Merge pull request #57319 from kkampf/patch-10

Reviewed and updated wording

Author: PRMerger9

articles/hdinsight/spark/apache-spark-python-package-installation.md

@@ -8,7 +8,7 @@ ms.reviewer: jasonh
 ms.service: hdinsight
 ms.custom: hdinsightactive
 ms.topic: conceptual
-ms.date: 01/09/2018
+ms.date: 11/06/2018
 ms.author: hrasheed
 
 ---
@@ -28,7 +28,7 @@ Learn how to use Script Actions to configure an Apache Spark cluster on HDInsigh
 
 You can search the [package index](https://pypi.python.org/pypi) for the complete list of packages that are available. You can also get a list of available packages from other sources. For example, you can install packages made available through [Anaconda](https://docs.continuum.io/anaconda/pkg-docs) or [conda-forge](https://conda-forge.org/feedstocks/).
 
-In this article, you learn how to install the [TensorFlow](https://www.tensorflow.org/) package using Script Action on your cluster and use it via the Jupyter notebook.
+In this article, you learn how to install the [TensorFlow](https://www.tensorflow.org/) package using Script Action on your cluster and use it via the Jupyter notebook as an example.
 
 ## Prerequisites
 You must have the following:
@@ -40,12 +40,27 @@ You must have the following:
    > If you do not already have a Spark cluster on HDInsight Linux, you can run script actions during cluster creation. Visit the documentation on [how to use custom script actions](https://docs.microsoft.com/azure/hdinsight/hdinsight-hadoop-customize-cluster-linux).
    > 
    > 
+   
+   ## Support for open-source software used on HDInsight clusters
+
+The Microsoft Azure HDInsight service uses an ecosystem of open-source technologies formed around Hadoop. Microsoft Azure provides a general level of support for open-source technologies. For more information, see the **Support Scope** section of the [Azure Support FAQ website](https://azure.microsoft.com/support/faq/). The HDInsight service provides an additional level of support for built-in components.
+
+There are two types of open-source components that are available in the HDInsight service:
+
+* **Built-in components** - These components are pre-installed on HDInsight clusters and provide core functionality of the cluster. For example, YARN ResourceManager, the Hive query language (HiveQL), and the Mahout library belong to this category. A full list of cluster components is available in [What's new in the Hadoop cluster versions provided by HDInsight](https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-component-versioning).
+* **Custom components** - You, as a user of the cluster, can install or use in your workload any component available in the community or created by you.
+
+> [!WARNING]
+> Components provided with the HDInsight cluster are fully supported. Microsoft Support helps to isolate and resolve issues related to these components.
+>
+> Custom components receive commercially reasonable support to help you to further troubleshoot the issue. Microsoft support may be able to resolve the issue OR they may ask you to engage available channels for the open source technologies where deep expertise for that technology is found. For example, there are many community sites that can be used, like: [MSDN forum for HDInsight](https://social.msdn.microsoft.com/Forums/azure/home?forum=hdinsight), [http://stackoverflow.com](http://stackoverflow.com). Also Apache projects have project sites on [http://apache.org](http://apache.org), for example: [Hadoop](http://hadoop.apache.org/).
+
 
 ## Use external packages with Jupyter notebooks
 
 1. From the [Azure Portal](https://portal.azure.com/), from the startboard, click the tile for your Spark cluster (if you pinned it to the startboard). You can also navigate to your cluster under **Browse All** > **HDInsight Clusters**.   
 
-2. From the Spark cluster blade, click **Script Actions** from the left pane. Run the custom action that installs TensorFlow in the head nodes and the worker nodes. The bash script can be referenced from: https://hdiconfigactions.blob.core.windows.net/linuxtensorflow/tensorflowinstall.sh
+2. From the Spark cluster blade, click **Script Actions** from the left pane. Use the script type "Custom" and enter a friendly name for the script action. Run the script on the **head and worker nodes** and leave the parameters field blank. The bash script can be referenced from: https://hdiconfigactions.blob.core.windows.net/linuxtensorflow/tensorflowinstall.sh
 Visit the documentation on [how to use custom script actions](https://docs.microsoft.com/azure/hdinsight/hdinsight-hadoop-customize-cluster-linux).
 
    > [!NOTE]