Merge pull request #223841 from whhender/retirement-flag

Retirement flag

Author: v-stsavell

articles/data-lake-analytics/data-lake-analytics-account-policies.md

@@ -8,11 +8,15 @@ ms.date: 04/30/2018
 ---
 # Manage Azure Data Lake Analytics using Account Policies
 
-Account policies help you control how resources an Azure Data Lake Analytics account are used. These policies allow you to control the cost of using Azure Data Lake Analytics. For example, with these policies you can prevent unexpected cost spikes by limiting how many AUs the account can simultaneously use.## Account-level policies
+Account policies help you control how resources an Azure Data Lake Analytics account are used. These policies allow you to control the cost of using Azure Data Lake Analytics. For example, with these policies you can prevent unexpected cost spikes by limiting how many AUs the account can simultaneously use.
+
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
+## Account-level policies
 
 These policies apply to all jobs in a Data Lake Analytics account.
 
-## Maximum number of AUs in a Data Lake Analytics account
+### Maximum number of AUs in a Data Lake Analytics account
 
 A policy controls the total number of Analytics Units (AUs) your Data Lake Analytics account can use. By default, the value is set to 250. For example, if this value is set to 250 AUs, you can have one job running with 250 AUs assigned to it, or 10 jobs running with 25 AUs each. Additional jobs that are submitted are queued until the running jobs are finished. When running jobs are finished, AUs are freed up for the queued jobs to run.
 
@@ -26,7 +30,7 @@ To change the number of AUs for your Data Lake Analytics account:
    > [!NOTE]
    > If you need more than the default (250) AUs, in the portal, click **Help+Support** to submit a support request. The number of AUs available in your Data Lake Analytics account can be increased.
 
-## Maximum number of jobs that can run simultaneously
+### Maximum number of jobs that can run simultaneously
 
 This policy limits how many jobs can run simultaneously. By default, this value is set to 20. If your Data Lake Analytics has AUs available, new jobs are scheduled to run immediately until the total number of running jobs reaches the value of this policy. When you reach the maximum number of jobs that can run simultaneously, subsequent jobs are queued in priority order until one or more running jobs complete (depending on available AUs).
 
@@ -40,7 +44,7 @@ To change the number of jobs that can run simultaneously:
    > [!NOTE]
    > If you need to run more than the default (20) number of jobs, in the portal, click **Help+Support** to submit a support request. The number of jobs that can run simultaneously in your Data Lake Analytics account can be increased.
 
-## How long to keep job metadata and resources
+### How long to keep job metadata and resources
 
 When your users run U-SQL jobs, the Data Lake Analytics service keeps all related files. These files include the U-SQL script, the DLL files referenced in the U-SQL script, compiled resources, and statistics. The files are in the /system/ folder of the default Azure Data Lake Storage account. This policy controls how long these resources are stored before they are automatically deleted (the default is 30 days). You can use these files for debugging, and for performance-tuning of jobs that you'll rerun in the future.
 

articles/data-lake-analytics/data-lake-analytics-add-users.md

@@ -9,6 +9,8 @@ ms.date: 05/24/2018
 
 # Adding a user in the Azure portal
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 ## Start the Add User Wizard
 1. Open your Azure Data Lake Analytics via https://portal.azure.com.
 2. Click **Add User Wizard**.

articles/data-lake-analytics/data-lake-analytics-analyze-weblogs.md

@@ -9,6 +9,8 @@ ms.date: 12/05/2016
 # Analyze Website logs using Azure Data Lake Analytics
 Learn how to analyze website logs using Data Lake Analytics, especially on finding out which referrers ran into errors when they tried to visit the website.
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 ## Prerequisites
 * **Visual Studio 2015 or Visual Studio 2013**.
 * **[Data Lake Tools for Visual Studio](https://aka.ms/adltoolsvs)**.

articles/data-lake-analytics/data-lake-analytics-cicd-manage-assemblies.md

@@ -10,6 +10,8 @@ ms.date: 10/30/2018
 
 In this article, you learn how to manage U-SQL assembly source code with the newly introduced U-SQL database project. You also learn how to set up a continuous integration and deployment (CI/CD) pipeline for assembly registration by using Azure DevOps.
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 ## Use the U-SQL database project to manage assembly source code
 
 [The U-SQL database project](data-lake-analytics-data-lake-tools-develop-usql-database.md) is a project type in Visual Studio that helps developers develop, manage, and deploy their U-SQL databases quickly and easily. You can manage all U-SQL database objects (except for credentials) with the U-SQL database project.

articles/data-lake-analytics/data-lake-analytics-cicd-overview.md

@@ -10,6 +10,8 @@ ms.custom: devx-track-azurepowershell
 
 In this article, you learn how to set up a continuous integration and deployment (CI/CD) pipeline for U-SQL jobs and U-SQL databases.  
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 [!INCLUDE [updated-for-az](../../includes/updated-for-az.md)]
 
 ## Use CI/CD for U-SQL jobs

articles/data-lake-analytics/data-lake-analytics-cicd-test.md

@@ -9,6 +9,8 @@ ms.date: 08/30/2019
 
 Azure Data Lake provides the [U-SQL](data-lake-analytics-u-sql-get-started.md) language. U-SQL combines declarative SQL with imperative C# to process data at any scale. In this document, you learn how to create test cases for U-SQL and extended C# user-defined operator (UDO) code.
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 ## Test U-SQL scripts
 
 The U-SQL script is compiled and optimized for executable code to run in Azure or on your local computer. The compilation and optimization process treats the entire U-SQL script as a whole. You can't do a traditional unit test for every statement. However, by using the U-SQL test SDK and the local run SDK, you can do script-level tests.

articles/data-lake-analytics/data-lake-analytics-data-lake-tools-data-skew-solutions.md

@@ -9,6 +9,8 @@ ms.date: 12/16/2016
 
 # Resolve data-skew problems by using Azure Data Lake Tools for Visual Studio
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 ## What is data skew?
 
 Briefly stated, data skew is an over-represented value. Imagine that you have assigned 50 tax examiners to audit tax returns, one examiner for each US state. The Wyoming examiner, because the population there is small, has little to do. In California, however, the examiner is kept very busy because of the state's large population.

articles/data-lake-analytics/data-lake-analytics-data-lake-tools-debug-recurring-job.md

@@ -9,6 +9,8 @@ ms.date: 05/20/2018
 
 # Troubleshoot an abnormal recurring job
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 This article shows how to use [Azure Data Lake Tools for Visual Studio](https://aka.ms/adltoolsvs) to troubleshoot problems with recurring jobs. Learn more about pipeline and recurring jobs from the [Azure Data Lake and Azure HDInsight blog](/archive/blogs/azuredatalake/managing-pipeline-recurring-jobs-in-azure-data-lake-analytics-made-easy).
 
 Recurring jobs usually share the same query logic and similar input data. For example, imagine that you have a recurring job running every Monday morning at 8 A.M. to count last week’s weekly active user. The scripts for these jobs share one script template that contains the query logic. The inputs for these jobs are the usage data for last week. Sharing the same query logic and similar input usually means that performance of these jobs is similar and stable. If one of your recurring jobs suddenly performs abnormally, fails, or slows down a lot, you might want to:

articles/data-lake-analytics/data-lake-analytics-data-lake-tools-develop-usql-database.md

@@ -10,6 +10,8 @@ ms.date: 07/03/2018
 ---
 # Use a U-SQL database project to develop a U-SQL database for Azure Data Lake
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 U-SQL database provides structured views over unstructured data and managed structured data in tables. It also provides a general metadata catalog system for organizing your structured data and custom code. The database is the concept that groups these related objects together.
 
 Learn more about [U-SQL database and Data Definition Language (DDL)](/u-sql/data-definition-language-ddl-statements).

articles/data-lake-analytics/data-lake-analytics-data-lake-tools-export-database.md

@@ -9,6 +9,8 @@ ms.date: 11/27/2017
 
 # Export a U-SQL database
 
+[!INCLUDE [retirement-flag](includes/retirement-flag.md)]
+
 In this article, learn how to use [Azure Data Lake Tools for Visual Studio](https://aka.ms/adltoolsvs) to export a U-SQL database as a single U-SQL script and downloaded resources. You can import the exported database to a local account in the same process.
 
 Customers usually maintain multiple environments for development, test, and production. These environments are hosted on both a local account, on a developer's local computer, and in an Azure Data Lake Analytics account in Azure.