Merge pull request #218693 from sreekzz/patch-124

Removed Storm contents

Author: prmerger-automator[bot]

articles/hdinsight/hadoop/apache-hadoop-linux-tutorial-get-started-bicep.md

@@ -6,7 +6,7 @@ ms.author: nijelsf
 ms.service: hdinsight
 ms.topic: quickstart
 ms.custom: subject-armqs, mode-arm
-ms.date: 07/18/2022
+ms.date: 11/17/2022
 #Customer intent: As a data analyst, I need to create a Hadoop cluster in Azure HDInsight using Bicep
 ---
 
@@ -57,7 +57,7 @@ Two Azure resources are defined in the Bicep file:
     You need to provide values for the parameters:
 
     * Replace **\<cluster-name\>** with the name of the HDInsight cluster to create.
-    * Replace **\<cluster-type\>** with the type of the HDInsight cluster to create. Allowed strings include: `hadoop`, `interactivehive`, `hbase`, `storm`, and `spark`.
+    * Replace **\<cluster-type\>** with the type of the HDInsight cluster to create. Allowed strings include: `hadoop`, `interactivehive`, `hbase`, and `spark`.
     * Replace **\<cluster-username\>** with the credentials used to submit jobs to the cluster and to log in to cluster dashboards.
     * Replace **\<ssh-username\>** with the credentials used to remotely access the cluster. The username cannot be admin.
 

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

@@ -4,7 +4,7 @@ description: Learn architecture best practices for migrating on-premises Hadoop
 ms.service: hdinsight
 ms.topic: how-to
 ms.custom: hdinsightactive
-ms.date: 07/18/2022
+ms.date: 11/17/2022
 ---
 
 # Migrate on-premises Apache Hadoop clusters to Azure HDInsight - architecture best practices
@@ -21,7 +21,7 @@ Azure HDInsight clusters are designed for a specific type of compute usage. Beca
 |---|---|
 |Batch processing (ETL / ELT)|Hadoop, Spark|
 |Data warehousing|Hadoop, Spark, Interactive Query|
-|IoT / Streaming|Kafka, Storm, Spark|
+|IoT / Streaming|Kafka, Spark|
 |NoSQL Transactional processing|HBase|
 |Interactive and Faster queries with in-memory caching|Interactive Query|
 |Data Science| Spark|

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

@@ -4,7 +4,7 @@ description: Learn the motivation and benefits for migrating on-premises Hadoop
 ms.service: hdinsight
 ms.custom: ignite-2022
 ms.topic: how-to
-ms.date: 04/28/2022
+ms.date: 11/17/2022
 ---
 
 # Migrate on-premises Apache Hadoop clusters to Azure HDInsight - motivation and benefits
@@ -19,9 +19,7 @@ Azure HDInsight is a cloud distribution of Hadoop components. Azure HDInsight ma
 - Apache Spark
 - Apache Hive with LLAP
 - Apache Kafka
-- Apache Storm
 - Apache HBase
-- R
 
 ## Azure HDInsight advantages over on-premises Hadoop
 
@@ -84,7 +82,7 @@ This section provides template questionnaires to help gather important informati
 |**Topic**: **Environment**|||
 |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|
+|Cluster types|Hadoop, Spark, Confluent Kafka, Solr|
 |Number of clusters|4|
 |Number of master nodes|2|
 |Number of worker nodes|100|

articles/hdinsight/hbase/apache-hbase-overview.md

@@ -4,7 +4,7 @@ description: An introduction to Apache HBase in HDInsight, a NoSQL database buil
 ms.service: hdinsight
 ms.topic: overview
 ms.custom: hdinsightactive,hdiseo17may2017,seoapr2020
-ms.date: 05/11/2022
+ms.date: 11/17/2022
 
 #Customer intent: As a developer new to Apache HBase and Apache HBase in Azure HDInsight, I want to have a basic understanding of Microsoft's implementation of Apache HBase in Azure HDInsight so I can decide if I want to use it rather than build my own cluster.
 ---
@@ -37,7 +37,7 @@ The canonical use case for which BigTable (and by extension, HBase) was created
 |Key-value store|HBase can be used as a key-value store, and it's suitable for managing message systems. Facebook uses HBase for their messaging system, and it's ideal for storing and managing Internet communications. WebTable uses HBase to search for and manage tables that are extracted from webpages.|
 |Sensor data|HBase is useful for capturing data that is collected incrementally from various sources. This data includes social analytics, and time series. And keeping interactive dashboards up to date with trends and counters, and managing audit log systems. Examples include Bloomberg trader terminal and the Open Time Series Database (OpenTSDB). OpenTSDB stores and provides access to metrics collected about the health of server systems.|
 |Real-time query|[Apache Phoenix](https://phoenix.apache.org/) is a SQL query engine for Apache HBase. It's accessed as a JDBC driver, and it enables querying and managing HBase tables by using SQL.|
-|HBase as a platform|Applications can run on top of HBase by using it as a datastore. Examples include Phoenix, OpenTSDB, `Kiji`, and Titan. Applications can also integrate with HBase. Examples include: [Apache Hive](https://hive.apache.org/), Apache Pig, [Solr](https://lucene.apache.org/solr/), Apache Storm, Apache Flume, [Apache Impala](https://impala.apache.org/), Apache Spark, `Ganglia`, and Apache Drill.|
+|HBase as a platform|Applications can run on top of HBase by using it as a datastore. Examples include Phoenix, OpenTSDB, `Kiji`, and Titan. Applications can also integrate with HBase. Examples include: [Apache Hive](https://hive.apache.org/), Apache Pig, [Solr](https://lucene.apache.org/solr/), Apache Flume, [Apache Impala](https://impala.apache.org/), Apache Spark, `Ganglia`, and Apache Drill.|
 
 ## Next steps
 

articles/hdinsight/hdinsight-administer-use-command-line.md

@@ -1,10 +1,10 @@
 ---
 title: Manage Azure HDInsight clusters using Azure CLI
-description: Learn how to use the Azure CLI to manage Azure HDInsight clusters. Cluster types include Apache Hadoop, Spark, HBase, Storm, Kafka, Interactive Query.
+description: Learn how to use the Azure CLI to manage Azure HDInsight clusters. Cluster types include Apache Hadoop, Spark, HBase, Kafka, Interactive Query.
 ms.service: hdinsight
 ms.topic: conceptual
 ms.custom: hdinsightactive,hdiseo17may2017, devx-track-azurecli
-ms.date: 06/16/2022
+ms.date: 11/17/2022
 ---
 
 # Manage Azure HDInsight clusters using Azure CLI

articles/hdinsight/kafka/apache-kafka-azure-container-services.md

@@ -4,7 +4,7 @@ description: Learn how to use Kafka on HDInsight from container images hosted in
 ms.service: hdinsight
 ms.topic: how-to
 ms.custom: hdinsightactive
-ms.date: 08/23/2022
+ms.date: 11/17/2022
 ---
 
 # Use Azure Kubernetes Service with Apache Kafka on HDInsight
@@ -224,7 +224,6 @@ Use the following links to learn how to use Apache Kafka on HDInsight:
 
 * [Use MirrorMaker to create a replica of Apache Kafka on HDInsight](apache-kafka-mirroring.md)
 
-* [Use Apache Storm with Apache Kafka on HDInsight](../hdinsight-apache-storm-with-kafka.md)
 
 * [Use Apache Spark with Apache Kafka on HDInsight](../hdinsight-apache-spark-with-kafka.md)
 

articles/hdinsight/kafka/apache-kafka-connector-iot-hub.md

@@ -5,7 +5,7 @@ description: Learn how to use Apache Kafka on HDInsight with Azure IoT Hub. The
 ms.service: hdinsight
 ms.topic: how-to
 ms.custom: hdinsightactive
-ms.date: 09/15/2022
+ms.date: 11/17/2022
 ---
 
 # Use Apache Kafka on HDInsight with Azure IoT Hub
@@ -352,4 +352,3 @@ For more information on using the sink connector, see [https://github.com/Azure/
 In this document, you learned how to use the Apache Kafka Connect API to start the IoT Kafka Connector on HDInsight. Use the following links to discover other ways to work with Kafka:
 
 * [Use Apache Spark with Apache Kafka on HDInsight](../hdinsight-apache-spark-with-kafka.md)
-* [Use Apache Storm with Apache Kafka on HDInsight](../hdinsight-apache-storm-with-kafka.md)

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

@@ -4,7 +4,7 @@ description: 'Learn about Apache Kafka on HDInsight: What it is, what it does, a
 ms.service: hdinsight
 ms.topic: overview
 ms.custom: hdinsightactive
-ms.date: 03/30/2022
+ms.date: 10/17/2022
 #Customer intent: As a developer, I want to understand how Kafka on HDInsight is different from Kafka on other platforms.
 ---
 
@@ -58,7 +58,7 @@ The following are common tasks and patterns that can be performed using Kafka on
 |---|---|
 |Replication of Apache Kafka data|Kafka provides the MirrorMaker utility, which replicates data between Kafka clusters. For information on using MirrorMaker, see [Replicate Apache Kafka topics with Apache Kafka on HDInsight](apache-kafka-mirroring.md).|
 |Publish-subscribe messaging pattern|Kafka provides a Producer API for publishing records to a Kafka topic. The Consumer API is used when subscribing to a topic. For more information, see [Start with Apache Kafka on HDInsight](apache-kafka-get-started.md).|
-|Stream processing|Kafka is often used with Apache Storm or Spark for real-time stream processing. Kafka 0.10.0.0 (HDInsight version 3.5 and 3.6) introduced a streaming API that allows you to build streaming solutions without requiring Storm or Spark. For more information, see [Start with Apache Kafka on HDInsight](apache-kafka-get-started.md).|
+|Stream processing|Kafka is often used with Spark for real-time stream processing. Kafka 0.10.0.0 (HDInsight version 3.5 and 3.6) introduced a streaming API that allows you to build streaming solutions without requiring Spark. For more information, see [Start with Apache Kafka on HDInsight](apache-kafka-get-started.md).|
 |Horizontal scale|Kafka partitions streams across the nodes in the HDInsight cluster. Consumer processes can be associated with individual partitions to provide load balancing when consuming records. For more information, see [Start with Apache Kafka on HDInsight](apache-kafka-get-started.md).|
 |In-order delivery|Within each partition, records are stored in the stream in the order that they were received. By associating one consumer process per partition, you can guarantee that records are processed in-order. For more information, see [Start with Apache Kafka on HDInsight](apache-kafka-get-started.md).|
 |Messaging|Since it supports the publish-subscribe message pattern, Kafka is often used as a message broker.|
@@ -76,4 +76,3 @@ Use the following links to learn how to use Apache Kafka on HDInsight:
 
 * [Tutorial: Use Apache Spark with Apache Kafka on HDInsight](../hdinsight-apache-spark-with-kafka.md)
 
-* [Tutorial: Use Apache Storm with Apache Kafka on HDInsight](../hdinsight-apache-storm-with-kafka.md)

articles/hdinsight/kafka/apache-kafka-scalability.md

@@ -45,7 +45,6 @@ To control the number of disks used by the worker nodes in a Kafka cluster, use
 For more information on working with Apache Kafka on HDInsight, see the following documents:
 
 * [Use MirrorMaker to create a replica of Apache Kafka on HDInsight](apache-kafka-mirroring.md)
-* [Use Apache Storm with Apache Kafka on HDInsight](../hdinsight-apache-storm-with-kafka.md)
 * [Use Apache Spark with Apache Kafka on HDInsight](../hdinsight-apache-spark-with-kafka.md)
 * [Connect to Apache Kafka through an Azure Virtual Network](apache-kafka-connect-vpn-gateway.md)
 

articles/hdinsight/kafka/apache-kafka-streams-api.md

@@ -4,7 +4,7 @@ description: Tutorial - Learn how to use the Apache Kafka Streams API with Kafka
 ms.service: hdinsight
 ms.topic: tutorial
 ms.custom: hdinsightactive
-ms.date: 08/23/2022
+ms.date: 11/17/2022
 #Customer intent: As a developer, I need to create an application that uses the Kafka streams API with Kafka on HDInsight
 ---
 
@@ -14,7 +14,7 @@ Learn how to create an application that uses the Apache Kafka Streams API and ru
 
 The application used in this tutorial is a streaming word count. It reads text data from a Kafka topic, extracts individual words, and then stores the word and count into another Kafka topic.
 
-Kafka stream processing is often done using Apache Spark or Apache Storm. Kafka version 1.1.0 (in HDInsight 3.5 and 3.6) introduced the Kafka Streams API. This API allows you to transform data streams between input and output topics. In some cases, this may be an alternative to creating a Spark or Storm streaming solution.
+Kafka stream processing is often done using Apache Spark. Kafka version 1.1.0 (in HDInsight 3.5 and 3.6) introduced the Kafka Streams API. This API allows you to transform data streams between input and output topics. 
 
 For more information on Kafka Streams, see the [Intro to Streams](https://kafka.apache.org/10/documentation/streams/) documentation on Apache.org.