freshness118

Author: dagiro

articles/hdinsight/storm/apache-storm-develop-python-topology.md

@@ -2,34 +2,32 @@
 title: Apache Storm with Python components - Azure HDInsight 
 description: Learn how to create an Apache Storm topology that uses Python components in Azure HDInsight
 author: hrasheed-msft
+ms.author: hrasheed
 ms.reviewer: jasonh
-keywords: apache storm python
-
 ms.service: hdinsight
-ms.custom: hdinsightactive,hdiseo17may2017
 ms.topic: conceptual
-ms.date: 04/30/2018
-ms.author: hrasheed
-
+ms.custom: hdinsightactive,hdiseo17may2017
+ms.date: 12/16/2019
 ---
+
 # Develop Apache Storm topologies using Python on HDInsight
 
 Learn how to create an [Apache Storm](https://storm.apache.org/) topology that uses Python components. Apache Storm supports multiple languages, even allowing you to combine components from several languages in one topology. The [Flux](https://storm.apache.org/releases/current/flux.html) framework (introduced with Storm 0.10.0) allows you to easily create solutions that use Python components.
 
 > [!IMPORTANT]  
-> The information in this document was tested using Storm on HDInsight 3.6. 
-
-The code for this project is available at [https://github.com/Azure-Samples/hdinsight-python-storm-wordcount](https://github.com/Azure-Samples/hdinsight-python-storm-wordcount).
+> The information in this document was tested using Storm on HDInsight 3.6.
 
 ## Prerequisites
 
-* Python 2.7 or higher
+* An Apache Storm cluster on HDInsight. See [Create Apache Hadoop clusters using the Azure portal](../hdinsight-hadoop-create-linux-clusters-portal.md) and select **Storm** for **Cluster type**.
+
+* A local Storm development environment (Optional). A local Storm environment is only needed if you want to run the topology locally. For more information, see [Setting up a development environment](http://storm.apache.org/releases/current/Setting-up-development-environment.html).
 
-* Java JDK 1.8 or higher
+* [Python 2.7 or higher](https://www.python.org/downloads/).
 
-* [Apache Maven 3](https://maven.apache.org/download.cgi)
+* [Java Developer Kit (JDK) version 8](https://aka.ms/azure-jdks).
 
-* (Optional) A local Storm development environment. A local Storm environment is only needed if you want to run the topology locally. For more information, see [Setting up a development environment](http://storm.apache.org/releases/current/Setting-up-development-environment.html).
+* [Apache Maven](https://maven.apache.org/download.cgi) properly [installed](https://maven.apache.org/install.html) according to Apache.  Maven is a project build system for Java projects.
 
 ## Storm multi-language support
 
@@ -67,80 +65,79 @@ Flux expects the Python scripts to be in the `/resources` directory inside the j
 </resource>
 ```
 
-As mentioned earlier, there is a `storm.py` file that implements the Thrift definition for Storm. The Flux framework includes `storm.py` automatically when the project is built, so you don't have to worry about including it.
+As mentioned earlier, there's a `storm.py` file that implements the Thrift definition for Storm. The Flux framework includes `storm.py` automatically when the project is built, so you don't have to worry about including it.
 
 ## Build the project
 
-From the root of the project, use the following command:
-
-```bash
-mvn clean compile package
-```
-
-This command creates a `target/WordCount-1.0-SNAPSHOT.jar` file that contains the compiled topology.
-
-## Run the topology locally
+1. Download the project from [https://github.com/Azure-Samples/hdinsight-python-storm-wordcount](https://github.com/Azure-Samples/hdinsight-python-storm-wordcount).
 
-To run the topology locally, use the following command:
+1. Open a command prompt and navigate to the project root: `hdinsight-python-storm-wordcount-master`. Enter the following command:
 
-```bash
-storm jar WordCount-1.0-SNAPSHOT.jar org.apache.storm.flux.Flux -l -R /topology.yaml
-```
-
-> [!NOTE]  
-> This command requires a local Storm development environment. For more information, see [Setting up a development environment](https://storm.apache.org/releases/current/Setting-up-development-environment.html)
+    ```cmd
+    mvn clean compile package
+    ```
 
-Once the topology starts, it emits information to the local console similar to the following text:
+    This command creates a `target/WordCount-1.0-SNAPSHOT.jar` file that contains the compiled topology.
 
+## Run the Storm topology on HDInsight
 
-    24302 [Thread-25-sentence-spout-executor[4 4]] INFO  o.a.s.s.ShellSpout - ShellLog pid:2436, name:sentence-spout Emiting the cow jumped over the moon
-    24302 [Thread-30] INFO  o.a.s.t.ShellBolt - ShellLog pid:2438, name:splitter-bolt Emitting the
-    24302 [Thread-28] INFO  o.a.s.t.ShellBolt - ShellLog pid:2437, name:counter-bolt Emitting years:160
-    24302 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=the, count=599}
-    24303 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=seven, count=302}
-    24303 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=dwarfs, count=143}
-    24303 [Thread-25-sentence-spout-executor[4 4]] INFO  o.a.s.s.ShellSpout - ShellLog pid:2436, name:sentence-spout Emiting the cow jumped over the moon
-    24303 [Thread-30] INFO  o.a.s.t.ShellBolt - ShellLog pid:2438, name:splitter-bolt Emitting cow
-    24303 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=four, count=160}
+1. Use [ssh command](../hdinsight-hadoop-linux-use-ssh-unix.md) to copy the `WordCount-1.0-SNAPSHOT.jar` file to your Storm on HDInsight cluster. Edit the command below by replacing CLUSTERNAME with the name of your cluster, and then enter the command:
 
+    ```cmd
+    scp target/WordCount-1.0-SNAPSHOT.jar [email protected]:
+    ```
 
-To stop the topology, use __Ctrl + C__.
+1. Once the file has been uploaded, connect to the cluster using SSH:
 
-## Run the Storm topology on HDInsight
+    ```cmd
+    ssh [email protected]
+    ```
 
-1. Use the following command to copy the `WordCount-1.0-SNAPSHOT.jar` file to your Storm on HDInsight cluster:
+1. From the SSH session, use the following command to start the topology on the cluster:
 
     ```bash
-    scp target\WordCount-1.0-SNAPSHOT.jar [email protected]
+    storm jar WordCount-1.0-SNAPSHOT.jar org.apache.storm.flux.Flux -r -R /topology.yaml
     ```
 
-    Replace `sshuser` with the SSH user for your cluster. Replace `mycluster` with the cluster name. You may be prompted to enter the password for the SSH user.
+    Once started, a Storm topology runs until stopped.
 
-    For more information on using SSH and SCP, see [Use SSH with HDInsight](../hdinsight-hadoop-linux-use-ssh-unix.md).
+1. Use the Storm UI to view the topology on the cluster. The Storm UI is located at `https://CLUSTERNAME.azurehdinsight.net/stormui`. Replace `CLUSTERNAME` with your cluster name.
 
-2. Once the file has been uploaded, connect to the cluster using SSH:
+1. Stop the Storm topology. Use the following command to stop the topology on the cluster:
 
     ```bash
-    ssh [email protected]
+    storm kill wordcount
     ```
 
-3. From the SSH session, use the following command to start the topology on the cluster:
+    Alternatively, you can use the Storm UI. Under **Topology actions** for the topology, select **Kill**.
 
-    ```bash
-    storm jar WordCount-1.0-SNAPSHOT.jar org.apache.storm.flux.Flux -r -R /topology.yaml
-    ```
+## Run the topology locally
 
-3. You can use the Storm UI to view the topology on the cluster. The Storm UI is located at https://mycluster.azurehdinsight.net/stormui. Replace `mycluster` with your cluster name.
+To run the topology locally, use the following command:
+
+```bash
+storm jar WordCount-1.0-SNAPSHOT.jar org.apache.storm.flux.Flux -l -R /topology.yaml
+```
 
 > [!NOTE]  
-> Once started, a Storm topology runs until stopped. To stop the topology, use one of the following methods:
->
-> * The `storm kill TOPOLOGYNAME` command from the command line
-> * The **Kill** button in the Storm UI.
+> This command requires a local Storm development environment. For more information, see [Setting up a development environment](https://storm.apache.org/releases/current/Setting-up-development-environment.html).
 
+Once the topology starts, it emits information to the local console similar to the following text:
 
-## Next steps
+```output
+24302 [Thread-25-sentence-spout-executor[4 4]] INFO  o.a.s.s.ShellSpout - ShellLog pid:2436, name:sentence-spout Emiting the cow jumped over the moon
+24302 [Thread-30] INFO  o.a.s.t.ShellBolt - ShellLog pid:2438, name:splitter-bolt Emitting the
+24302 [Thread-28] INFO  o.a.s.t.ShellBolt - ShellLog pid:2437, name:counter-bolt Emitting years:160
+24302 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=the, count=599}
+24303 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=seven, count=302}
+24303 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=dwarfs, count=143}
+24303 [Thread-25-sentence-spout-executor[4 4]] INFO  o.a.s.s.ShellSpout - ShellLog pid:2436, name:sentence-spout Emiting the cow jumped over the moon
+24303 [Thread-30] INFO  o.a.s.t.ShellBolt - ShellLog pid:2438, name:splitter-bolt Emitting cow
+24303 [Thread-17-log-executor[3 3]] INFO  o.a.s.f.w.b.LogInfoBolt - {word=four, count=160}
+```
 
-See the following documents for other ways to use Python with HDInsight:
+To stop the topology, use __Ctrl + C__.
+
+## Next steps
 
-* [How to use Python User Defined Functions (UDF) in Apache Pig and Apache Hive](../hadoop/python-udf-hdinsight.md)
+See the following documents for other ways to use Python with HDInsight: [How to use Python User Defined Functions (UDF) in Apache Pig and Apache Hive](../hadoop/python-udf-hdinsight.md).