Plugins
=======

.. contents::
   :local:
   :depth: 2

List of available plugins
-------------------------

Anaconda for cluster management can install and manage the following plugins on
a cluster:

 - `Anaconda <https://docs.continuum.io/anaconda/index>`_
 - `Dask/Distributed <http://distributed.readthedocs.org/en/latest/>`_
 - `Ganglia <http://ganglia.sourceforge.net/>`_
 - `IPython Parallel <https://ipyparallel.readthedocs.org/>`_
 - `Jupyter Notebook <https://jupyter.org/>`_
 - `Salt <http://saltstack.com/>`_

The following plugins are unsupported and should only by used for
prototyping/experimental purposes:

 - `Elasticsearch <https://www.elastic.co/products/elasticsearch>`_
 - `HDFS <http://hadoop.apache.org/docs/r1.2.1/hdfs_design.html>`_
 - `Hive <https://hive.apache.org/>`_
 - `Impala <http://impala.io/>`_
 - `Kibana <https://www.elastic.co/products/kibana>`_
 - `Logstash <https://www.elastic.co/products/logstash>`_
 - `Spark (standalone mode or YARN) <https://spark.apache.org/>`_
 - `Storm <https://storm.apache.org/>`_
 - `YARN <http://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html>`_
 - `ZooKeeper <https://zookeeper.apache.org/>`_

If you're interested in using Anaconda with production Hadoop clusters,
Anaconda for cluster management works with enterprise Hadoop distributions such as
`Cloudera CDH <https://www.cloudera.com/products/apache-hadoop/key-cdh-components.html>`_
or `Hortonworks HDP <http://hortonworks.com/products/hdp/>`_.

On clusters with existing enterprise Hadoop installations, Anaconda for cluster
management can manage packages (e.g., for PySpark, SparkR, or Dask) and can
install and manage the Jupyter Notebook and Dask plugins.


Installing Plugins
------------------

Plugins can be installed using two methods:

 1. Using the cluster ``profile.yaml`` file when creating or provisioning a cluster.
 2. Using the ``acluster install`` command after the cluster is created.

**1. Install plugins with the profile.yaml file**

When creating or provisioning a cluster, create or edit the file
``~/.acluster/profiles.d/profile_name.yaml`` as shown in the example below:

::

  name: profile_name
  provider: aws
  node_id: ami-d05e75b8  # Ubuntu 14.04, us-east-1 region
  user: ubuntu
  node_type: m3.large
  num_nodes: 5
  plugins:
    - notebook
    - dask

Optionally, you can configure some plugin settings from within your profile. For
example, you can specify a password to protect a Jupyter Notebook using:

::

  name: profile_name
  provider: aws
  node_id: ami-d05e75b8  # Ubuntu 14.04, us-east-1 region
  user: ubuntu
  node_type: m3.large
  num_nodes: 5
  plugins:
    - notebook:
        password: secret

Refer to the :ref:`plugin_settings` section for more details on configuring plugin settings.


**2. Install plugins using the acluster install command**

After the cluster has been created, you can view a list of available plugins with the command ``acluster install`` as shown in the example below:

::

  $ acluster install
  Usage: acluster install [OPTIONS] COMMAND [ARGS]...

    Install plugins across the cluster

  Options:
    -h, --help  Show this message and exit.

  Commands:
    conda             Install (mini)conda
    dask              Install Dask/Distributed
    elasticsearch     Install Elasticsearch
    ganglia           Install Ganglia
    hdfs              Install HDFS
    hive              Install Hive
    impala            Install Impala
    ipython-parallel  Install IPython Parallel
    kibana            Install Kibana
    notebook          Install Jupyter Notebook
    logstash          Install Logstash
    salt              Install Salt
    spark-standalone  Install Spark (standalone)
    spark-yarn        Install Spark (YARN)
    storm             Install Storm
    yarn              Install YARN
    zookeeper         Install Zookeeper

All of the above subcommands can optionally receive a ``--cluster/-x`` option
to specify a cluster. This option is not required if you only have one cluster
running.

**Note**: Salt is the base for all plugins except Conda. Therefore, the Salt
plugin needs to be installed before the other plugins can be installed. Salt is
installed by default when you create or provision a cluster using the
``acluster create`` or ``acluster provision`` command.


.. _plugin_settings:

Plugin Settings
---------------

The following plugins support custom settings that can be defined within a profile.

Conda
~~~~~

Configure conda packages and environments to be installed upon cluster creation
or provisioning:

::

  name: profile_name
  plugins:
    - conda:
        environments:
          root:
            - numpy
          py27:
            - python=2.7
            - scipy
            - numba
          py34:
            - python=3.4
            - pandas
            - nltk

Configure the installation location of conda (default: ``/opt/anaconda``):

::

  name: profile_name
  plugins:
    - conda:
        install_prefix: /opt/another_anaconda

Set ``conda_sh`` to false to disable the creation of
``/etc/profile.d/conda.sh`` on cluster nodes (default: true):

::

  name: profile_name
  plugins:
    - conda:
        conda_sh: false

Set ``conda_group_name`` to any valid unix group (default: anaconda):

::

  name: profile_name
  plugins:
    - conda:
        conda_group_name: anaconda

Set ``conda_acl`` to a list of users who will be given access for Anaconda Cluster
admin capabilities.  Note:  When using this setting at least one user must have
sudo access during the provisioning phase.  Typically, this will include the user
previously set above as ``user``.

::

  name: profile_name
  plugins:
    - conda:
        conda_acl:
          - user1
          - user2

Set ``ssl_verify`` to a custom SSL path or to ``False`` to disable SSL
verification for ``conda``. Refer to the `conda documentation <http://conda.pydata.org/docs/install/central.html#ssl-verification>`_
for more information.

::

  name: profile_name
  plugins:
    - conda:
        ssl_verify: False

Dask
~~~~

You can optionally set the number of processes (``nprocs``) to use for
the Dask/Distributed workers and the ``host`` to access the Dask/Distributed UI
via a browser. Refer to the
`Dask distributed scheduler documentation <http://distributed.readthedocs.org/en/latest/>`_
for more information about these settings.

::

  name: profile_name
  plugins:
    - dask:
        nprocs: 8
        host: dask-ui.com

HDFS
~~~~

By default, the HDFS plugin is configured to use the following directories:
``/data/dfs/nn`` on the namenode and ``/data/dfs/dn`` on the datanodes. When
multiple drives are available, the same directories are used on all non-root
drives.

You can optionally set custom directories for the HDFS namenode and datanode.
For example, the following settings can be used if you want to utilize a large
root volume (e.g., using the ``root_volume`` profile setting with Amazon EC2):

::

  name: profile_name
  plugins:
    - hdfs:
        namenode_dirs:
          - /data/dfs/nn
        datanode_dirs:
          - /data/dfs/dn

Jupyter Notebook
~~~~~~~~~~~~~~~~

Set a custom password to protect a Jupyter Notebook (default: ``acluster``):

::

  name: profile_name
  plugins:
    - notebook:
        password: acluster

Set a custom port for the Jupyter Notebook server (default: ``8888``):

::

  name: profile_name
  plugins:
    - notebook:
        port: 8888

Set a custom directory for Jupyter Notebooks (default: ``/opt/notebooks``):

::

  name: profile_name
  plugins:
    - notebook:
        directory: /opt/notebooks

Custom download settings for plugins
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Most plugins are installed from the standard package management repositories
for your Linux distribution. Some plugins are downloaded directly from their
source/project website. You can override the default download settings for the
following plugins:

::

  name: profile_name
  plugins:
    - elasticsearch:
        download_url: https://download.elasticsearch.org/elasticsearch/release/org/elasticsearch/distribution/tar/elasticsearch/2.1.0/elasticsearch-2.1.0.tar.gz
        download_hash: sha1=b6d681b878e3a906fff8c067b3cfe855240bffbb
        version: elasticsearch-2.1.0
    - logstash:
        download_url: https://download.elastic.co/logstash/logstash/logstash-2.1.1.tar.gz
        download_hash: sha1=d71a6e015509030ab6012adcf79291994ece0b39
        version: logstash-2.1.1
    - kibana:
        download_url: https://download.elastic.co/kibana/kibana/kibana-4.3.0-linux-x64.tar.gz
        download_hash: sha1=d64e1fc0ddeaaab85e168177de6c78ed82bb3a3b
        version: kibana-4.3.0-linux-x64
    - storm:
        source_url: http://apache.arvixe.com/storm/apache-storm-0.9.5/apache-storm-0.9.5.tar.gz
        version_name: apache-storm-0.9.5


Managing Plugins
----------------

The following commands can be used to manage your plugins:

Plugin Status
~~~~~~~~~~~~~

Check the status of the plugins by using the ``acluster status`` command:

::

    $ acluster status
    Usage: acluster status [OPTIONS] COMMAND [ARGS]...

    Options:
      -x, --cluster TEXT              Cluster name
      -l, --log-level [info|debug|error]
                                      Library logging level
      -h, --help                      Show this message and exit.

    Commands:
      conda             Check Conda status
      dask              Check Dask/Distributed status
      elasticsearch     Check Elasticsearch status
      ganglia           Check Ganglia status
      hdfs              Check HDFS status
      hive              Check Hive status
      impala            Check Impala status
      ipython-parallel  Check IPython Parallel status
      kibana            Check Kibana status
      notebook          Check IPython/Jupyter Notebook status
      salt              Check Salt package status
      salt-conda        Check Salt Conda module status
      salt-key          Check salt-minion keys status
      spark-standalone  Check Spark (standalone) status
      ssh               Check SSH status
      storm             Check Storm status
      yarn              Check YARN status

Example:

::

    $ acluster status conda
    Checking status of conda on cluster: demo_cluster
    54.81.187.22: True
    54.91.219.252: True
    54.163.26.229: True
    54.145.10.211: True
    Status all: True

    $ acluster status salt
    54.167.128.130: True
    54.205.160.114: True
    50.16.32.99: True
    50.16.34.82: True
    54.163.143.34: True
    Status all: True

    $ acluster status salt-key
    ip-10-156-23-215.ec2.internal: True
    ip-10-147-47-235.ec2.internal: True
    ip-10-225-181-251.ec2.internal: True
    ip-10-237-145-2.ec2.internal: True
    ip-10-156-30-32.ec2.internal: True
    Status all: True

    $ acluster status salt-conda
    ip-10-156-23-215.ec2.internal: True
    ip-10-237-145-2.ec2.internal: True
    ip-10-225-181-251.ec2.internal: True
    ip-10-147-47-235.ec2.internal: True
    ip-10-156-30-32.ec2.internal: True
    Status all: True


The multiple salt status checks perform different checks. The ``acluster status salt``
command verifies that the salt package is installed, the ``acluster status salt-key``
command verifies that the salt minions are connected to the head node, and the
``acluster status salt-conda`` command verifies that the salt conda module is
distributed across the cluster and is operational.

All of the above checks should return a successful status after executing ``acluster install salt``.

Open Plugin UIs
~~~~~~~~~~~~~~~

Some of the plugins provide a browser UI that can be displayed to the user. The
``acluster open`` command is a utility command that opens a browser window
corresponding to each plugin. The command:

::

    $ acluster open notebook

will open a browser window to the Jupyter Notebook (port 8888).

Use the ``--no-browser`` option to print the URL for the plugin interface
without opening a browser window.

::

    $ acluster open notebook --no-browser
    notebook: http://54.172.82.53:8888

Restart Plugins
~~~~~~~~~~~~~~~

If a plugin is not working correctly, restart the processes by using the ``acluster restart`` command.

Stop Plugins
~~~~~~~~~~~~

To stop a plugin, use the ``acluster stop`` command.


Plugin Notes and Network Ports
------------------------------

HDFS
~~~~

Requires: ``salt``

Distributed file system used by many of the distributed analytics engines such
as ``Impala``, ``Hive``, and ``Spark``.

+------------+------------+-----------+
| Service    | Location   | Port      |
+============+============+===========+
| NameNode UI| Head node  | 50070     |
+------------+------------+-----------+
| HDFS Master| Head node  | 9000      |
+------------+------------+-----------+
| WebHDFS    | Head node  | 14000     |
+------------+------------+-----------+

Jupyter Notebook
~~~~~~~~~~~~~~~~

Requires: ``salt``

Web-based interactive computational environment for Python.

+------------+------------+-----------+
| Service    | Location   | Port      |
+============+============+===========+
| Notebook   | Head node  | 8888      |
+------------+------------+-----------+

Notebooks are saved in the directory ``/opt/notebooks``. You can upload and download notebooks
from the cluster by using the ``put`` and ``get`` commands, respectively.

::

    $ acluster put mynotebook.ipynb /opt/notebooks/mynotebook.ipynb
    $ acluster get /opt/notebooks/mynotebook.ipynb mynotebook.ipynb

Miniconda
~~~~~~~~~

Python distribution from `Continuum Analytics <http://continuum.io>`_ -- ships with Python libraries for
large-scale data processing, predictive analytics, and scientific computing.

Salt
~~~~

Requires: ``conda``

Configuration management system.

+----------------------+-------------+-----------+
| Service              | Location    | Port      |
+======================+=============+===========+
| Salt Master/Minion   | All nodes   | 4505      |
+----------------------+-------------+-----------+
| Salt Master/Minion   | All nodes   | 4506      |
+----------------------+-------------+-----------+

Spark
~~~~~

Computing framework and analytics engine written in Java/Scala with a Python interface (PySpark).

+-----------------------+------------+-----------+
| Service               | Location   | Port      |
+=======================+============+===========+
| Spark UI (standalone) | Head node  | 8080      |
+-----------------------+------------+-----------+

YARN
~~~~

Resource manager in which all Hadoop and Hadoop-like jobs are run.

+------------+-----------------+-----------+
| Service    | Location        | Port      |
+============+=================+===========+
| Resource UI| Head node       | 9026      |
+------------+-----------------+-----------+
| NodeManager| Compute node(s) | 9035      |
+------------+-----------------+-----------+
