Merge pull request #211678 from sreekzz/patch-109

Freshness Score MS Date Change

Author: ShannonLeavitt

articles/hdinsight/hdinsight-upgrade-cluster.md

@@ -5,11 +5,11 @@ description: Learn guidelines to migrate your Azure HDInsight cluster to a newer
 ms.service: hdinsight
 ms.topic: how-to
 ms.custom: hdinsightactive
-ms.date: 01/31/2020
+ms.date: 09/19/2022
 ---
 # Migrate HDInsight cluster to a newer version
 
-To take advantage of the latest HDInsight features, we recommend that HDInsight clusters be regularly migrated to latest version. HDInsight does not support in-place upgrades where an existing cluster is upgraded to a newer component version. You must create a new cluster with the desired component and platform version and then migrate your applications to use the new cluster. Follow the below guidelines to migrate your HDInsight cluster versions.
+To take advantage of the latest HDInsight features, we recommend that HDInsight clusters be regularly migrated to latest version. HDInsight doesn't support in-place upgrades where an existing cluster is upgraded to a newer component version. You must create a new cluster with the desired component and platform version and then migrate your applications to use the new cluster. Follow the below guidelines to migrate your HDInsight cluster versions.
 
 > [!NOTE]  
 > For information on supported versions of HDInsight, see [HDInsight component versions](hdinsight-component-versioning.md#supported-hdinsight-versions).
@@ -24,9 +24,9 @@ The workflow to upgrade HDInsight Cluster is as follows.
 3. Copy existing jobs, data sources, and sinks to the new environment.
 4. Perform validation testing to make sure that your jobs work as expected on the new cluster.
 
-Once you have verified that everything works as expected, schedule downtime for the migration. During this downtime, do the following actions:
+Once you've verified that everything works as expected, schedule downtime for the migration. During this downtime, do the following actions:
 
-1. Back up any transient data stored locally on the cluster nodes. For example, if you have data stored directly on a head node.
+1. Back up any transient data stored locally on the cluster nodes. For example, if you've data stored directly on a head node.
 1. [Delete the existing cluster](./hdinsight-delete-cluster.md).
 1. Create a cluster in the same VNET subnet with latest (or supported) HDI version using the same default data store that the previous cluster used. This allows the new cluster to continue working against your existing production data.
 1. Import any transient data you backed up.
@@ -46,18 +46,18 @@ For more information about database backup and restore, see [Recover a database
 
 ## Upgrade scenarios
 
-As mentioned above, Microsoft recommends that HDInsight clusters be regularly migrated to the latest version in order to take advantage of new features and fixes. Please see the following list of reasons we would request that a cluster be deleted and redeployed:
+As mentioned above, Microsoft recommends that HDInsight clusters be regularly migrated to the latest version in order to take advantage of new features and fixes.  See the following list of reasons we would request that a cluster to be deleted and redeployed:
 
-* The cluster version is [Retired](hdinsight-retired-versions.md) or in [Basic support](hdinsight-36-component-versioning.md) and you are having a cluster issue that would be resolved with a newer version.
-* The root cause of a cluster issue is determined to be related to an undersized VM. [View Microsoft's recommended node configuration](hdinsight-supported-node-configuration.md).
+* The cluster version is [Retired](hdinsight-retired-versions.md) or in [Basic support](hdinsight-36-component-versioning.md) and you're having a cluster issue that would be resolved with a newer version.
+* The root cause of a cluster issue is determined to relate an undersized VM. [View Microsoft's recommended node configuration](hdinsight-supported-node-configuration.md).
 * A customer opens a support case and the Microsoft engineering team determines the issue has already been fixed in a newer cluster version.
-* A default metastore database (Ambari, Hive, Oozie, Ranger) has reached it's utilization limit. Microsoft will ask you to recreate the cluster using a [custom metastore](hdinsight-use-external-metadata-stores.md#custom-metastore) database.
+* A default metastore database (Ambari, Hive, Oozie, Ranger) has reached its utilization limit. Microsoft will ask you to recreate the cluster using a [custom metastore](hdinsight-use-external-metadata-stores.md#custom-metastore) database.
 * The root cause of a cluster issue is due to an **Unsupported Operation**. Here are some of the common unsupported operations:
-     * **Moving or Adding a service in Ambari**. When viewing information on the cluster services in Ambari, one of the actions available from the Service Actions menu is **Move [Service Name]**. Another action is **Add [Service Name]**. Both of these options are unsupported.
+     * **Moving or Adding a service in Ambari**. See the information on the cluster services in Ambari, one of the actions available from the Service Actions menu is **Move [Service Name]**. Another action is **Add [Service Name]**. Both of these options are unsupported.
      * **Python package corruption**. HDInsight clusters depend on the built-in Python environments, Python 2.7 and Python 3.5. Directly installing custom packages in those default built-in environments may cause unexpected library version changes and break the cluster. Learn how to [safely install custom external Python packages](./spark/apache-spark-python-package-installation.md#safely-install-external-python-packages) for your Spark applications.
-     * **Third-party software**. Customers have the ability to install third-party software on their HDInsight clusters; however, we will recommend recreating the cluster if it breaks the existing functionality.
-     * **Multiple workloads on the same cluster**. In HDInsight 4.0, the Hive Warehouse Connector needs separate clusters for Spark and Interactive Query workloads. [Follow these steps to set up both clusters in Azure HDInsight](interactive-query/apache-hive-warehouse-connector.md). Similarly, integrating [Spark with HBASE](hdinsight-using-spark-query-hbase.md) requires 2 different clusters.
-     * **Custom Ambari DB password changed**. The Ambari DB password is set during cluster creation and there is no current mechanism to update it. If a customer deploys the cluster with a [custom Ambari DB](hdinsight-custom-ambari-db.md), they will have the ability to change the DB password on the SQL DB; however, there is no way to update this password for a running HDInsight cluster.
+     * **Third-party software**. Customers have the ability to install third-party software on their HDInsight clusters; however, we'll recommend recreating the cluster if it breaks the existing functionality.
+     * **Multiple workloads on the same cluster**. In HDInsight 4.0, the Hive Warehouse Connector needs separate clusters for Spark and Interactive Query workloads. [Follow these steps to set up both clusters in Azure HDInsight](interactive-query/apache-hive-warehouse-connector.md). Similarly, integrating [Spark with HBASE](hdinsight-using-spark-query-hbase.md) requires two  different clusters.
+     * **Custom Ambari DB password changed**. The Ambari DB password is set during cluster creation and there's no current mechanism to update it. If a customer deploys the cluster with a [custom Ambari DB](hdinsight-custom-ambari-db.md), they'll have the ability to change the DB password on the SQL DB; however, there's no way to update this password for a running HDInsight cluster.
 
 ## Next steps