Merge pull request #294636 from whhender/fixing-broken-author

Stacyrch140 · web-flow · commit c6043ef6d0ec · 2025-02-13T19:24:17.000-05:00
Resolving authors
diff --git a/articles/synapse-analytics/spark/apache-spark-24-runtime.md b/articles/synapse-analytics/spark/apache-spark-24-runtime.md
@@ -1,8 +1,8 @@
 ---
 title: Azure Synapse Runtime for Apache Spark 2.4 (unsupported)
 description: Versions of Spark, Scala, Python, and .NET for Apache Spark 2.4.
-author: ekote
-ms.author: eskot 
+author: ms-arali
+ms.author: arali
 ms.service: azure-synapse-analytics
 ms.topic: reference
 ms.subservice: spark
diff --git a/articles/synapse-analytics/spark/apache-spark-3-runtime.md b/articles/synapse-analytics/spark/apache-spark-3-runtime.md
@@ -1,9 +1,9 @@
 ---
 title: Azure Synapse Runtime for Apache Spark 3.1 (unsupported)
 description: Supported versions of Spark, Scala, Python, and .NET for Apache Spark 3.1.
-author: ekote
-ms.author: eskot 
-ms.reviewer: whhender, whhender
+author: ms-arali
+ms.author: arali
+ms.reviewer: whhender
 ms.service: azure-synapse-analytics
 ms.topic: reference
 ms.subservice: spark
@@ -17,12 +17,12 @@ Azure Synapse Analytics supports multiple runtimes for Apache Spark. This docume
 
 > [!CAUTION]
 > Deprecation and disablement notification for Azure Synapse Runtime for Apache Spark 3.1. 
->* **On August 29, 2024,** partial pools and jobs disablement will begin. We will continue with further, **full disablement by September 30, 2024.**  **Immediately** migrate to higher runtime versions otherwise your jobs will stop executing. 
+>* **On August 29, 2024,** partial pools and jobs disablement will begin. We'll continue with further, **full disablement by September 30, 2024.**  **Immediately** migrate to higher runtime versions otherwise your jobs will stop executing. 
 > * **All Spark jobs running on Azure Synapse Runtime for Apache Spark 3.1 will be fully disabled as of** **September 30, 2024.**
 * End of Support for Azure Synapse Runtime for Apache Spark 3.1 announced January 26, 2023.
  * Effective January 26, 2024, the Azure Synapse has stopped official support for Spark 3.1 Runtimes.
- * Post January 26, 2024, we will not be addressing any support tickets related to Spark 3.1. There will be no release pipeline in place for bug or security fixes for Spark 3.1. Utilizing Spark 3.1 post the support cutoff date is undertaken at one's own risk. We strongly discourage its continued use due to potential security and functionality concerns.
- * Recognizing that certain customers may need additional time to transition to a higher runtime version, we are temporarily extending the usage option for Spark 3.1, but we will not provide any official support for it.
+ * Post January 26, 2024, we won't be addressing any support tickets related to Spark 3.1. There will be no release pipeline in place for bug or security fixes for Spark 3.1. Utilizing Spark 3.1 post the support cutoff date is undertaken at one's own risk. We strongly discourage its continued use due to potential security and functionality concerns.
+ * Recognizing that certain customers might need more time to transition to a higher runtime version, we're temporarily extending the usage option for Spark 3.1, but we won't provide any official support for it.
  * **We strongly advise proactively upgrading workloads to a more recent version of the runtime (e.g., [Azure Synapse Runtime for Apache  Spark 3.4 (GA)](./apache-spark-34-runtime.md))**.
 ## Component versions
 
diff --git a/articles/synapse-analytics/spark/apache-spark-32-runtime.md b/articles/synapse-analytics/spark/apache-spark-32-runtime.md
@@ -1,9 +1,9 @@
 ---
 title: Azure Synapse Runtime for Apache Spark 3.2
 description: Supported versions of Spark, Scala, Python, and .NET for Apache Spark 3.2.
-author: ekote
-ms.author: eskot
-ms.reviewer: whhender, whhender
+author: ms-arali
+ms.author: arali
+ms.reviewer: whhender
 ms.service: azure-synapse-analytics
 ms.topic: reference
 ms.subservice: spark
diff --git a/articles/synapse-analytics/spark/apache-spark-33-runtime.md b/articles/synapse-analytics/spark/apache-spark-33-runtime.md
@@ -1,9 +1,9 @@
 ---
 title: Azure Synapse Runtime for Apache Spark 3.3
 description: New runtime is GA and ready for production workloads. Spark 3.3.1, Python 3.10, Delta Lake 2.2.
-author: ekote
-ms.author: eskot
-ms.reviewer: whhender, whhender
+author: ms-arali
+ms.author: arali
+ms.reviewer: whhender
 ms.service: azure-synapse-analytics
 ms.topic: reference
 ms.subservice: spark
@@ -41,9 +41,9 @@ Azure Synapse Analytics supports multiple runtimes for Apache Spark. This docume
 > .NET for Apache Spark
 > * The [.NET for Apache Spark](https://github.com/dotnet/spark) is an open-source project under the .NET Foundation that currently requires the .NET 3.1 library, which has reached the out-of-support status. We would like to inform users of Azure Synapse Spark of the removal of the .NET for Apache Spark library in the Azure Synapse Runtime for Apache Spark version 3.3. Users may refer to the [.NET Support Policy](https://dotnet.microsoft.com/platform/support/policy/dotnet-core) for more details on this matter.
 >
-> * As a result, it will no longer be possible for users to utilize Apache Spark APIs via C# and F#, or execute C# code in notebooks within Synapse or through Apache Spark Job definitions in Synapse. It is important to note that this change affects only Azure Synapse Runtime for Apache Spark 3.3 and above. 
+> * As a result, it will no longer be possible for users to utilize Apache Spark APIs via C# and F#, or execute C# code in notebooks within Synapse or through Apache Spark Job definitions in Synapse. It's important to note that this change affects only Azure Synapse Runtime for Apache Spark 3.3 and above. 
 > 
-> * We will continue to support .NET for Apache Spark in all previous versions of the Azure Synapse Runtime according to [their lifecycle stages](runtime-for-apache-spark-lifecycle-and-supportability.md). However, we do not have plans to support .NET for Apache Spark in Azure Synapse Runtime for Apache Spark 3.3 and future versions. We recommend that users with existing workloads written in C# or F# migrate to Python or Scala. Users are advised to take note of this information and plan accordingly.
+> * We'll continue to support .NET for Apache Spark in all previous versions of the Azure Synapse Runtime according to [their lifecycle stages](runtime-for-apache-spark-lifecycle-and-supportability.md). However, we don't have plans to support .NET for Apache Spark in Azure Synapse Runtime for Apache Spark 3.3 and future versions. We recommend that users with existing workloads written in C# or F# migrate to Python or Scala. Users are advised to take note of this information and plan accordingly.
 
 ## Libraries
 To check the libraries included in Azure Synapse Runtime for Apache Spark 3.3 for Java/Scala, Python, and R go to [Azure Synapse Runtime for Apache Spark 3.3](https://github.com/microsoft/synapse-spark-runtime/tree/main/Synapse/spark3.3)
@@ -58,4 +58,4 @@ To check the libraries included in Azure Synapse Runtime for Apache Spark 3.3 fo
 
 ## Migration between Apache Spark versions - support
 
-For guidance on migrating from older runtime versions to Azure Synapse Runtime for Apache Spark 3.3 or 3.4 refer to [Runtime for Apache Spark Overview](./apache-spark-version-support.md#migration-between-apache-spark-versions---support).
+For guidance on migrating from older runtime versions to Azure Synapse Runtime for Apache Spark 3.3 or 3.4, refer to [Runtime for Apache Spark Overview](./apache-spark-version-support.md#migration-between-apache-spark-versions---support).
diff --git a/articles/synapse-analytics/spark/apache-spark-34-runtime.md b/articles/synapse-analytics/spark/apache-spark-34-runtime.md
@@ -1,9 +1,9 @@
 ---
 title: Azure Synapse Runtime for Apache Spark 3.4 
 description: New runtime is in GA stage. Try it and use Spark 3.4.1, Python 3.10, Delta Lake 2.4.
-author: ekote
-ms.author: eskot
-ms.reviewer: whhender, whhender
+author: ms-arali
+ms.author: arali
+ms.reviewer: whhender
 ms.service: azure-synapse-analytics
 ms.topic: reference
 ms.subservice: spark
diff --git a/articles/synapse-analytics/spark/apache-spark-performance-hyperspace.md b/articles/synapse-analytics/spark/apache-spark-performance-hyperspace.md
@@ -1,9 +1,9 @@
 ---
 title: Hyperspace indexes for Apache Spark
 description: Performance optimization for Apache Spark using Hyperspace indexes
-author: ekote
-ms.author: eskot 
-ms.reviewer: whhender, whhender
+author: ms-arali
+ms.author: arali
+ms.reviewer: whhender
 ms.service: azure-synapse-analytics
 ms.topic: conceptual 
 ms.subservice: spark
diff --git a/articles/synapse-analytics/spark/apache-spark-version-support.md b/articles/synapse-analytics/spark/apache-spark-version-support.md
@@ -1,8 +1,8 @@
 ---
 title: Apache Spark version support
 description: Supported versions of Spark, Scala, Python
-author: ekote
-ms.author: eskot
+author: ms-arali
+ms.author: arali
 ms.reviewer: maghan, whhender, whhender
 ms.date: 03/08/2024
 ms.service: azure-synapse-analytics
@@ -29,7 +29,7 @@ The following table lists the runtime name, Apache Spark version, and release da
 | Runtime name | Release date | Release stage                | End of Support announcement date | End of Support effective date |
 | --- | --- |------------------------------| --- | --- |
 | [Azure Synapse Runtime for Apache Spark 3.4](./apache-spark-34-runtime.md) | Nov 21, 2023 | GA (as of Apr 8, 2024)       | Q2 2025| Q1 2026|
-| [Azure Synapse Runtime for Apache Spark 3.3](./apache-spark-33-runtime.md) | Nov 17, 2022 |**end of support announced**|July 12th, 2024| 3/31/2025 |
+| [Azure Synapse Runtime for Apache Spark 3.3](./apache-spark-33-runtime.md) | Nov 17, 2022 |**end of support announced**|July 12, 2024| 3/31/2025 |
 | [Azure Synapse Runtime for Apache Spark 3.2](./apache-spark-32-runtime.md) | July 8, 2022 | __deprecated and soon disabled__ | July 8, 2023 | __July 8, 2024__ |
 | [Azure Synapse Runtime for Apache Spark 3.1](./apache-spark-3-runtime.md) | May 26, 2021 | __deprecated and soon disabled__         | January 26, 2023 | __January 26, 2024__ |
 | [Azure Synapse Runtime for Apache Spark 2.4](./apache-spark-24-runtime.md) | December 15, 2020 | __deprecated and soon disabled__           | July 29, 2022 | __September 29, 2023__ |
@@ -60,7 +60,7 @@ Azure Synapse runtimes for Apache Spark patches are rolled out monthly containin
 > * ```org/apache/log4j/jdbc/JDBCAppender.class```
 > * ```org/apache/log4j/chainsaw/*```
 >  
-> While the above classes were not used in the default Log4j configurations in Synapse, it is possible that some user application could still depend on it. If your application needs to use these classes, use Library Management to add a secure version of Log4j to the Spark Pool. __Do not use Log4j version 1.2.17__, as it would be reintroducing the vulnerabilities.
+> While the above classes weren't used in the default Log4j configurations in Synapse, it's possible that some user application could still depend on it. If your application needs to use these classes, use Library Management to add a secure version of Log4j to the Spark Pool. __Do not use Log4j version 1.2.17__, as it would be reintroducing the vulnerabilities.
 
 The patch policy differs based on the [runtime lifecycle stage](./runtime-for-apache-spark-lifecycle-and-supportability.md):
 
@@ -75,20 +75,20 @@ The patch policy differs based on the [runtime lifecycle stage](./runtime-for-ap
 
 ## Migration between Apache Spark versions - support
 
-This guide provides a structured approach for users looking to upgrade their Azure Synapse Runtime for Apache Spark workloads from versions 2.4, 3.1, 3.2, or 3.3 to [the latest GA version, such as 3.4](./apache-spark-34-runtime.md). Upgrading to the most recent version enables users to benefit from performance enhancements, new features, and improved security measures. It is important to note that transitioning to a higher version may require adjustments to your existing Spark code due to incompatibilities or deprecated features.
+This guide provides a structured approach for users looking to upgrade their Azure Synapse Runtime for Apache Spark workloads from versions 2.4, 3.1, 3.2, or 3.3 to [the latest GA version, such as 3.4](./apache-spark-34-runtime.md). Upgrading to the most recent version enables users to benefit from performance enhancements, new features, and improved security measures. It's important to note that transitioning to a higher version may require adjustments to your existing Spark code due to incompatibilities or deprecated features.
 
 ### Step 1: Evaluate and plan
-- **Assess Compatibility:** Start with reviewing Apache Spark migration guides to identify any potential incompatibilities, deprecated features, and new APIs between your current Spark version (2.4, 3.1, 3.2, or 3.3) and the target version (e.g., 3.4).
+- **Assess Compatibility:** Start with reviewing Apache Spark migration guides to identify any potential incompatibilities, deprecated features, and new APIs between your current Spark version (2.4, 3.1, 3.2, or 3.3) and the target version (for example, 3.4).
 - **Analyze Codebase:** Carefully examine your Spark code to identify the use of deprecated or modified APIs. Pay particular attention to SQL queries and User Defined Functions (UDFs), which may be affected by the upgrade.
 
 ### Step 2: Create a new Spark pool for testing
-- **Create a New Pool:** In Azure Synapse, go to the Spark pools section and set up a new Spark pool. Select the target Spark version (e.g., 3.4) and configure it according to your performance requirements.
+- **Create a New Pool:** In Azure Synapse, go to the Spark pools section and set up a new Spark pool. Select the target Spark version (for example, 3.4) and configure it according to your performance requirements.
 - **Configure Spark Pool Configuration:** Ensure that all libraries and dependencies in your new Spark pool are updated or replaced to be compatible with Spark 3.4.
 
 ### Step 3: Migrate and test your code
 - **Migrate Code:** Update your code to be compliant with the new or revised APIs in Apache Spark 3.4. This involves addressing deprecated functions and adopting new features as detailed in the official Apache Spark documentation.
 - **Test in Development Environment:** Test your updated code within a development environment in Azure Synapse, not locally. This step is essential for identifying and fixing any issues before moving to production.
-- **Deploy and Monitor:** After thorough testing and validation in the development environment, deploy your application to the new Spark 3.4 pool. It is critical to monitor the application for any unexpected behaviors.  Utilize the monitoring tools available in Azure Synapse to keep track of your Spark applications' performance.
+- **Deploy and Monitor:** After thorough testing and validation in the development environment, deploy your application to the new Spark 3.4 pool. It's critical to monitor the application for any unexpected behaviors. Utilize the monitoring tools available in Azure Synapse to keep track of your Spark applications' performance.
 
 **Question:** What steps should be taken in migrating from 2.4 to 3.X?
 
@@ -102,7 +102,7 @@ This guide provides a structured approach for users looking to upgrade their Azu
 
 **Question:** Why can't I upgrade to 3.4 without recreating a new Spark pool?
 
-**Answer:** This is not allowed from UX, customer can use Azure PowerShell to update Spark version. Please use "ForceApplySetting", so that any existing clusters (with old version) are decommissioned. 
+**Answer:** This isn't allowed from UX, customer can use Azure PowerShell to update Spark version. Use "ForceApplySetting", so that any existing clusters (with old version) are decommissioned. 
 
 **Sample query:**
 
diff --git a/articles/synapse-analytics/spark/data-sources/apache-spark-sql-connector.md b/articles/synapse-analytics/spark/data-sources/apache-spark-sql-connector.md
@@ -1,8 +1,8 @@
 ---
 title: Azure SQL and SQL Server 
 description: This article provides information on how to use the  connector for moving data between Azure MS SQL and serverless Apache Spark pools.
-author: ekote
-ms.author: eskot 
+author: ms-arali
+ms.author: arali
 ms.service: azure-synapse-analytics
 ms.topic: overview
 ms.subservice: spark
@@ -13,14 +13,14 @@ ms.custom: has-adal-ref
 # Azure SQL Database and SQL Server connector for Apache Spark
 The Apache Spark connector for Azure SQL Database and SQL Server enables these databases to act as input data sources and output data sinks for Apache Spark jobs. It allows you to use real-time transactional data in big data analytics and persist results for ad-hoc queries or reporting.
 
-Compared to the built-in JDBC connector, this connector provides the ability to bulk insert data into SQL databases. It can outperform row-by-row insertion with 10x to 20x faster performance. The Spark connector for SQL Server and Azure SQL Database also supports Microsoft Entra [authentication](/sql/connect/spark/connector#azure-active-directory-authentication), enabling you to connect securely to your Azure SQL databases from Azure Synapse Analytics. 
+Compared to the built-in JDBC connector, this connector provides the ability to bulk insert data into SQL databases. It can outperform row-by-row insertion with 10 to 20 times faster performance. The Spark connector for SQL Server and Azure SQL Database also supports Microsoft Entra [authentication](/sql/connect/spark/connector#azure-active-directory-authentication), enabling you to connect securely to your Azure SQL databases from Azure Synapse Analytics. 
 
 This article covers how to use the DataFrame API to connect to SQL databases using the MS SQL connector. This article provides detailed examples using the PySpark API. For all of the supported arguments and samples for connecting to SQL databases using the MS SQL connector, see [Azure Data SQL samples](https://github.com/microsoft/sql-server-samples#azure-data-sql-samples-repository).
 
 
   
 ## Connection details
-In this example, we will use the Microsoft Spark utilities to facilitate acquiring secrets from a pre-configured Key Vault. To learn more about Microsoft Spark utilities, please visit [introduction to Microsoft Spark Utilities](../microsoft-spark-utilities.md).
+In this example, we'll use the Microsoft Spark utilities to facilitate acquiring secrets from a preconfigured Key Vault. To learn more about Microsoft Spark utilities, visit [introduction to Microsoft Spark Utilities](../microsoft-spark-utilities.md).
 
 ```python
 # The servername is in the format "jdbc:sqlserver://<AzureSQLServerName>.database.windows.net:1433"
@@ -35,7 +35,7 @@ password = mssparkutils.credentials.getSecret('azure key vault name','secret nam
 ```
 
 > [!NOTE]
-> Currently, there is no linked service or Microsoft Entra pass-through support with the Azure SQL connector.
+> Currently, there's no linked service or Microsoft Entra pass-through support with the Azure SQL connector.
 
 ## Use the Azure SQL and SQL Server connector
 
@@ -144,12 +144,12 @@ jdbc_df = spark.read \
 > - A required dependency must be installed in order to authenticate using Active Directory. 
 > - The format of `user` when using ActiveDirectoryPassword should be the UPN format, for example `username@domainname.com`. 
 >   - For **Scala**, the `com.microsoft.aad.adal4j` artifact will need to be installed.
->   - For **Python**, the `adal` library will need to be installed.  This is available via pip.
+>   - For **Python**, the `adal` library will need to be installed. This is available via pip.
 > - Check the [sample notebooks](https://github.com/microsoft/sql-spark-connector/tree/master/samples) for examples and for latest drivers and versions, visit [Apache Spark connector: SQL Server & Azure SQL](/sql/connect/spark/connector).
 
 ## Support
 
-The Apache Spark Connector for Azure SQL and SQL Server is an open-source project. This connector does not come with any Microsoft support. For issues with or questions about the connector, create an Issue in this project repository. The connector community is active and monitoring submissions.
+The Apache Spark Connector for Azure SQL and SQL Server is an open-source project. This connector doesn't come with any Microsoft support. For issues with or questions about the connector, create an Issue in this project repository. The connector community is active and monitoring submissions.
 
 ## Next steps
 - [Learn more about the SQL Server and Azure SQL connector](/sql/connect/spark/connector)
diff --git a/articles/synapse-analytics/spark/synapse-spark-sql-pool-import-export.md b/articles/synapse-analytics/spark/synapse-spark-sql-pool-import-export.md
@@ -1,12 +1,12 @@
 ---
 title: Azure Synapse Dedicated SQL Pool Connector for Apache Spark
 description: Azure Synapse Dedicated SQL Pool Connector for Apache Spark to move data between the Synapse Serverless Spark Pool and the Synapse Dedicated SQL Pool.
-author: kalyankadiyala-Microsoft
+author: dawn2111
 ms.service: azure-synapse-analytics
 ms.topic: overview
 ms.subservice: spark
 ms.date: 01/22/2025
-ms.author: kakadiya
+ms.author: prdawn
 ms.reviewer: ktuckerdavis, aniket.adnaik
 --- 
 # Azure Synapse Dedicated SQL Pool Connector for Apache Spark
