From e993b807c259c56ca67242d109d072685e532d84 Mon Sep 17 00:00:00 2001 From: Pam Lahoud Date: Sun, 3 Nov 2019 13:23:46 -0800 Subject: [PATCH] Updating a few links. --- samples/features/sql2019notebooks/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/samples/features/sql2019notebooks/README.md b/samples/features/sql2019notebooks/README.md index f7405f2780..749ab7a0b1 100644 --- a/samples/features/sql2019notebooks/README.md +++ b/samples/features/sql2019notebooks/README.md @@ -1,7 +1,7 @@ # SQL Server 2019 Feature Notebooks In this folder, you will find various notebooks that you can use in [Azure Data Studio](https://docs.microsoft.com/sql/azure-data-studio/what-is) to guide you through the new features of SQL Server 2019. -The [What's New](https://docs.microsoft.com/en-us/sql/sql-server/what-s-new-in-sql-server-ver15?view=sql-server-ver15) article covers all the *NEW* features in SQL Server 2019. +The [What's New](https://docs.microsoft.com/sql/sql-server/what-s-new-in-sql-server-ver15) article covers all the *NEW* features in SQL Server 2019. ## Notebook List ### Intelligent Query Processing @@ -18,12 +18,12 @@ The [What's New](https://docs.microsoft.com/en-us/sql/sql-server/what-s-new-in-s * **[MemoryOptmizedTempDBMetadata-Python.ipynb](https://github.com/microsoft/sql-server-samples/blob/master/samples/features/in-memory-database/memory-optimized-tempdb-metadata/MemoryOptmizedTempDBMetadata-Python.ipynb)** - This is a Python notebook which shows the benefits of Memory Optimized Tempdb metadata. ### Availability -* **[Basic_ADR.ipynb](https://github.com/microsoft/sql-server-samples/blob/master/samples/features/accelerated-database-recovery/basic_adr.ipynb)** - In this notebook, you will see how fast rollback can now be with Accelerated Database Recovery. You will also see that a long active transaction does not affect the ability to truncate the transaction log. +* **[Basic_ADR.ipynb](https://github.com/microsoft/sql-server-samples/blob/master/samples/features/accelerated-database-recovery/basic_adr.ipynb)** - In this notebook, you will see how fast long-running transaction rollback can now be with Accelerated Database Recovery. You will also see that a long active transaction does not affect the ability to truncate the transaction log. * **[Recovery_ADR.ipynb](https://github.com/microsoft/sql-server-samples/blob/master/samples/features/accelerated-database-recovery/recovery_adr.ipynb)** - In this example, you will see how Accelerated Database Recovery will speed up recovery. ### Big Data, Machine Learning & Data Virtualization * **[SQL Server Big Data Clusters](https://github.com/microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters/SQL2019BDC/notebooks)** - Part of our **[Ground to Cloud](https://aka.ms/sqlworkshops)** workshop. In this lab, you will use notebooks to experiment with SQL Server Big Data Clusters (BDC), and learn how you can use it to implement large-scale data processing and machine learning. -* **[Data Virtualization using PolyBase](https://github.com/microsoft/sqlworkshops/tree/master/sql2019workshop/sql2019wks/08_DataVirtualization/sqldatahub)** - The notebooks in this SQL Server 2019 workshop covers how to use SQL Server as a hub for data virtualization for sources like Oracle, SAP HANA, Azure CosmosDB, SQL Server and Azure SQL Database. +* **[Data Virtualization using PolyBase](https://github.com/microsoft/sqlworkshops/tree/master/sql2019workshop/sql2019wks/08_DataVirtualization/sqldatahub)** - The notebooks in this SQL Server 2019 workshop cover how to use SQL Server as a hub for data virtualization for sources like [Oracle](https://github.com/microsoft/sqlworkshops/tree/master/sql2019lab/04_DataVirtualization/sqldatahub/oracle), [SAP HANA](https://github.com/microsoft/sqlworkshops/tree/master/sql2019lab/04_DataVirtualization/sqldatahub/saphana), [Azure CosmosDB](https://github.com/microsoft/sqlworkshops/tree/master/sql2019lab/04_DataVirtualization/sqldatahub/cosmosdb), [SQL Server](https://github.com/microsoft/sqlworkshops/tree/master/sql2019lab/04_DataVirtualization/sqldatahub/sql2008r2) and [Azure SQL Database](https://github.com/microsoft/sqlworkshops/tree/master/sql2019lab/04_DataVirtualization/sqldatahub/azuredb). * **[Spark with Big Data Clusters](https://github.com/microsoft/sql-server-samples/tree/master/samples/features/sql-big-data-cluster/spark)** - The notebooks in this folder cover the following scenarios: * Data Loading - Transforming CSV to Parquet