Merge pull request #79422 from hrasheed-msft/hdi_hdp_cleanup2

HDInsight remove hortonworks mentions

Author: Ja-Dunn

.openpublishing.redirection.json

@@ -39543,6 +39543,11 @@
       "redirect_url": "/azure/hdinsight/",
       "redirect_document_id": true
     },
+    {
+      "source_path": "articles/hdinsight/hdinsight-migrate-from-windows-to-linux.md",
+      "redirect_url": "/azure/hdinsight/",
+      "redirect_document_id": true
+    },
     {
       "source_path" : "articles/active-directory-domain-services/active-directory-ds-troubleshoot-service-principals.md",
       "redirect_url" : "/azure/active-directory-domain-services/alert-service-principal",

articles/hdinsight/domain-joined/apache-domain-joined-introduction.md

@@ -16,7 +16,7 @@ In the past, Azure HDInsight supported only a single user: local admin. This wor
 
 You can create an HDInsight cluster with Enterprise Security Package (ESP) that's joined to an Active Directory domain. You can then configure a list of employees from the enterprise who can authenticate through Azure Active Directory to sign in to the HDInsight cluster. No one from outside the enterprise can sign in or access the HDInsight cluster. 
 
-The enterprise admin can configure role-based access control (RBAC) for Apache Hive security by using [Apache Ranger](https://hortonworks.com/apache/ranger/). Configuring RBAC restricts data access to only what's needed. Finally, the admin can audit the data access by employees and any changes done to access control policies. The admin can then achieve a high degree of governance of their corporate resources.
+The enterprise admin can configure role-based access control (RBAC) for Apache Hive security by using [Apache Ranger](https://ranger.apache.org/). Configuring RBAC restricts data access to only what's needed. Finally, the admin can audit the data access by employees and any changes done to access control policies. The admin can then achieve a high degree of governance of their corporate resources.
 
 > [!NOTE]  
 > Apache Oozie is now enabled on ESP clusters. To access the Oozie web UI, users should enable [tunneling](../hdinsight-linux-ambari-ssh-tunnel.md).
@@ -38,14 +38,14 @@ With this setup, enterprise employees can sign in to the cluster nodes by using
 ## Authorization
 A best practice that most enterprises follow is making sure that not every employee has access to all enterprise resources. Likewise, the admin can define role-based access control policies for the cluster resources. 
 
-For example, the admin can configure [Apache Ranger](https://hortonworks.com/apache/ranger/) to set access control policies for Hive. This functionality ensures that employees can access only as much data as they need to be successful in their jobs. SSH access to the cluster is also restricted to only the administrator.
+For example, the admin can configure [Apache Ranger](https://ranger.apache.org/) to set access control policies for Hive. This functionality ensures that employees can access only as much data as they need to be successful in their jobs. SSH access to the cluster is also restricted to only the administrator.
 
 ## Auditing
 Auditing of all access to the cluster resources, and the data, is necessary to track unauthorized or unintentional access of the resources. It's as important as protecting the HDInsight cluster resources from unauthorized users and securing the data. 
 
 The admin can view and report all access to the HDInsight cluster resources and data. The admin can also view and report all changes to the access control policies created in Apache Ranger supported endpoints. 
 
-A HDInsight cluster with ESP uses the familiar Apache Ranger UI to search audit logs. On the back end, Ranger uses [Apache Solr](https://hortonworks.com/apache/solr/) for storing and searching the logs.
+A HDInsight cluster with ESP uses the familiar Apache Ranger UI to search audit logs. On the back end, Ranger uses [Apache Solr](http://lucene.apache.org/solr/) for storing and searching the logs.
 
 ## Encryption
 Protecting data is important for meeting organizational security and compliance requirements. Along with restricting access to data from unauthorized employees, you should encrypt it. 

articles/hdinsight/hadoop/TOC.yml

@@ -471,9 +471,6 @@
   items:
   - name: Windows clusters
     items:
-    - name: Migrate Windows clusters to Linux clusters
-      href: ../hdinsight-migrate-from-windows-to-linux.md
-      maintainContext: true
     - name: Migrate .NET solutions to Linux clusters
       href: ../hdinsight-hadoop-migrate-dotnet-to-linux.md
       maintainContext: true

articles/hdinsight/hadoop/apache-hadoop-introduction.md

@@ -21,7 +21,7 @@ This article provides an introduction to Apache Hadoop on Azure HDInsight. Azure
 [Apache Hadoop](https://hadoop.apache.org/) was the original open-source framework for distributed processing and analysis of big data sets on clusters. The Hadoop technology stack includes related software and utilities, including Apache Hive, Apache HBase, Spark, Kafka, and many others.
 
 
-Azure HDInsight is a cloud distribution of the Hadoop components from the [Hortonworks Data Platform (HDP)](https://hortonworks.com/products/data-center/hdp/). Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data. You can use the most popular open-source frameworks such as Hadoop, Spark, Hive, LLAP, Kafka, Storm, R, and more. With these frameworks, you can enable a broad range of scenarios such as extract, transform, and load (ETL), data warehousing, machine learning, and IoT.
+Azure HDInsight is a cloud distribution of Hadoop components. Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data. You can use the most popular open-source frameworks such as Hadoop, Spark, Hive, LLAP, Kafka, Storm, R, and more. With these frameworks, you can enable a broad range of scenarios such as extract, transform, and load (ETL), data warehousing, machine learning, and IoT.
 
 To see available Hadoop technology stack components on HDInsight, see [Components and versions available with HDInsight](../hdinsight-component-versioning.md). To read more about Hadoop in HDInsight, see the [Azure features page for HDInsight](https://azure.microsoft.com/services/hdinsight/).
 

articles/hdinsight/hadoop/apache-hadoop-on-premises-migration-best-practices-infrastructure.md

@@ -31,7 +31,7 @@ See [Default node configuration and virtual machine sizes for clusters](../hdins
 
 ## Check Hadoop components availability in HDInsight
 
-Each HDInsight version is a cloud distribution of a version of Hortonworks Data Platform (HDP) and consists of a set of Hadoop eco-system components. See [HDInsight Component Versioning](../hdinsight-component-versioning.md) for details on all HDInsight components and their current versions.
+Each HDInsight version is a cloud distribution of a set of Hadoop eco-system components. See [HDInsight Component Versioning](../hdinsight-component-versioning.md) for details on all HDInsight components and their current versions.
 
 You can also use Apache Ambari UI or Ambari REST API to check the Hadoop components and versions in HDInsight.
 

articles/hdinsight/hadoop/apache-hadoop-on-premises-migration-motivation.md

@@ -15,7 +15,7 @@ This article is the first in a series on best-practices for migrating on-premise
 
 ## Why to migrate to Azure HDInsight
 
-Azure HDInsight is a cloud distribution of the Hadoop components from the [Hortonworks Data Platform(HDP)](https://hortonworks.com/products/data-center/hdp/). Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data. HDInsight includes the most popular open-source frameworks such as:
+Azure HDInsight is a cloud distribution of Hadoop components. Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data. HDInsight includes the most popular open-source frameworks such as:
 
 - Apache Hadoop
 - Apache Spark
@@ -84,14 +84,13 @@ This section provides template questionnaires to help gather important informati
 | **Question** | **Example** | **Answer** |
 |---|---|---|
 |**Topic**: **Environment**|||
-|Cluster Distribution type|Hortonworks, Cloudera, MapR| |
 |Cluster Distribution version|HDP 2.6.5, CDH 5.7|
 |Big Data eco-system components|HDFS, Yarn, Hive, LLAP, Impala, Kudu, HBase, Spark, MapReduce, Kafka, Zookeeper, Solr, Sqoop, Oozie, Ranger, Atlas, Falcon, Zeppelin, R|
 |Cluster types|Hadoop, Spark, Confluent Kafka, Storm, Solr|
 |Number of clusters|4|
-|Number of Master Nodes|2|
-|Number of Worker Nodes|100|
-|Number of Edge Nodes| 5|
+|Number of master nodes|2|
+|Number of worker nodes|100|
+|Number of edge nodes| 5|
 |Total Disk space|100 TB|
 |Master Node configuration|m/y, cpu, disk, etc.|
 |Data Nodes configuration|m/y, cpu, disk, etc.|
@@ -193,7 +192,6 @@ This section provides template questionnaires to help gather important informati
 |Share metastores between different clusters?|Yes||
 |Deconstruct workloads?|Replace Hive jobs with Spark jobs||
 |Use ADF for data orchestration?|No||
-|HDInsight vs Hortonworks Data Platform on IaaS?|HDInsight||
 
 ## Next steps
 

articles/hdinsight/hbase/TOC.yml

@@ -264,7 +264,5 @@
   items:
   - name: Windows clusters
     items:
-    - name: Migrate Windows clusters to Linux clusters
-      href: ../hdinsight-migrate-from-windows-to-linux.md
     - name: Migrate .NET solutions to Linux clusters
       href: ../hdinsight-hadoop-migrate-dotnet-to-linux.md

articles/hdinsight/hdinsight-component-versioning.md

@@ -15,8 +15,6 @@ ms.date: 06/07/2019
 
 Learn about the [Apache Hadoop](https://hadoop.apache.org/) ecosystem components and versions in Microsoft Azure HDInsight, as well as the Enterprise Security Package. Also, learn how to check Hadoop component versions in HDInsight.
 
-Each HDInsight version is a cloud distribution of a version of Hortonworks Data Platform (HDP).
-
 ## Apache Hadoop components available with different HDInsight versions
 
 Azure HDInsight supports multiple Hadoop cluster versions that can be deployed at any time. Each version choice creates a specific version of the HDP distribution and a set of components that are contained within that distribution. As of April 4, 2017, the default cluster version used by Azure HDInsight is 3.6 and is based on HDP 2.6.
@@ -143,7 +141,7 @@ For information on pricing and SLA for the Enterprise Security Package, see [HDI
 
 ## Service level agreement for HDInsight cluster versions
 
-The service level agreement (SLA) is defined in terms of a _support window_. The support window is the period of time that an HDInsight cluster version is supported by Microsoft Customer Service and Support. If the version has a _support expiration date_ that has passed, the HDInsight cluster is outside the support window. For more information about supported versions, see the list of [supported HDInsight cluster versions](hdinsight-migrate-from-windows-to-linux.md). The support expiration date for a specified HDInsight version X (after a newer X+1 version is available) is calculated as the later of:  
+The service level agreement (SLA) is defined in terms of a _support window_. The support window is the period of time that an HDInsight cluster version is supported by Microsoft Customer Service and Support. If the version has a _support expiration date_ that has passed, the HDInsight cluster is outside the support window. The support expiration date for a specified HDInsight version X (after a newer X+1 version is available) is calculated as the later of:  
 
 * Formula 1: Add 180 days to the date when the HDInsight cluster version X was released.
 * Formula 2: Add 90 days to the date when the HDInsight cluster version X+1 is made available in Azure portal.

articles/hdinsight/hdinsight-hadoop-access-yarn-app-logs-linux.md

@@ -30,9 +30,9 @@ YARN Timeline Server includes the following type of data:
 
 YARN supports multiple programming models ([Apache Hadoop MapReduce](https://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html)  being one of them) by decoupling resource management from application scheduling/monitoring. YARN uses a global *ResourceManager* (RM), per-worker-node *NodeManagers* (NMs), and per-application *ApplicationMasters* (AMs). The per-application AM negotiates resources (CPU, memory, disk, network) for running your application with the RM. The RM works with NMs to grant these resources, which are granted as *containers*. The AM is responsible for tracking the progress of the containers assigned to it by the RM. An application may require many containers depending on the nature of the application.
 
-Each application may consist of multiple *application attempts*. If an application fails, it may be retried as a new attempt. Each attempt runs in a container. In a sense, a container provides the context for basic unit of work performed by a YARN application. All work that is done within the context of a container is performed on the single worker node on which the container was allocated. See [Apache Hadoop YARN Concepts][YARN-concepts] for further reference.
+Each application may consist of multiple *application attempts*. If an application fails, it may be retried as a new attempt. Each attempt runs in a container. In a sense, a container provides the context for basic unit of work performed by a YARN application. All work that is done within the context of a container is performed on the single worker node on which the container was allocated. See [Apache Hadoop YARN Concepts](https://hadoop.apache.org/docs/r2.7.4/hadoop-yarn/hadoop-yarn-site/WritingYarnApplications.html) for further reference.
 
-Application logs (and the associated container logs) are critical in debugging problematic Hadoop applications. YARN provides a nice framework for collecting, aggregating, and storing application logs with the [Log Aggregation][log-aggregation] feature. The Log Aggregation feature makes accessing application logs more deterministic. It aggregates logs across all containers on a worker node and stores them as one aggregated log file per worker node. The log is stored on the default file system after an application finishes. Your application may use hundreds or thousands of containers, but logs for all containers run on a single worker node are always aggregated to a single file. So there is only 1 log per worker node used by your application. Log Aggregation is enabled by default on HDInsight clusters version 3.0 and above. Aggregated logs are located in default storage for the cluster. The following path is the HDFS path to the logs:
+Application logs (and the associated container logs) are critical in debugging problematic Hadoop applications. YARN provides a nice framework for collecting, aggregating, and storing application logs with the [Log Aggregation](https://hortonworks.com/blog/simplifying-user-logs-management-and-access-in-yarn/) feature. The Log Aggregation feature makes accessing application logs more deterministic. It aggregates logs across all containers on a worker node and stores them as one aggregated log file per worker node. The log is stored on the default file system after an application finishes. Your application may use hundreds or thousands of containers, but logs for all containers run on a single worker node are always aggregated to a single file. So there is only 1 log per worker node used by your application. Log Aggregation is enabled by default on HDInsight clusters version 3.0 and above. Aggregated logs are located in default storage for the cluster. The following path is the HDFS path to the logs:
 
     /app-logs/<user>/logs/<applicationId>
 
@@ -66,7 +66,5 @@ The YARN ResourceManager UI runs on the cluster headnode. It is accessed through
     You are presented with a list of links to YARN logs.
 
 [YARN-timeline-server]:https://hadoop.apache.org/docs/r2.4.0/hadoop-yarn/hadoop-yarn-site/TimelineServer.html
-[log-aggregation]:https://hortonworks.com/blog/simplifying-user-logs-management-and-access-in-yarn/
 [T-file]:https://issues.apache.org/jira/secure/attachment/12396286/TFile%20Specification%2020081217.pdf
 [binary-format]:https://issues.apache.org/jira/browse/HADOOP-3315
-[YARN-concepts]:https://hortonworks.com/blog/apache-hadoop-yarn-concepts-and-applications/

articles/hdinsight/hdinsight-hadoop-linux-information.md

@@ -280,7 +280,6 @@ To use a different version of a component, upload the version you need and use i
 
 ## Next steps
 
-* [Migrate from Windows-based HDInsight to Linux-based](hdinsight-migrate-from-windows-to-linux.md)
 * [Manage HDInsight clusters by using the Apache Ambari REST API](./hdinsight-hadoop-manage-ambari-rest-api.md)
 * [Use Apache Hive with HDInsight](hadoop/hdinsight-use-hive.md)
 * [Use Apache Pig with HDInsight](hadoop/hdinsight-use-pig.md)