Merge pull request #305243 from whhender/updating-invalid-author

prmerger-automator[bot] · web-flow · commit 45fb7d5eec02 · 2025-09-09T17:54:11.000Z
Updating author
diff --git a/articles/hdinsight/component-version-validation-error-arm-templates.md b/articles/hdinsight/component-version-validation-error-arm-templates.md
@@ -5,8 +5,8 @@ ms.service: azure-hdinsight
 ms.custom: devx-track-arm-template
 ms.topic: troubleshooting-known-issue
 ms.date: 03/26/2024
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ---
 
diff --git a/articles/hdinsight/disk-encryption.md b/articles/hdinsight/disk-encryption.md
@@ -6,8 +6,8 @@ ms.service: azure-hdinsight
 ms.topic: conceptual
 ms.date: 06/15/2024
 ms.devlang: azurecli
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: hgowrisankar
 ms.custom:
   - devx-track-azurepowershell
diff --git a/articles/hdinsight/hdinsight-40-component-versioning.md b/articles/hdinsight/hdinsight-40-component-versioning.md
@@ -3,8 +3,8 @@ title: Open-source components and versions - Azure HDInsight 4.0
 description: Learn about the open-source  components and versions in Azure HDInsight 4.0.
 ms.service: azure-hdinsight
 ms.topic: conceptual
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 04/11/2024
 ---
diff --git a/articles/hdinsight/hdinsight-5x-component-versioning.md b/articles/hdinsight/hdinsight-5x-component-versioning.md
@@ -3,8 +3,8 @@ title: Open-source components and versions - Azure HDInsight 5.x
 description: Learn about the open-source components and versions in Azure HDInsight 5.x.
 ms.service: azure-hdinsight
 ms.topic: conceptual
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 10/17/2024
 ---
diff --git a/articles/hdinsight/hdinsight-apps-install-applications.md b/articles/hdinsight/hdinsight-apps-install-applications.md
@@ -4,8 +4,8 @@ description: Learn how to install third-party Apache Hadoop applications on Azur
 ms.service: azure-hdinsight
 ms.custom: hdinsightactive
 ms.topic: how-to
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: hgowrisankar
 ms.date: 12/02/2024
 
diff --git a/articles/hdinsight/hdinsight-component-retirements-and-action-required.md b/articles/hdinsight/hdinsight-component-retirements-and-action-required.md
@@ -4,8 +4,8 @@ description: Learn about HDInsight retirement versions and its components in Azu
 ms.service: azure-hdinsight
 ms.topic: conceptual
 ms.date: 08/11/2025
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: hgowrisankar
 ---
 
diff --git a/articles/hdinsight/hdinsight-component-versioning.md b/articles/hdinsight/hdinsight-component-versioning.md
@@ -3,8 +3,8 @@ title: Open-source components and versions - Azure HDInsight
 description: Learn about the open-source components and versions in Azure HDInsight.
 ms.service: azure-hdinsight
 ms.topic: conceptual
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 11/04/2024
 ---
diff --git a/articles/hdinsight/hdinsight-known-issues-conda-version-regression.md b/articles/hdinsight/hdinsight-known-issues-conda-version-regression.md
@@ -3,8 +3,8 @@ title: Conda Version Regression in a recent HDInsight release
 description: Known issue affecting image version 5.1.3000.0.2308052231
 ms.service: azure-hdinsight
 ms.topic: troubleshooting-known-issue
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 02/03/2025
 ---
diff --git a/articles/hdinsight/hdinsight-overview-versioning.md b/articles/hdinsight/hdinsight-overview-versioning.md
@@ -3,8 +3,8 @@ title: Versioning introduction - Azure HDInsight
 description: Learn how versioning works in Azure HDInsight.
 ms.service: azure-hdinsight
 ms.topic: conceptual
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 04/11/2024
 ---
diff --git a/articles/hdinsight/hdinsight-ranger-5-1-migration.md b/articles/hdinsight/hdinsight-ranger-5-1-migration.md
@@ -3,8 +3,8 @@ title: Upgrade to Apache Ranger in Azure HDInsight
 description: Learn how to upgrade to Apache Ranger in Azure HDInsight 
 ms.service: azure-hdinsight
 ms.topic: how-to
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 09/10/2024
 ---
diff --git a/articles/hdinsight/hdinsight-retired-versions.md b/articles/hdinsight/hdinsight-retired-versions.md
@@ -3,8 +3,8 @@ title: Azure HDInsight retired versions
 description: Learn about retired versions in Azure HDInsight.
 ms.service: azure-hdinsight
 ms.topic: conceptual
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 07/10/2024
 ---
diff --git a/articles/hdinsight/hdinsight-supported-node-configuration.md b/articles/hdinsight/hdinsight-supported-node-configuration.md
@@ -5,8 +5,8 @@ keywords: vm sizes, cluster sizes, cluster configuration
 ms.service: azure-hdinsight
 ms.topic: conceptual
 ms.custom: hdinsightactive
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: nijelsf
 ms.date: 07/12/2024
 ---
diff --git a/articles/hdinsight/open-source-software.md b/articles/hdinsight/open-source-software.md
@@ -4,8 +4,8 @@ description: Microsoft Azure provides a general level of support for open-source
 ms.service: azure-hdinsight
 ms.topic: how-to
 ms.date: 02/03/2025
-author: anuj1905
-ms.author: anujsharda
+author: apurbasroy
+ms.author: apsinhar
 ms.reviewer: hgowrisankar
 ---
 
diff --git a/articles/synapse-analytics/overview-faq.yml b/articles/synapse-analytics/overview-faq.yml
@@ -2,12 +2,12 @@
 metadata:
   title: FAQ - Azure Synapse Analytics
   description: FAQ for Azure Synapse Analytics
-  author: guyhay
+  author: ajagadish-24
   ms.service: azure-synapse-analytics
   ms.topic: faq
   ms.subservice: overview
   ms.date: 11/16/2022
-  ms.author: guyhay
+  ms.author: ajagadish
 title: Azure Synapse Analytics frequently asked questions
 summary: In this guide, you'll find the most frequently asked questions for Azure Synapse Analytics.
 
diff --git a/articles/synapse-analytics/overview-terminology.md b/articles/synapse-analytics/overview-terminology.md
@@ -1,12 +1,12 @@
 ---
 title: Terminology - Azure Synapse Analytics
 description: Learn about basic concepts and terminology for Azure Synapse Analytics in this reference guide.
-author: guyhay
+author: ajagadish-24
 ms.service: azure-synapse-analytics
 ms.topic: overview
 ms.subservice: overview
 ms.date: 01/23/2025
-ms.author: guyhay
+ms.author: ajagadish
 ---
 
 # Azure Synapse Analytics terminology
diff --git a/articles/synapse-analytics/overview-what-is.md b/articles/synapse-analytics/overview-what-is.md
@@ -1,12 +1,12 @@
 ---
 title: What is Azure Synapse Analytics?
 description: An Overview of Azure Synapse Analytics
-author: guyhay
+author: ajagadish-24
 ms.service: azure-synapse-analytics
 ms.topic: overview
 ms.subservice: overview
 ms.date: 07/10/2024
-ms.author: guyhay
+ms.author: ajagadish
 ---
 
 # What is Azure Synapse Analytics?
diff --git a/articles/synapse-analytics/plan-manage-costs.md b/articles/synapse-analytics/plan-manage-costs.md
@@ -4,8 +4,8 @@ description: Learn how to plan for and manage costs for Azure Synapse Analytics
 ms.topic: how-to
 ms.service: azure-synapse-analytics
 ms.subservice: overview
-ms.author: guyhay
-author: guyhay
+ms.author: ajagadish
+author: ajagadish-24
 ms.date: 02/09/2023
 ms.custom:
   - subject-cost-optimization
diff --git a/articles/synapse-analytics/spark/apache-spark-autoscale.md b/articles/synapse-analytics/spark/apache-spark-autoscale.md
@@ -1,8 +1,8 @@
 ---
 title: Automatically scale Apache Spark instances
 description: Use the Azure Synapse Analytics autoscale feature to automatically scale Apache Spark Pools
-author: guyhay
-ms.author: guyhay
+author: ajagadish-24
+ms.author: ajagadish
 ms.service: azure-synapse-analytics
 ms.topic: conceptual
 ms.subservice: spark
@@ -11,7 +11,7 @@ ms.date: 03/11/2024
 
 # Automatically scale Azure Synapse Analytics Apache Spark pools
 
-Apache Spark for Azure Synapse Analytics pool's Autoscale feature automatically scales the number of nodes in a cluster instance up and down. During the creation of a new Apache Spark for Azure Synapse Analytics pool, a minimum and maximum number of nodes, up to 200 nodes, can be set when Autoscale is selected. Autoscale then monitors the resource requirements of the load and scales the number of nodes up or down. There's no additional charge for this feature.
+Apache Spark for Azure Synapse Analytics pool's Autoscale feature automatically scales the number of nodes in a cluster instance up and down. During the creation of a new Apache Spark for Azure Synapse Analytics pool, a minimum and maximum number of nodes, up to 200 nodes, can be set when Autoscale is selected. Autoscale then monitors the resource requirements of the load and scales the number of nodes up or down. There's no extra charge for this feature.
 
 ## Metrics monitoring
 
@@ -38,10 +38,10 @@ When the following conditions are detected, Autoscale will issue a scale request
 
 For scale-up, the Azure Synapse Autoscale service calculates how many new nodes are needed to meet the current CPU and memory requirements, and then issues a scale-up request to add the required number of nodes.
 
-For scale-down, based on the number of executors, application masters per node, the current CPU and memory requirements, Autoscale issues a request to remove a certain number of nodes. The service also detects which nodes are candidates for removal based on current job execution. The scale down operation first decommissions the nodes, and then removes them from the cluster.
+For scale-down, based on the number of executors, application masters per node, the current CPU, and memory requirements, Autoscale issues a request to remove some nodes. The service also detects which nodes are candidates for removal based on current job execution. The scale down operation first decommissions the nodes, and then removes them from the cluster.
 
 >[!NOTE]
->A note about updating and force applying autoscale configuration to an existing Spark pool. If **Force new setting** in the Azure portal or `ForceApplySetting` in [PowerShell](/powershell/module/az.synapse/update-azsynapsesparkpool) is enabled, then all existing Spark sessions are terminated and configuration changes are applied immediately. If this option is not selected, then the configuration is applied to the new Spark sessions and existing sessions are not terminated.
+>A note about updating and force applying autoscale configuration to an existing Spark pool. If **Force new setting** in the Azure portal or `ForceApplySetting` in [PowerShell](/powershell/module/az.synapse/update-azsynapsesparkpool) is enabled, then all existing Spark sessions are terminated and configuration changes are applied immediately. If this option isn't selected, then the configuration is applied to the new Spark sessions and existing sessions aren't terminated.
 
 ## Get started
 
@@ -75,7 +75,7 @@ Apache Spark enables configuration of Dynamic Allocation of Executors through co
 ```
 The defaults specified through the code override the values set through the user interface.
 
-In this example, if your job requires only 2 executors, it will use only 2 executors.  When the job requires more, it will scale up to 6 executors (1 driver, 6 executors).  When the job doesn't need the executors, then it will decommission the executors. If it doesn't need the node, it will free up the node.
+In this example, if your job requires only two executors, it uses only two executors. When the job requires more, it will scale up to six executors (one driver, six executors). When the job doesn't need the executors, then it will decommission the executors. If it doesn't need the node, it will free up the node.
 
 >[!NOTE]
 >The maxExecutors will reserve the number of executors configured. Considering the example, even if you use only 2, it will reserve 6. 
diff --git a/articles/synapse-analytics/spark/apache-spark-concepts.md b/articles/synapse-analytics/spark/apache-spark-concepts.md
@@ -4,8 +4,8 @@ description: Introduction to core concepts for Apache Spark in Azure Synapse Ana
 ms.service: azure-synapse-analytics
 ms.subservice: spark
 ms.topic: overview
-author: guyhay
-ms.author: guyhay
+author: ajagadish-24
+ms.author: ajagadish
 ms.date: 04/02/2024 
 ---
 
@@ -21,17 +21,17 @@ A serverless Apache Spark pool is created in the Azure portal. It's the definiti
 
 As there's no dollar or resource cost associated with creating Spark pools, any number can be created with any number of different configurations. Permissions can also be applied to Spark pools allowing users only to have access to some and not others.
 
-A best practice is to create smaller Spark pools that may be used for development and debugging and then larger ones for running production workloads.
+A best practice is to create smaller Spark pools that for development and debugging and then larger ones for running production workloads.
 
 You can read how to create a Spark pool and see all their properties here [Get started with Spark pools in Azure Synapse Analytics](../quickstart-create-apache-spark-pool-portal.md)
 
 ## Spark instances
 
-Spark instances are created when you connect to a Spark pool, create a session, and run a job. As multiple users may have access to a single Spark pool, a new Spark instance is created for each user that connects.
+Spark instances are created when you connect to a Spark pool, create a session, and run a job. As multiple users can have access to a single Spark pool, a new Spark instance is created for each user that connects.
 
 When you submit a second job, if there's capacity in the pool, the existing Spark instance also has capacity. Then, the existing instance processes the job. Otherwise, if capacity is available at the pool level, a new Spark instance is created.
 
-Billing for the instances starts when the Azure VM(s) starts. Billing for the Spark pool instances stops when pool instances change to terminating. For more information on how Azure VMs are started and deallocated, see [States and billing status of Azure Virtual Machines](/azure/virtual-machines/states-billing).
+Billing for the instances starts when the Azure virtual machine starts. Billing for the Spark pool instances stops when pool instances change to terminating. For more information on how Azure VMs are started and deallocated, see [States and billing status of Azure Virtual Machines](/azure/virtual-machines/states-billing).
 
 ## Examples
 
@@ -40,7 +40,7 @@ Billing for the instances starts when the Azure VM(s) starts. Billing for the Sp
 - You create a Spark pool called SP1; it has a fixed cluster size of 20 medium nodes
 - You submit a notebook job, J1 that uses 10 nodes, a Spark instance, SI1 is created to process the job
 - You now submit another job, J2, that uses 10 nodes because there's still capacity in the pool and the instance, the J2, is processed by SI1
-- If J2 had asked for 11 nodes, there wouldn't have been capacity in SP1 or SI1. In this case, if J2 comes from a notebook, then the job is rejected; if J2 comes from a batch job, it is queued.
+- If J2 had asked for 11 nodes, there wouldn't have been capacity in SP1 or SI1. In this case, if J2 comes from a notebook, then the job is rejected; if J2 comes from a batch job, it's queued.
 - Billing starts at the submission of notebook job J1.
   - The Spark pool is instantiated with 20 medium nodes, each with 8 vCores, and typically takes ~3 minutes to start. 20 x 8 = 160 vCores.
   - Depending on the exact Spark pool start-up time, idle timeout and the runtime of the two notebook jobs; the pool is likely to run for between 18 and 20 minutes (Spark pool instantiation time + notebook job runtime + idle timeout).
@@ -70,7 +70,7 @@ Billing for the instances starts when the Azure VM(s) starts. Billing for the Sp
   - Depending on the exact Spark pool start-up time, the ide timeout and the runtime of the first, and third notebook job; The SI1 pool is likely to run for between 18 and 20 minutes (Spark pool instantiation time + notebook job runtime + idle timeout).
   - Another Spark pool SI2 is instantiated with 20 medium nodes, each with 8 vCores, and typically takes ~3 minutes to start. 20 x 8, 160 vCores
   - Depending on the exact Spark pool start-up time, the ide timeout and the runtime of the first notebook job; The SI2 pool is likely to run for between 18 and 20 minutes (Spark pool instantiation time + notebook job runtime + idle timeout).
-  - Assuming the two pools run for 20 minutes each, 160 x .03 x 2 = 96 vCore hours.
+  - Assuming the two pools run for 20 minutes each, 160 x 0.03 x 2 = 96 vCore hours.
   - Note: vCore hours are billed per minute and vCore pricing varies by Azure region. For more information, see [Azure Synapse Pricing](https://azure.microsoft.com/pricing/details/synapse-analytics/#pricing)
 
 ## Quotas and resource constraints in Apache Spark for Azure Synapse
@@ -97,7 +97,7 @@ The following article describes how to request an increase in workspace vCore qu
 
 ### Spark pool level
 
-When you define a Spark pool you're effectively defining a quota per user for that pool, if you run multiple notebooks, or jobs or a mix of the 2 it's possible to exhaust the pool quota. If you do, then an error message will be generated
+When you define a Spark pool you're effectively defining a quota per user for that pool, if you run multiple notebooks, jobs, or a mix of the two, it's possible to exhaust the pool quota. If you do, then an error message will be generated
 
 ```console
 Failed to start session: Your Spark job requested xx vCores.
diff --git a/articles/synapse-analytics/spark/apache-spark-pool-configurations.md b/articles/synapse-analytics/spark/apache-spark-pool-configurations.md
@@ -5,8 +5,8 @@ ms.topic: concept-article
 ms.service: azure-synapse-analytics
 ms.subservice: spark
 ms.custom: references_regions
-author: guyhay
-ms.author: guyhay
+author: ajagadish-24
+ms.author: ajagadish
 ms.date: 12/06/2024
 ---
 
