Merge pull request #113237 from dagiro/freshness_c62

freshness_c62

Author: PRMerger12

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

@@ -6,7 +6,8 @@ ms.author: hrasheed
 ms.reviewer: jasonh
 ms.service: hdinsight
 ms.topic: conceptual
-ms.date: 03/16/2020
+ms.custom: seoapr2020
+ms.date: 04/29/2020
 ---
 
 # Safely manage Python environment on Azure HDInsight using Script Action
@@ -15,15 +16,15 @@ ms.date: 03/16/2020
 > * [Using cell magic](apache-spark-jupyter-notebook-use-external-packages.md)
 > * [Using Script Action](apache-spark-python-package-installation.md)
 
-HDInsight has two built-in Python installations in the Spark cluster, Anaconda Python 2.7 and Python 3.5. In some cases, customers need to customize the Python environment, like installing external Python packages or another Python version. In this article, we show the best practice of safely managing Python environments for an [Apache Spark](./apache-spark-overview.md) cluster on HDInsight.
+HDInsight has two built-in Python installations in the Spark cluster, Anaconda Python 2.7 and Python 3.5. Customers may need to customize the Python environment. Like installing external Python packages or another Python version. Here, we show the best practice of safely managing Python environments for Apache Spark clusters on HDInsight.
 
 ## Prerequisites
 
-An Apache Spark cluster on HDInsight. For instructions, see [Create Apache Spark clusters in Azure HDInsight](apache-spark-jupyter-spark-sql.md). If you do not already have a Spark cluster on HDInsight, you can run script actions during cluster creation. Visit the documentation on [how to use custom script actions](../hdinsight-hadoop-customize-cluster-linux.md).
+An Apache Spark cluster on HDInsight. For instructions, see [Create Apache Spark clusters in Azure HDInsight](apache-spark-jupyter-spark-sql.md). If you don't already have a Spark cluster on HDInsight, you can run script actions during cluster creation. Visit the documentation on [how to use custom script actions](../hdinsight-hadoop-customize-cluster-linux.md).
 
 ## Support for open-source software used on HDInsight clusters
 
-The Microsoft Azure HDInsight service uses an ecosystem of open-source technologies formed around Apache Hadoop. Microsoft Azure provides a general level of support for open-source technologies. For more information, see [Azure Support FAQ website](https://azure.microsoft.com/support/faq/). The HDInsight service provides an additional level of support for built-in components.
+The Microsoft Azure HDInsight service uses an environment of open-source technologies formed around Apache Hadoop. Microsoft Azure provides a general level of support for open-source technologies. For more information, see [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:
 
@@ -35,7 +36,7 @@ There are two types of open-source components that are available in the HDInsigh
 > [!IMPORTANT]
 > 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), [https://stackoverflow.com](https://stackoverflow.com). Also Apache projects have project sites on [https://apache.org](https://apache.org), for example: [Hadoop](https://hadoop.apache.org/).
+> 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), `https://stackoverflow.com`. Also Apache projects have project sites on `https://apache.org`.
 
 ## Understand default Python installation
 
@@ -50,9 +51,9 @@ HDInsight Spark cluster is created with Anaconda installation. There are two Pyt
 
 ## Safely install external Python packages
 
-HDInsight cluster depends on the built-in Python environment, both Python 2.7 and Python 3.5. Directly installing custom packages in those default built-in environments may cause unexpected library version changes, and break the cluster further. In order to safely install custom external Python packages for your Spark applications, follow below steps.
+HDInsight cluster depends on the built-in Python environment, both Python 2.7 and Python 3.5. Directly installing custom packages in those default built-in environments may cause unexpected library version changes. And break the cluster further. To safely install custom external Python packages for your Spark applications, follow below steps.
 
-1. Create Python virtual environment using conda. A virtual environment provides an isolated space for your projects without breaking others. When creating the Python virtual environment, you can specify python version that you want to use. Note that you still need to create virtual environment even though you would like to use Python 2.7 and 3.5. This is to make sure the cluster's default environment not getting broke. Run script actions on your cluster for all nodes with below script to create a Python virtual environment.
+1. Create Python virtual environment using conda. A virtual environment provides an isolated space for your projects without breaking others. When creating the Python virtual environment, you can specify python version that you want to use. You still need to create virtual environment even though you would like to use Python 2.7 and 3.5. This requirement is to make sure the cluster's default environment not getting broke. Run script actions on your cluster for all nodes with below script to create a Python virtual environment.
 
     -   `--prefix` specifies a path where a conda virtual environment lives. There are several configs that need to be changed further based on the path specified here. In this example, we use the py35new, as the cluster has an existing virtual environment called py35 already.
     -   `python=` specifies the Python version for the virtual environment. In this example, we use version 3.5, the same version as the cluster built in one. You can also use other Python versions to create the virtual environment.
@@ -62,9 +63,9 @@ HDInsight cluster depends on the built-in Python environment, both Python 2.7 an
     sudo /usr/bin/anaconda/bin/conda create --prefix /usr/bin/anaconda/envs/py35new python=3.5 anaconda --yes
     ```
 
-2. Install external Python packages in the created virtual environment if needed. Run script actions on your cluster for all nodes with below script to install external Python packages. You need to have sudo privilege here in order to write files to the virtual environment folder.
+2. Install external Python packages in the created virtual environment if needed. Run script actions on your cluster for all nodes with below script to install external Python packages. You need to have sudo privilege here to write files to the virtual environment folder.
 
-    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 [conda-forge](https://conda-forge.org/feedstocks/).
+    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 [conda-forge](https://conda-forge.org/feedstocks/).
 
     Use below command if you would like to install a library with its latest version:
 
@@ -109,7 +110,7 @@ HDInsight cluster depends on the built-in Python environment, both Python 2.7 an
 
     2. Expand Advanced livy2-env, add below statements at bottom. If you installed the virtual environment with a different prefix, change the path correspondingly.
 
-        ```
+        ```bash
         export PYSPARK_PYTHON=/usr/bin/anaconda/envs/py35new/bin/python
         export PYSPARK_DRIVER_PYTHON=/usr/bin/anaconda/envs/py35new/bin/python
         ```
@@ -118,7 +119,7 @@ HDInsight cluster depends on the built-in Python environment, both Python 2.7 an
 
     3. Expand Advanced spark2-env, replace the existing export PYSPARK_PYTHON statement at bottom. If you installed the virtual environment with a different prefix, change the path correspondingly.
 
-        ```
+        ```bash
         export PYSPARK_PYTHON=${PYSPARK_PYTHON:-/usr/bin/anaconda/envs/py35new/bin/python}
         ```
 
@@ -128,7 +129,7 @@ HDInsight cluster depends on the built-in Python environment, both Python 2.7 an
 
         ![Change Spark config through Ambari](./media/apache-spark-python-package-installation/ambari-restart-services.png)
 
-4. If you would like to use the new created virtual environment on Jupyter. You need to change Jupyter configs and restart Jupyter. Run script actions on all header nodes with below statement to point Jupyter to the new created virtual environment. Make sure to modify the path to the prefix you specified for your virtual environment. After running this script action, restart Jupyter service through Ambari UI to make this change available.
+4. If you would like to use the new created virtual environment on Jupyter. Change Jupyter configs and restart Jupyter. Run script actions on all header nodes with below statement to point Jupyter to the new created virtual environment. Make sure to modify the path to the prefix you specified for your virtual environment. After running this script action, restart Jupyter service through Ambari UI to make this change available.
 
     ```bash
     sudo sed -i '/python3_executable_path/c\ \"python3_executable_path\" : \"/usr/bin/anaconda/envs/py35new/bin/python3\"' /home/spark/.sparkmagic/config.json
@@ -140,13 +141,12 @@ HDInsight cluster depends on the built-in Python environment, both Python 2.7 an
 
 ## Known issue
 
-There is a known bug for Anaconda version 4.7.11, 4.7.12 and 4.8.0. If you see your script actions hanging at `"Collecting package metadata (repodata.json): ...working..."` and failing with `"Python script has been killed due to timeout after waiting 3600 secs"`. You can download [this script](https://gregorysfixes.blob.core.windows.net/public/fix-conda.sh) and run it as script actions on all nodes to fix the issue.
+There's a known bug for Anaconda version `4.7.11`, `4.7.12`, and `4.8.0`. If you see your script actions hanging at `"Collecting package metadata (repodata.json): ...working..."` and failing with `"Python script has been killed due to timeout after waiting 3600 secs"`. You can download [this script](https://gregorysfixes.blob.core.windows.net/public/fix-conda.sh) and run it as script actions on all nodes to fix the issue.
 
 To check your Anaconda version, you can SSH to the cluster header node and run `/usr/bin/anaconda/bin/conda --v`.
 
 ## Next steps
 
 * [Overview: Apache Spark on Azure HDInsight](apache-spark-overview.md)
-* [Apache Spark with BI: Perform interactive data analysis using Spark in HDInsight with BI tools](apache-spark-use-bi-tools.md)
-* [Manage resources for the Apache Spark cluster in Azure HDInsight](apache-spark-resource-manager.md)
+* [External packages with Jupyter notebooks in Apache Spark](apache-spark-jupyter-notebook-use-external-packages.md)
 * [Track and debug jobs running on an Apache Spark cluster in HDInsight](apache-spark-job-debugging.md)