop-linux-tutorial-get-started/hdinsight-linux-get-started-arm-template-on-portal.png "Deploy Hadoop cluster in HDInsight using the Azure portal and a resource group manager template")
+    :::image type="content" source="./media/apache-hadoop-linux-tutorial-get-started/hdinsight-linux-get-started-arm-template-on-portal.png " alt-text="HDInsight Linux gets started Resource Manager template on portal" border="true":::
 
 1. Review the **TERMS AND CONDITIONS**. Then select **I agree to the terms and conditions stated above**, then **Purchase**. You'll receive a notification that your deployment is in progress. It takes about 20 minutes to create a cluster.
 
@@ -80,7 +80,7 @@ After you complete the quickstart, you may want to delete the cluster. With HDIn
 
 From the Azure portal, navigate to your cluster, and select **Delete**.
 
-![HDInsight delete cluster from portal](./media/apache-hadoop-linux-tutorial-get-started/hdinsight-delete-cluster.png "HDInsight delete cluster from portal")
+:::image type="content" source="./media/apache-hadoop-linux-tutorial-get-started/hdinsight-delete-cluster.png " alt-text="HDInsight delete cluster from portal" border="true":::
 
 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.
 

articles/hdinsight/interactive-query/apache-hive-query-odbc-driver-powershell.md

@@ -39,7 +39,7 @@ The following steps show you how to create an Apache Hive ODBC data source.
 
 1. From Windows, navigate to **Start** > **Windows Administrative Tools** > **ODBC Data Sources (32-bit)/(64-bit)**.  An **ODBC Data Source Administrator** window opens.
 
-    ![OBDC data source administrator](./media/apache-hive-query-odbc-driver-powershell/hive-odbc-driver-dsn-setup.png "Configure a DSN using ODBC Data Source Administrator")
+    :::image type="content" source="./media/apache-hive-query-odbc-driver-powershell/hive-odbc-driver-dsn-setup.png " alt-text="OBDC data source administrator" border="true":::
 
 1. From the **User DSN** tab, select **Add** to open the **Create New Data Source** window.
 
@@ -65,7 +65,7 @@ The following steps show you how to create an Apache Hive ODBC data source.
    |  Rows fetched per block |When fetching a large number of records, tuning this parameter may be required to ensure optimal performances. |
    |  Default string column length, Binary column length, Decimal column scale |The data type lengths and precisions may affect how data is returned. They cause incorrect information to be returned because of loss of precision and truncation. |
 
-    ![Advanced DSN configuration options](./media/apache-hive-query-odbc-driver-powershell/odbc-data-source-advanced-options.png "Advanced DSN configuration options")
+    :::image type="content" source="./media/apache-hive-query-odbc-driver-powershell/odbc-data-source-advanced-options.png " alt-text="Advanced DSN configuration options" border="true":::
 
 1. Select **Test** to test the data source. When the data source is configured correctly, the test result shows **SUCCESS**.  
 

articles/hdinsight/interactive-query/gateway-best-practices.md

@@ -16,7 +16,7 @@ The HDInsight gateway is the only part of an HDInsight cluster that is publicly
 
 The following diagram provides a rough illustration of how the Gateway provides an abstraction in front of all the different host resolution possibilities within HDInsight.
 
-![Host Resolution Diagram](./media/gateway-best-practices/host-resolution-diagram.png "Host Resolution Diagram")
+:::image type="content" source="./media/gateway-best-practices/host-resolution-diagram.png " alt-text="Host Resolution Diagram" border="true":::
 
 ## Motivation
 
@@ -34,7 +34,7 @@ The Gateway's performance degradation around queries of a large size is because
 
 The following diagram illustrates the steps involved in a SELECT query.
 
-![Result Diagram](./media/gateway-best-practices/result-retrieval-diagram.png "Result Diagram")
+:::image type="content" source="./media/gateway-best-practices/result-retrieval-diagram.png " alt-text="Result Diagram" border="true":::
 
 Apache Hive is a relational abstraction on top of an HDFS-compatible filesystem. This abstraction means **SELECT** statements in Hive correspond to **READ** operations on the filesystem. The **READ** operations are translated into the appropriate schema before reported to the user. The latency of this process increases with data size and total hops required to reach the end user.
 

articles/hdinsight/interactive-query/hdinsight-grafana.md

@@ -26,7 +26,7 @@ See [Create Apache Hadoop clusters using the Azure portal](../hdinsight-hadoop-c
 
 1. The Grafana dashboard appears and looks like this example:
 
-    ![HDInsight Grafana web dashboard](./media/hdinsight-grafana/hdinsight-grafana-dashboard.png "HDInsight Grafana dashboard")
+    :::image type="content" source="./media/hdinsight-grafana/hdinsight-grafana-dashboard.png " alt-text="HDInsight Grafana web dashboard" border="true":::
 
 ## Clean up resources
 

articles/hdinsight/interactive-query/hdinsight-security-options-for-hive.md

@@ -11,7 +11,7 @@ ms.date: 10/02/2020
 
 This document describes the recommended security options for Hive in HDInsight. These options can be configured through Ambari.
 
-![`Security Options for Hive`](./media/hdinsight-security-options-for-hive/security-options-hive.png "Security Options for Hive")
+:::image type="content" source="./media/hdinsight-security-options-for-hive/security-options-hive.png " alt-text="`Security Options for Hive`" border="true":::
 
 ## HiveServer2 authentication
 

articles/hdinsight/interactive-query/hive-llap-sizing-guide.md

@@ -43,7 +43,7 @@ specific tuning.
 
 ### **LLAP Architecture/Components:**  
 
-![`LLAP Architecture/Components`](./media/hive-llap-sizing-guide/LLAP_architecture_sizing_guide.png "LLAP Architecture/Components")
+:::image type="content" source="./media/hive-llap-sizing-guide/LLAP_architecture_sizing_guide.png " alt-text="`LLAP Architecture/Components`" border="true":::
 
 ### **LLAP Daemon size estimations:** 
 
@@ -77,7 +77,7 @@ Default HDInsight cluster has four LLAP daemons running on four worker nodes, so
 
 **Ambari UI slider for Hive config variable `hive.server2.tez.sessions.per.default.queue`:**
 
-![`LLAP maximum concurrent queries`](./media/hive-llap-sizing-guide/LLAP_sizing_guide_max_concurrent_queries.png "LLAP maximum number of concurrent queries")
+:::image type="content" source="./media/hive-llap-sizing-guide/LLAP_sizing_guide_max_concurrent_queries.png " alt-text="`LLAP maximum concurrent queries`" border="true":::
 
 #### **5. Tez Container and Tez Application Master size**    
 Configuration: ***tez.am.resource.memory.mb, hive.tez.container.size***  
@@ -163,7 +163,7 @@ For D14 v2, this value is 19 x 3 GB = **57 GB**
 
 `Ambari environment variable for LLAP heap size:`
 
-![`LLAP heap size`](./media/hive-llap-sizing-guide/LLAP_sizing_guide_llap_heap_size.png "LLAP heap size")
+:::image type="content" source="./media/hive-llap-sizing-guide/LLAP_sizing_guide_llap_heap_size.png " alt-text="`LLAP heap size`" border="true":::
 
 When SSD cache is disabled, the in-memory cache is amount of memory that is left after taking out Headroom size and Heap size from the LLAP daemon container size.
 
@@ -196,11 +196,11 @@ Ambari environment variables: ***num_llap_nodes, num_llap_nodes_for_llap_daemons
 
 **num_llap_nodes** - specifies number of nodes used by Hive LLAP service, this includes nodes running LLAP daemon, LLAP Service Master, and Tez Application Master(Tez AM).  
 
-![`Number of Nodes for LLAP service`](./media/hive-llap-sizing-guide/LLAP_sizing_guide_num_llap_nodes.png "Number of Nodes for LLAP service")  
+:::image type="content" source="./media/hive-llap-sizing-guide/LLAP_sizing_guide_num_llap_nodes.png " alt-text="`Number of Nodes for LLAP service`" border="true":::  
 
 **num_llap_nodes_for_llap_daemons** - specified number of nodes used only for LLAP daemons. LLAP daemon container sizes are set to max fit node, so it will result in one llap daemon on each node.
 
-![`Number of Nodes for LLAP daemons`](./media/hive-llap-sizing-guide/LLAP_sizing_guide_num_llap_nodes_for_llap_daemons.png "Number of Nodes for LLAP daemons")
+:::image type="content" source="./media/hive-llap-sizing-guide/LLAP_sizing_guide_num_llap_nodes_for_llap_daemons.png " alt-text="`Number of Nodes for LLAP daemons`" border="true":::
 
 It's recommended to keep both values same as number of worker nodes in Interactive Query cluster.
 

articles/hdinsight/kafka/apache-kafka-get-started.md

@@ -67,7 +67,7 @@ To create an Apache Kafka cluster on HDInsight, use the following steps:
     |Primary storage account|Use the drop-down list to select an existing storage account, or select **Create new**. If you create a new account, the name must be between 3 and 24 characters in length, and can include numbers and lowercase letters only|
     |Container|Use the auto-populated value.|
 
-    ![HDInsight Linux get started provide cluster storage values](./media/apache-kafka-get-started/azure-portal-cluster-storage.png "Provide storage values for creating an HDInsight cluster")
+    :::image type="content" source="./media/apache-kafka-get-started/azure-portal-cluster-storage.png " alt-text="HDInsight Linux get started provide cluster storage values" border="true":::
 
     Select the **Security + networking** tab.
 

articles/hdinsight/spark/apache-azure-spark-history-server.md

@@ -20,7 +20,7 @@ The Spark History Server is the web UI for completed and running Spark applicati
 1. From the [Azure portal](https://portal.azure.com/), open the Spark cluster. For more information, see [List and show clusters](../hdinsight-administer-use-portal-linux.md#showClusters).
 2. From **Cluster dashboards**, select  **Spark history server**. When prompted, enter the admin credentials for the Spark cluster.
 
-    ![Launch the Spark History Server from the Azure portal.](./media/apache-azure-spark-history-server/azure-portal-dashboard-spark-history.png "Spark History Server")
+    :::image type="content" source="./media/apache-azure-spark-history-server/azure-portal-dashboard-spark-history.png " alt-text="Launch the Spark History Server from the Azure portal." border="true":::the Azure portal." border="true":::
 
 ### Open the Spark History Server web UI by URL
 

articles/hdinsight/spark/apache-spark-connect-to-sql-database.md

@@ -30,7 +30,7 @@ Start by creating a Jupyter Notebook associated with the Spark cluster. You use
 1. From the [Azure portal](https://portal.azure.com/), open your cluster.
 1. Select **Jupyter Notebook** underneath **Cluster dashboards** on the right side.  If you don't see **Cluster dashboards**, select **Overview** from the left menu. If prompted, enter the admin credentials for the cluster.
 
-    ![Jupyter Notebook on Apache Spark](./media/apache-spark-connect-to-sql-database/hdinsight-spark-cluster-dashboard-jupyter-notebook.png "Jupyter Notebook on Spark")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/hdinsight-spark-cluster-dashboard-jupyter-notebook.png " alt-text="Jupyter Notebook on Apache Spark" border="true":::
 
    > [!NOTE]  
    > You can also access the Jupyter Notebook on Spark cluster by opening the following URL in your browser. Replace **CLUSTERNAME** with the name of your cluster:
@@ -39,7 +39,7 @@ Start by creating a Jupyter Notebook associated with the Spark cluster. You use
 
 1. In the Jupyter Notebook, from the top-right corner, click **New**, and then click **Spark** to create a Scala notebook. Jupyter Notebooks on HDInsight Spark cluster also provide the **PySpark** kernel for Python2 applications, and the **PySpark3** kernel for Python3 applications. For this article, we create a Scala notebook.
 
-    ![Kernels for Jupyter Notebook on Spark](./media/apache-spark-connect-to-sql-database/kernel-jupyter-notebook-on-spark.png "Kernels for Jupyter Notebook on Spark")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/kernel-jupyter-notebook-on-spark.png " alt-text="Kernels for Jupyter Notebook on Spark" border="true":::
 
     For more information about the kernels, see [Use Jupyter Notebook kernels with Apache Spark clusters in HDInsight](apache-spark-jupyter-notebook-kernels.md).
 
@@ -48,7 +48,7 @@ Start by creating a Jupyter Notebook associated with the Spark cluster. You use
 
 1. A new notebook opens with a default name, **Untitled**. Click the notebook name and enter a name of your choice.
 
-    ![Provide a name for the notebook](./media/apache-spark-connect-to-sql-database/hdinsight-spark-jupyter-notebook-name.png "Provide a name for the notebook")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/hdinsight-spark-jupyter-notebook-name.png " alt-text="Provide a name for the notebook" border="true":::
 
 You can now start creating your application.
 
@@ -95,7 +95,7 @@ In this section, you read data from a table (for example, **SalesLT.Address**) t
 
     You see an output similar to the following image:
 
-    ![schema output](./media/apache-spark-connect-to-sql-database/read-from-sql-schema-output.png "schema output")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/read-from-sql-schema-output.png " alt-text="schema output" border="true":::
 
 1. You can also do operations like, retrieve the top 10 rows.
 
@@ -162,11 +162,11 @@ In this section, we use a sample CSV file available on the cluster to create a t
 
     a. Start SSMS and connect to the Azure SQL Database by providing connection details as shown in the screenshot below.
 
-    ![Connect to SQL Database using SSMS1](./media/apache-spark-connect-to-sql-database/connect-to-sql-db-ssms.png "Connect to SQL Database using SSMS1")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/connect-to-sql-db-ssms.png " alt-text="Connect to SQL Database using SSMS1" border="true":::
 
     b. From **Object Explorer**, expand the database and the table node to see the **dbo.hvactable** created.
 
-    ![Connect to SQL Database using SSMS2](./media/apache-spark-connect-to-sql-database/connect-to-sql-db-ssms-locate-table.png "Connect to SQL Database using SSMS2")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/connect-to-sql-db-ssms-locate-table.png " alt-text="Connect to SQL Database using SSMS2" border="true":::
 
 1. Run a query in SSMS to see the columns in the table.
 
@@ -204,7 +204,7 @@ In this section, we stream data into the `hvactable` that you created in the pre
 
 1. The output shows the schema of **HVAC.csv**. The `hvactable` has the same schema as well. The output lists the columns in the table.
 
-    ![`hdinsight Apache Spark schema table`](./media/apache-spark-connect-to-sql-database/hdinsight-schema-table.png "Schema of table")
+    :::image type="content" source="./media/apache-spark-connect-to-sql-database/hdinsight-schema-table.png " alt-text="`hdinsight Apache Spark schema table`" border="true":::
 
 1. Finally, use the following snippet to read data from the HVAC.csv and stream it into the `hvactable` in your database. Paste the snippet in a code cell, replace the placeholder values with the values for your database, and then press **SHIFT + ENTER** to run.
 

articles/hdinsight/spark/apache-spark-create-standalone-application.md

@@ -223,7 +223,7 @@ If you're not going to continue to use this application, delete the cluster that
 
 1. Select **Delete**. Select **Yes**.
 
-![`HDInsight azure portal delete cluster`](./media/apache-spark-create-standalone-application/hdinsight-azure-portal-delete-cluster.png "Delete HDInsight cluster")
+:::image type="content" source="./media/apache-spark-create-standalone-application/hdinsight-azure-portal-delete-cluster.png " alt-text="`HDInsight azure portal delete cluster`" border="true":::lete cluster`" border="true":::
 
 ## Next step
 

articles/hdinsight/spark/apache-spark-custom-library-website-log-analysis.md

@@ -25,11 +25,11 @@ Once your data is saved as an Apache Hive table, in the next section we'll conne
 
 1. Create a new notebook. Select **New**, and then **PySpark**.
 
-    ![Create a new Apache Jupyter Notebook](./media/apache-spark-custom-library-website-log-analysis/hdinsight-create-jupyter-notebook.png "Create a new Jupyter Notebook")
+    :::image type="content" source="./media/apache-spark-custom-library-website-log-analysis/hdinsight-create-jupyter-notebook.png " alt-text="Create a new Apache Jupyter Notebook" border="true":::Notebook" border="true":::
 
 1. A new notebook is created and opened with the name Untitled.pynb. Select the notebook name at the top, and enter a friendly name.
 
-    ![Provide a name for the notebook](./media/apache-spark-custom-library-website-log-analysis/hdinsight-name-jupyter-notebook.png "Provide a name for the notebook")
+    :::image type="content" source="./media/apache-spark-custom-library-website-log-analysis/hdinsight-name-jupyter-notebook.png " alt-text="Provide a name for the notebook" border="true":::tebook" border="true":::
 
 1. Because you created a notebook using the PySpark kernel, you don't need to create any contexts explicitly. The Spark and Hive contexts will be automatically created for you when you run the first code cell. You can start by importing the types that are required for this scenario. Paste the following snippet in an empty cell, and then press **Shift + Enter**.
 
@@ -168,7 +168,7 @@ Once your data is saved as an Apache Hive table, in the next section we'll conne
 
    You should see an output like the following image:
 
-   ![hdinsight jupyter sql query output](./media/apache-spark-custom-library-website-log-analysis/hdinsight-jupyter-sql-qyery-output.png "SQL query output")
+   :::image type="content" source="./media/apache-spark-custom-library-website-log-analysis/hdinsight-jupyter-sql-qyery-output.png " alt-text="hdinsight jupyter sql query output" border="true":::yter sql query output" border="true":::
 
    For more information about the `%%sql` magic, see [Parameters supported with the %%sql magic](apache-spark-jupyter-notebook-kernels.md#parameters-supported-with-the-sql-magic).
 
@@ -186,7 +186,7 @@ Once your data is saved as an Apache Hive table, in the next section we'll conne
 
    You should see an output like the following image:
 
-   ![apache spark web log analysis plot](./media/apache-spark-custom-library-website-log-analysis/hdinsight-apache-spark-web-log-analysis-plot.png "Matplotlib output")
+   :::image type="content" source="./media/apache-spark-custom-library-website-log-analysis/hdinsight-apache-spark-web-log-analysis-plot.png " alt-text="apache spark web log analysis plot" border="true":::eb log analysis plot" border="true":::
 
 1. After you have finished running the application, you should shut down the notebook to release the resources. To do so, from the **File** menu on the notebook, select **Close and Halt**. This action will shut down and close the notebook.
 

articles/hdinsight/spark/apache-spark-eclipse-tool-plugin.md

@@ -315,9 +315,9 @@ When using **Link A Cluster**, I would suggest you to provide credential of stor
 
 There are two modes to submit the jobs. If storage credential is provided, batch mode will be used to submit the job. Otherwise, interactive mode will be used. If the cluster is busy, you might get the error below.
 
-![eclipse get error when cluster busy](./media/apache-spark-eclipse-tool-plugin/eclipse-interactive-cluster-busy-upload.png "eclipse get error when cluster busy")
+:::image type="content" source="./media/apache-spark-eclipse-tool-plugin/eclipse-interactive-cluster-busy-upload.png " alt-text="eclipse get error when cluster busy" border="true":::
 
-![eclipse get error when cluster busy yarn](./media/apache-spark-eclipse-tool-plugin/eclipse-interactive-cluster-busy-submit.png "eclipse get error when cluster busy yarn")
+:::image type="content" source="./media/apache-spark-eclipse-tool-plugin/eclipse-interactive-cluster-busy-submit.png " alt-text="eclipse get error when cluster busy yarn" border="true":::
 
 ## See also