Merge pull request #86883 from anumjs/t46-releasenotes

T46 releasenotes

Author: PRMerger6

articles/sql-data-warehouse/release-notes-10-0-10106-0.md

@@ -5,7 +5,7 @@ services: sql-data-warehouse
 ms.service: sql-data-warehouse
 ms.topic: conceptual
 ms.subservice: 
-ms.date: 07/03/2019
+ms.date: 09/18/2019
 author: anumjs
 ms.author: anjangsh
 ms.reviewer: jrasnick
@@ -14,24 +14,34 @@ manager: craigg
 
 # Azure SQL Data Warehouse release notes
 
-This article summarizes the new features and improvements in the recent releases of [Azure SQL Data Warehouse](sql-data-warehouse-overview-what-is.md). The article also lists notable content updates that aren't directly related to the release but published in the same time frame. For improvements to other Azure services, see [Service updates](https://azure.microsoft.com/updates).
+This article summarizes the new features and improvements in the recent releases of [Azure SQL Data Warehouse](sql-data-warehouse-overview-what-is.md) (Azure SQL DW). The article also lists notable content updates that aren't directly related to the release but published in the same time frame. For improvements to other Azure services, see [Service updates](https://azure.microsoft.com/updates).
 
 ## Check your Azure SQL Data Warehouse version
 
-As new features are being rolled out to all regions, check the version deployed to your instance and the latest Azure SQL DW release notes for the feature availability. To check your Azure SQL DW version, connect to your data warehouse via SQL Server Management Studio (SSMS) and run `SELECT @@VERSION AS 'SQL Data Warehouse';` to return the current version of Azure SQL DW.
+As new features are rolled out to all regions, check the version deployed to your instance and the latest Azure SQL DW release notes for feature availability. To check your Azure SQL DW version, connect to your data warehouse via SQL Server Management Studio (SSMS) and run `SELECT @@VERSION;` to return the current version of Azure SQL DW.
 
 Example output:
 
 ![SQL Data Warehouse version](./media/release-notes/sql_data_warehouse_version.png)
 
 Use the date identified to confirm which release has been applied to your Azure SQL DW.
 
+## September 2019
+
+| Service improvements | Details |
+| --- | --- |
+|**Azure Private Link (Preview)**|With [Azure Private Link](https://azure.microsoft.com/blog/announcing-azure-private-link/), you can create a private endpoint in your Virtual Network (VNet) and map it to your Azure SQL DW. These resources are then accessible over a private IP address in your VNet, enabling connectivity from on-premises through Azure ExpressRoute private peering and/or VPN gateway. Overall, this simplifies the network configuration by not requiring you to open it up to public IP addresses. This also enables protection against data exfiltration risks. For more details, see [overview](/azure/private-link/private-link-overview) and [SQL DW documentation](/azure/sql-database/sql-database-private-endpoint-overview).|
+|**Data Discovery & Classification (GA)**|[Data discovery and classification](/azure/sql-database/sql-database-data-discovery-and-classification?toc=/azure/sql-data-warehouse/toc.json) feature is now Generally Available. This feature provides advanced capabilities for **discovering, classifying, labeling & protecting** sensitive data in your databases.|
+|**Azure Advisor one-click Integration**|SQL Data Warehouse now directly integrates with Azure Advisor recommendations in the overview blade along with providing a one-click experience. You can now discover recommendations in the overview blade instead of navigating to the Azure advisor blade. Find out more about recommendations [here](sql-data-warehouse-concept-recommendations.md).|
+|**EXECUTE AS (Transact-SQL)**| [EXECUTE AS](/sql/t-sql/statements/execute-as-transact-sql?view=azure-sqldw-latest) T-SQL support is now available in SQL Data Warehouse enabling customers to set the execution context of a session to the specified user.|
+|**Additional T-SQL support**|The T-SQL language surface area for SQL Data Warehouse has been extended to include support for: </br> - [FORMAT (Transact-SQL)](/sql/t-sql/functions/format-transact-sql?view=azure-sqldw-latest)</br> - [TRY_PARSE (Transact-SQL)](/sql/t-sql/functions/try-parse-transact-sql?view=azure-sqldw-latest)</br> - [TRY_CAST (Transact-SQL)](/sql/t-sql/functions/try-cast-transact-sql?view=azure-sqldw-latest)</br> - [TRY_CONVERT (Transact-SQL)](/sql/t-sql/functions/try-convert-transact-sql?view=azure-sqldw-latest)</br> - [sys.user_token (Transact-SQL)](/sql//relational-databases/system-catalog-views/sys-user-token-transact-sql?view=azure-sqldw-latest)|
+
 ## July 2019
 
 | Service improvements | Details |
 | --- | --- |
 |**Materialized View (Preview)**|A Materialized View persists the data returned from the view definition query and automatically gets updated as data changes in the underlying tables. It improves the performance of complex queries (typically queries with joins and aggregations) while offering simple maintenance operations. For more information, see: </br> - [CREATE MATERIALIZED VIEW AS SELECT &#40;Transact-SQL&#41;](/sql/t-sql/statements/create-materialized-view-as-select-transact-sql?view=azure-sqldw-latest)</br> - [ALTER MATERIALIZED VIEW &#40;Transact-SQL&#41;](/sql/t-sql/statements/alter-materialized-view-transact-sql?view=azure-sqldw-latest) </br> - [T-SQL statements supported in Azure SQL Data Warehouse](/azure/sql-data-warehouse/sql-data-warehouse-reference-tsql-statements)|
-|**Additional T-SQL support**|The T-SQL language surface area for SQL Data Warehouse has been extended to include support for: </br> - [AT TIME ZONE](/sql/t-sql/queries/at-time-zone-transact-sql?view=azure-sqldw-latest)</br> - [STRING_AGG](/sql/t-sql/functions/string-agg-transact-sql?view=azure-sqldw-latest)|
+|**Additional T-SQL support**|The T-SQL language surface area for SQL Data Warehouse has been extended to include support for: </br> - [AT TIME ZONE (Transact-SQL)](/sql/t-sql/queries/at-time-zone-transact-sql?view=azure-sqldw-latest)</br> - [STRING_AGG (Transact-SQL)](/sql/t-sql/functions/string-agg-transact-sql?view=azure-sqldw-latest)|
 |**Result set caching (Preview)**|DBCC commands added to manage the previously announced result set cache. For more information, see: </br> - [DBCC DROPRESULTSETCACHE &#40;Transact-SQL&#41;](/sql/t-sql/database-console-commands/dbcc-dropresultsetcache-transact-sql?view=azure-sqldw-latest)  </br> - [DBCC SHOWRESULTCACHESPACEUSED &#40;Transact-SQL&#41;](/sql/t-sql/database-console-commands/dbcc-showresultcachespaceused-transact-sql?view=azure-sqldw-latest) </br></br> Also see the new result_set_cache column in [sys.dm_pdw_exec_requests](/sql/relational-databases/system-dynamic-management-views/sys-dm-pdw-exec-requests-transact-sql?view=azure-sqldw-latest) that shows when an executed query used the result set cache.|
 |**Ordered clustered columnstore index (Preview)**|New column, column_store_order_ordinal, added to [sys.index_columns](/sql/relational-databases/system-catalog-views/sys-index-columns-transact-sql?view=azure-sqldw-latest) to identify the order of columns in an ordered clustered columnstore index.|
 
@@ -52,7 +62,7 @@ Use the date identified to confirm which release has been applied to your Azure
 | --- | --- |
 |**Data Discovery & Classification**|Data Discovery & Classification is now available in public preview for Azure SQL Data Warehouse. It’s critical to protect sensitive data and the privacy of your customers. As your business and customer data assets grow, it becomes unmanageable to discover, classify, and protect your data. The data discovery and classification feature that we’re introducing natively with Azure SQL Data Warehouse helps make protecting your data more manageable. The overall benefits of this capability are:<br/>&bull; &nbsp; Meeting data privacy standards and regulatory compliance requirements.<br/>&bull; &nbsp; Restricting access to and hardening the security of data warehouses containing highly sensitive data.<br/>&bull; &nbsp; Monitoring and alerting on anomalous access to sensitive data.<br/>&bull; &nbsp; Visualization of sensitive data in a central dashboard on the Azure portal. </br></br>Data Discovery & Classification is available for Azure SQL Data Warehouse in all Azure regions, It's part of Advanced Data Security including Vulnerability Assessment and Threat Detection. For more information about Data Discovery & Classification, see the [blog post](https://azure.microsoft.com/blog/announcing-public-preview-of-data-discovery-classification-for-microsoft-azure-sql-data-warehouse/) and our online [documentation](/azure/sql-database/sql-database-data-discovery-and-classification).|
 |**GROUP BY ROLLUP**|ROLLUP is now a supported GROUP BY option in Azure Data Warehouse.   GROUP BY ROLLUP creates a group for each combination of column expressions. GROUP BY also "rolls up" the results into subtotals and grand totals. The GROUP BY function processes from right to left, decreasing the number of column expressions over which it creates groups and aggregation(s).  The column order affects the ROLLUP output and can affect the number of rows in the result set.<br/><br/>For more information on GROUP BY ROLLUP, see  [GROUP BY (Transact-SQL)](/sql/t-sql/queries/select-group-by-transact-sql?view=azure-sqldw-latest)
-|**Improved accuracy for DWU used and CPU portal metrics**|SQL Data Warehouse significantly enhances metric accuracy in the Azure portal.  This release includes a fix to the CPU and DWU Used metric definition to properly reflect your workload across all compute nodes. Before this fix, metric values were being undereported. Expect to see an increase in the DWU used and CPU metrics in the Azure portal. |
+|**Improved accuracy for DWU used and CPU portal metrics**|SQL Data Warehouse significantly enhances metric accuracy in the Azure portal.  This release includes a fix to the CPU and DWU Used metric definition to properly reflect your workload across all compute nodes. Before this fix, metric values were being underreported. Expect to see an increase in the DWU used and CPU metrics in the Azure portal. |
 |**Row Level Security**|We introduced Row-level Security capability back in Nov 2017. We’ve now extended this support to external tables as well. Additionally, we’ve added support for calling non-deterministic functions in the inline table-valued functions (inline TVFs) required for defining a security filter predicate. This addition allows you to specify IS_ROLEMEMBER(), USER_NAME() etc. in the security filter predicate. For more information, please see the examples in the [Row-level Security documentation](/sql/relational-databases/security/row-level-security).|
 |**Additional T-SQL Support**|The T-SQL language surface area for SQL Data Warehouse has been extended to include support for [STRING_SPLIT (Transact-SQL)](/sql/t-sql/functions/string-split-transact-sql).
 |**Query Optimizer enhancements** |Query optimization is a critical component of any database. Making optimal choices on how to best execute a query can yield significant improvements.  When executing complex analytical queries in a distributed environment, the number of operations executed matters. Query performance has been enhanced by producing better quality plans. These plans minimize expensive data transfer operations and redundant computations such as, repeated subqueries. For more information, see this Azure SQL Data Warehouse [blog post](https://azure.microsoft.com/blog/smarter-faster-safer-azure-sql-data-warehouse-is-simply-unmatched/).|