Merge pull request #291856 from MicrosoftDocs/repo_sync_working_branch

PhilKang0704 · web-flow · commit 6d4e63b5019e · 2024-12-12T13:00:55.000+08:00
Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)
diff --git a/articles/hdinsight-aks/control-egress-traffic-from-hdinsight-on-aks-clusters.md b/articles/hdinsight-aks/control-egress-traffic-from-hdinsight-on-aks-clusters.md
@@ -244,7 +244,7 @@ The Public FQDN can only be resolved to a CNAME with subdomain, therefore it mus
 The Private DNS zone should be able to resolve private FQDN to an IP `(privatelink.{clusterPoolName}.{subscriptionId})`. 
  
 > [!NOTE]
-> HDInsight on AKS creates private DNS zone in the cluster pool, virtual network. If your client applications are in same virtual network, you need not configure the private DNS zone again. In case you're using a client application in a different virtual network, you're required to use virutal network peering and bind to private dns zone in the cluster pool virtual network or use private endpoints in the virutal network, and private dns zones, to add the A-record to the private endpoint private IP. 
+> HDInsight on AKS creates private DNS zone in the cluster pool, virtual network. If your client applications are in same virtual network, you need not configure the private DNS zone again. In case you're using a client application in a different virtual network, you're required to use virtual network peering and bind to private dns zone in the cluster pool virtual network or use private endpoints in the virtual network, and private dns zones, to add the A-record to the private endpoint private IP. 
 
 Private FQDN： `{clusterName}.privatelink.{clusterPoolName}.{subscriptionId}.{region}.hdinsightaks.net`
 
diff --git a/articles/hdinsight-aks/create-cluster-error-dictionary.md b/articles/hdinsight-aks/create-cluster-error-dictionary.md
@@ -31,7 +31,7 @@ This article describes how to troubleshoot and resolve errors that could occur w
 |11|`Authorization_IdentityNotFound - {"code":null,"message":"The identity of the calling application could not be established."}`|The 1-p service principle  isn't on boarded to the tenant.|Execute the command to provision the 1-p service principle on the new tenant to onboard.|
 |12|`NotFound - ARM/AKS sdk error`|The user tries to update HDI on AKS cluster but the corresponding agent pool has been deleted.|The corresponding agent pool has been deleted. It's not recommended to operate AKS agent pool directly.|
 |13|`AuthorizationFailed - Scope invalid role assignment issue with managed RG and cluster msi`|Lack of permission to perform the operation.|Check if the service principle app ID mentioned in the error message owned by you. If yes,  grant the permission according to the error message. If no, open a support ticket to Azure HDInsight team.|
-|14|`DeleteAksClusterFailed - {"code":"DeleteAksClusterFailed","message":"An Azure service request has failed. ErrorCode: 'DeleteAksClusterFailed', ErrorMessage: 'Delete HDI cluster namespcae failed. Additional info: 'Can't access a disposed object.\\r\\nObject name: 'Microsoft.Azure.Common.Configuration.ManagedConfiguration was already disposed'.''."}`|RP switched to a new role instance unexpectedly.|retry the operation or open a support ticket to Azure HDInsight team.|
+|14|`DeleteAksClusterFailed - {"code":"DeleteAksClusterFailed","message":"An Azure service request has failed. ErrorCode: 'DeleteAksClusterFailed', ErrorMessage: 'Delete HDI cluster namespace failed. Additional info: 'Can't access a disposed object.\\r\\nObject name: 'Microsoft.Azure.Common.Configuration.ManagedConfiguration was already disposed'.''."}`|RP switched to a new role instance unexpectedly.|retry the operation or open a support ticket to Azure HDInsight team.|
 |15|`EntityStoreOperationError - ARM/AKS sdk error`|A database operation failed on AKS side during cluster update.|Retry the operation after some time. If the issue persists,  open a support ticket to Azure HDInsight team.|
 |16|`InternalServerError - {"exception":"System.Threading.Tasks.TaskCanceledException","message":"The operation was canceled."}`|This error caused due to various issues.|retry the operation or open a support ticket to Azure HDInsight team.|
 |17|`InternalServerError - {"exception":"System.IO.IOException","message":"Unable to read data from the transport connection: A connection attempt failed because the connected party didn't properly respond after a period of time, or established connection failed because connected host has failed to respond."}`|This error caused due to various issues.|retry the operation after some time. If the issue persists, open a support ticket to Azure HDInsight team.|
diff --git a/articles/hdinsight-aks/flink/azure-service-bus-demo.md b/articles/hdinsight-aks/flink/azure-service-bus-demo.md
@@ -45,7 +45,7 @@ After submitting the job, access the Flink Dashboard UI and click on the running
 
 Navigate to the Service Bus Explorer on the Azure portal and send messages to the corresponding Service Bus.
 
-:::image type="content" source="./media/azure-service-bus-demo/sending-message-azure-portal.png" alt-text="Screenshot shows sending message from Azure portal Serice Bus Explorer." lightbox="./media/azure-service-bus-demo/sending-message-azure-portal.png":::
+:::image type="content" source="./media/azure-service-bus-demo/sending-message-azure-portal.png" alt-text="Screenshot shows sending message from Azure portal Service Bus Explorer." lightbox="./media/azure-service-bus-demo/sending-message-azure-portal.png":::
 
 
 ### Check job run details on Apache Flink UI
@@ -318,7 +318,7 @@ This Flink source function, encapsulated within the `SessionBasedServiceBusSourc
 
 1. **Instance Variables**
 
-   The `connectionString`, `topicName`, and `subscriptionName` variables hold the connection string, topic name, and subscription name for your Azure Service Bus. The isRunning flag is used to control the execution of the source function. The `sessionReceiver` is an instance of `erviceBusSessionReceiverAsyncClient`, which is used to receive messages from the Service Bus.
+   The `connectionString`, `topicName`, and `subscriptionName` variables hold the connection string, topic name, and subscription name for your Azure Service Bus. The isRunning flag is used to control the execution of the source function. The `sessionReceiver` is an instance of `ServiceBusSessionReceiverAsyncClient`, which is used to receive messages from the Service Bus.
 
 1. **Constructor**
 
diff --git a/articles/hdinsight-aks/flink/change-data-capture-connectors-for-apache-flink.md b/articles/hdinsight-aks/flink/change-data-capture-connectors-for-apache-flink.md
@@ -111,7 +111,7 @@ VALUES ('hammer','16oz carpenter''s hammer',1.0);
 INSERT INTO products(name,description,weight)
 VALUES ('rocks','box of assorted rocks',5.3);
 INSERT INTO products(name,description,weight)
-VALUES ('jacket','water resistent black wind breaker',0.1);
+VALUES ('jacket','water resistant black wind breaker',0.1);
 INSERT INTO products(name,description,weight)
 VALUES ('spare tire','24 inch spare tire',22.2);
 
diff --git a/articles/hdinsight-aks/flink/flink-job-orchestration.md b/articles/hdinsight-aks/flink/flink-job-orchestration.md
@@ -139,7 +139,7 @@ The DAG expects to have setup for the Service Principal, as described during the
 
       "jarDirectory":"abfs://filesystem@<storageaccount>.dfs.core.windows.net", 
 
-      "subscritpion":"<cluster subscription id>", 
+      "subscription":"<cluster subscription id>", 
 
       "rg":"<cluster resource group>", 
 
@@ -173,7 +173,7 @@ The DAG expects to have setup for the Service Principal, as described during the
  {
   'jarName':'WordCount.jar',
   'jarDirectory':'abfs://filesystem@<storageaccount>.dfs.core.windows.net', 
-  'subscritpion':'<cluster subscription id>',
+  'subscription':'<cluster subscription id>',
   'rg':'<cluster resource group>', 
   'poolNm':'<cluster pool name>',
   'clusterNm':'<cluster name>'
diff --git a/articles/hdinsight-aks/flink/sink-sql-server-table-using-flink-sql.md b/articles/hdinsight-aks/flink/sink-sql-server-table-using-flink-sql.md
@@ -94,7 +94,7 @@ VALUES ('hammer','16oz carpenter''s hammer',1.0);
 INSERT INTO products(name,description,weight)
 VALUES ('rocks','box of assorted rocks',5.3);
 INSERT INTO products(name,description,weight)
-VALUES ('jacket','water resistent black wind breaker',0.1);
+VALUES ('jacket','water resistant black wind breaker',0.1);
 INSERT INTO products(name,description,weight)
 VALUES ('spare tire','24 inch spare tire',22.2);
 
diff --git a/articles/hdinsight-aks/spark/azure-hdinsight-spark-on-aks-delta-lake.md b/articles/hdinsight-aks/spark/azure-hdinsight-spark-on-aks-delta-lake.md
@@ -186,7 +186,7 @@ createDirectory(avgMoMKPIChangePath)
    1. Print Delta Table Schema for transformed and average KPI data1.
 
     ```
-    // tranform data schema
+    // transform data schema
     dtTransformed.toDF.printSchema
     // Average KPI Data Schema
     dtAvgKpi.toDF.printSchema
diff --git a/articles/hdinsight-aks/spark/create-spark-cluster.md b/articles/hdinsight-aks/spark/create-spark-cluster.md
@@ -63,7 +63,7 @@ You can use the Azure portal to create an Apache Spark cluster in cluster pool.
     |Number of worker nodes| 	Select the number of nodes for Spark cluster. Out of those, three nodes are reserved for coordinator and system services, remaining nodes are dedicated to Spark workers, one worker per node. For example, in a five-node cluster there are two workers|
     |Autoscale|	Click on the toggle button to enable Autoscale|
     |Autoscale Type	|Select from either load based or schedule based autoscale|
-    |Graceful decomission timeout	|Specify Graceful decommission timeout|
+    |Graceful decommission timeout	|Specify Graceful decommission timeout|
     |No of default worker node	|Select the number of nodes for autoscale|
     |Time Zone	|Select the time zone|
     |Autoscale Rules	|Select the day, start time, end time, no. of worker nodes|
diff --git a/articles/hdinsight-aks/spark/library-management.md b/articles/hdinsight-aks/spark/library-management.md
@@ -75,6 +75,6 @@ If you decide not to use the libraries anymore, then you can easily delete the l
    > [!NOTE]
    > * Packages installed from Jupyter notebook can only be deleted from Jupyter Notebook.
    > * Packages installed from library manager can only be uninstalled from library manager.
-   > * For upgrading a library/package, uninstall the current version of the library and resinstall the required version of the library.
-   > * Installation of libraries from Jupyter notebook is particular to the session. It is not persistant.
+   > * For upgrading a library/package, uninstall the current version of the library and reinstall the required version of the library.
+   > * Installation of libraries from Jupyter notebook is particular to the session. It is not persistent.
    > * Installing heavy packages may take some time due to their size and complexity.
diff --git a/articles/hdinsight-aks/trino/trino-airflow.md b/articles/hdinsight-aks/trino/trino-airflow.md
@@ -66,7 +66,7 @@ After restarting Airflow, find and run example_trino DAG. Results of the sample
 :::image type="content" source="./media/trino-airflow/print-result-log.png" alt-text="Screenshot showing how to check results for Airflow Trino DAG." lightbox="./media/trino-airflow/print-result-log.png":::
 
 > [!NOTE]
-> For production scenarios, you should choose to handle connection and secrets diffirently, using Airflow secrets management.
+> For production scenarios, you should choose to handle connection and secrets differently, using Airflow secrets management.
 
 ## Next steps
 This example demonstrates basic steps required to connect Airflow to Trino with HDInsight on AKS. Main steps are obtaining access token and running query.
diff --git a/articles/hdinsight-aks/trino/trino-fault-tolerance.md b/articles/hdinsight-aks/trino/trino-fault-tolerance.md
@@ -43,7 +43,7 @@ To set up exchange manager with Azure Blob Storage as spooling destination, you
 
 
 > [!TIP]
-> You need to add `exchange-manager.properties` file in `common` component inside `serviceConfigsProfiles.serviceName[“trino”]` section in the cluster ARM template. Refer to [manage confgurations](./trino-service-configuration.md#using-arm-template) on how to add configuration files to your cluster.
+> You need to add `exchange-manager.properties` file in `common` component inside `serviceConfigsProfiles.serviceName[“trino”]` section in the cluster ARM template. Refer to [manage configurations](./trino-service-configuration.md#using-arm-template) on how to add configuration files to your cluster.
 
 Example:
 
diff --git a/articles/hdinsight-aks/trino/trino-superset.md b/articles/hdinsight-aks/trino/trino-superset.md
@@ -124,7 +124,7 @@ This step creates the Azure Kubernetes Service (AKS) cluster where you can insta
 
     **Optional**: use Microsoft Azure Postgres instead of using the Postgres deployed inside the Kubernetes cluster. 
     
-    Create an "Azure Database for PostgreSQL" instance to allow easier maintainence, allow for backups, and provide better reliability.
+    Create an "Azure Database for PostgreSQL" instance to allow easier maintenance, allow for backups, and provide better reliability.
     
     ```yaml
     postgresql:
diff --git a/articles/hdinsight/apache-ambari-email.md b/articles/hdinsight/apache-ambari-email.md
@@ -28,7 +28,7 @@ In this tutorial, you learn how to:
 * An HDInsight cluster. See [Create Apache Hadoop clusters using the Azure portal](./hdinsight-hadoop-create-linux-clusters-portal.md).
 
 > [!NOTE]
-> Users can no logner set passwords for their SendGrid account, so we need use apikey to send email.
+> Users can no longer set passwords for their SendGrid account, so we need use apikey to send email.
 
 ## Obtain SendGrid apikey
 
diff --git a/articles/hdinsight/configure-azure-blob-storage.md b/articles/hdinsight/configure-azure-blob-storage.md
@@ -67,7 +67,7 @@ Same thing can be achieved via ARM request if that is how you want to create HDI
 
     } 
     ```
-1. For Exapmple, 
+1. For Example, 
 
     ```
     { 
diff --git a/articles/hdinsight/hadoop/apache-hadoop-connect-excel-hive-odbc-driver.md b/articles/hdinsight/hadoop/apache-hadoop-connect-excel-hive-odbc-driver.md
@@ -32,7 +32,7 @@ The following steps show you how to create a Hive ODBC Data Source.
 
 1. From Windows, navigate to **Start > Windows Administrative Tools > ODBC Data Sources (32-bit)/(64-bit)**.  This action opens the **ODBC Data Source Administrator** window.
 
-   :::image type="content" source="./media/apache-hadoop-connect-excel-hive-odbc-driver/simbahiveodbc-datasourceadmin1.png" alt-text="OBDC data source administrator." border="true":::
+   :::image type="content" source="./media/apache-hadoop-connect-excel-hive-odbc-driver/simbahiveodbc-datasourceadmin1.png" alt-text="ODBC data source administrator." border="true":::
 
 1. From the **User DSN** tab, select **Add** to open the **`Create New Data Source`** window.
 
diff --git a/articles/hdinsight/hdinsight-release-notes-archive.md b/articles/hdinsight/hdinsight-release-notes-archive.md
@@ -1260,7 +1260,7 @@ HDInsight made some improvements and optimizations on scaling for HBase accelera
 No deprecation in this release.
 
 ### Behavior changes
-#### Disable Stardard_A5 VM size as Head Node for HDInsight 4.0
+#### Disable Standard_A5 VM size as Head Node for HDInsight 4.0
 HDInsight cluster Head Node is responsible for initializing and managing the cluster. Standard_A5 VM size has reliability issues as Head Node for HDInsight 4.0. Starting from this release, customers won't be able to create new clusters with Standard_A5 VM size as Head Node. You can use other two-core VMs like E2_v3 or E2s_v3. Existing clusters will run as is. A four-core VM is highly recommended for Head Node to ensure the high availability and reliability of your production HDInsight clusters.
 
 #### Network interface resource not visible for clusters running on Azure virtual machine scale sets
@@ -1331,7 +1331,7 @@ You need to drop and recreate your clusters if you’d like to move existing clu
 
 It’s highly recommended that you test your script actions and custom applications deployed on edge nodes on an Ubuntu 18.04 virtual machine (VM) in advance. You can [create Ubuntu Linux VM on 18.04-LTS](https://azure.microsoft.com/resources/templates/vm-simple-linux/), then create and use a [secure shell (SSH) key pair](/azure/virtual-machines/linux/mac-create-ssh-keys#ssh-into-your-vm) on your VM to run and test your script actions and custom applications deployed on edge nodes.
 
-#### Disable Stardard_A5 VM size as Head Node for HDInsight 4.0
+#### Disable Standard_A5 VM size as Head Node for HDInsight 4.0
 HDInsight cluster Head Node is responsible for initializing and managing the cluster. Standard_A5 VM size has reliability issues as Head Node for HDInsight 4.0. Starting from the next release in May 2021, customers won't be able to create new clusters with Standard_A5 VM size as Head Node. You can use other 2-core VMs like E2_v3 or E2s_v3. Existing clusters will run as is. A 4-core VM is highly recommended for Head Node to ensure the high availability and reliability of your production HDInsight clusters.
 
 ### Bug fixes
@@ -1357,7 +1357,7 @@ HDInsight now uses Azure virtual machines to provision the cluster. The service
 
 ### Deprecation
 #### Disabled VM sizes
-Starting from January 9 2021, HDInsight will block all customers creating clusters using standand_A8, standand_A9, standand_A10 and standand_A11 VM sizes. Existing clusters will run as is. Consider moving to HDInsight 4.0 to avoid potential system/support interruption.
+Starting from January 9 2021, HDInsight will block all customers creating clusters using standard_A8, standard_A9, standard_A10 and standard_A11 VM sizes. Existing clusters will run as is. Consider moving to HDInsight 4.0 to avoid potential system/support interruption.
 
 ### Behavior changes
 #### Default cluster VM size changes to `Ev3`-series 
@@ -1400,7 +1400,7 @@ HDInsight now uses Azure virtual machines to provision the cluster. Starting fro
 HDInsight 3.6 ML Services cluster type will be end of support by December 31 2020. Customers won't be able to create new 3.6 ML Services clusters after December 31 2020. Existing clusters will run as is without the support from Microsoft. Check the support expiration for HDInsight versions and cluster types [here](./hdinsight-component-versioning.md).
 
 #### Disabled VM sizes
-Starting from November 16 2020, HDInsight will block new customers creating clusters using standand_A8, standand_A9, standand_A10 and standand_A11 VM sizes. Existing customers who have used these VM sizes in the past three months won't be affected. Starting from January 9 2021, HDInsight will block all customers creating clusters using standand_A8, standand_A9, standand_A10 and standand_A11 VM sizes. Existing clusters will run as is. Consider moving to HDInsight 4.0 to avoid potential system/support interruption.
+Starting from November 16 2020, HDInsight will block new customers creating clusters using standard_A8, standard_A9, standard_A10 and standard_A11 VM sizes. Existing customers who have used these VM sizes in the past three months won't be affected. Starting from January 9 2021, HDInsight will block all customers creating clusters using standard_A8, standard_A9, standard_A10 and standard_A11 VM sizes. Existing clusters will run as is. Consider moving to HDInsight 4.0 to avoid potential system/support interruption.
 
 ### Behavior changes
 #### Add NSG rule checking before scaling operation
@@ -1429,7 +1429,7 @@ HDInsight now uses Azure virtual machines to provision the cluster. Starting fro
 HDInsight 3.6 ML Services cluster type will be end of support by December 31 2020. Customers won't create new 3.6 ML Services clusters after December 31 2020. Existing clusters will run as is without the support from Microsoft. Check the support expiration for HDInsight versions and cluster types [here](./hdinsight-component-versioning.md#supported-hdinsight-versions).
 
 #### Disabled VM sizes
-Starting from November 16 2020, HDInsight will block new customers creating clusters using standand_A8, standand_A9, standand_A10 and standand_A11 VM sizes. Existing customers who have used these VM sizes in the past three months won't be affected. Starting from January 9 2021, HDInsight will block all customers creating clusters using standand_A8, standand_A9, standand_A10 and standand_A11 VM sizes. Existing clusters will run as is. Consider moving to HDInsight 4.0 to avoid potential system/support interruption.
+Starting from November 16 2020, HDInsight will block new customers creating clusters using standard_A8, standard_A9, standard_A10 and standard_A11 VM sizes. Existing customers who have used these VM sizes in the past three months won't be affected. Starting from January 9 2021, HDInsight will block all customers creating clusters using standard_A8, standard_A9, standard_A10 and standard_A11 VM sizes. Existing clusters will run as is. Consider moving to HDInsight 4.0 to avoid potential system/support interruption.
 
 ### Behavior changes
 No behavior change for this release.
diff --git a/articles/hdinsight/interactive-query/apache-hive-query-odbc-driver-powershell.md b/articles/hdinsight/interactive-query/apache-hive-query-odbc-driver-powershell.md
@@ -37,7 +37,7 @@ 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.
 
-    :::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":::
+    :::image type="content" source="./media/apache-hive-query-odbc-driver-powershell/hive-odbc-driver-dsn-setup.png " alt-text="ODBC data source administrator." border="true":::
 
 1. From the **User DSN** tab, select **Add** to open the **Create New Data Source** window.
 
diff --git a/articles/hdinsight/interactive-query/hive-warehouse-connector-apis.md b/articles/hdinsight/interactive-query/hive-warehouse-connector-apis.md
diff --git a/articles/hdinsight/interactive-query/hive-warehouse-connector-v2-apis.md b/articles/hdinsight/interactive-query/hive-warehouse-connector-v2-apis.md
diff --git a/articles/hdinsight/interactive-query/llap-schedule-based-autoscale-best-practices.md b/articles/hdinsight/interactive-query/llap-schedule-based-autoscale-best-practices.md
diff --git a/articles/hdinsight/optimize-hive-ambari.md b/articles/hdinsight/optimize-hive-ambari.md
diff --git a/articles/hdinsight/spark/apache-spark-intellij-tool-debug-remotely-through-ssh.md b/articles/hdinsight/spark/apache-spark-intellij-tool-debug-remotely-through-ssh.md
diff --git a/articles/hdinsight/spark/apache-spark-intellij-tool-failure-debug.md b/articles/hdinsight/spark/apache-spark-intellij-tool-failure-debug.md
diff --git a/articles/hdinsight/spark/apache-spark-load-data-run-query.md b/articles/hdinsight/spark/apache-spark-load-data-run-query.md
diff --git a/articles/hdinsight/spark/apache-spark-troubleshoot-event-log-requestbodytoolarge.md b/articles/hdinsight/spark/apache-spark-troubleshoot-event-log-requestbodytoolarge.md
