Make Modin on MPI through unidist component more explicit

Signed-off-by: Igoshev, Iaroslav <iaroslav.igoshev@intel.com>

README.md

@@ -65,7 +65,7 @@ If you want to install Modin with a specific engine, we recommend:
 ```bash
 pip install "modin[ray]" # Install Modin dependencies and Ray.
 pip install "modin[dask]" # Install Modin dependencies and Dask.
-pip install "modin[unidist]" # Install Modin dependencies and Unidist.
+pip install "modin[mpi]" # Install Modin dependencies and MPI through unidist.
 ```
 
 Modin automatically detects which engine(s) you have installed and uses that for scheduling computation.
@@ -85,7 +85,7 @@ Each engine can also be installed individually (and also as a combination of sev
 ```bash
 conda install -c conda-forge modin-ray  # Install Modin dependencies and Ray.
 conda install -c conda-forge modin-dask # Install Modin dependencies and Dask.
-conda install -c conda-forge modin-unidist # Install Modin dependencies and Unidist.
+conda install -c conda-forge modin-mpi # Install Modin dependencies and MPI through unidist.
 conda install -c conda-forge modin-hdk # Install Modin dependencies and HDK.
 ```
 
@@ -119,7 +119,7 @@ export MODIN_ENGINE=unidist # Modin will use Unidist
 ```
 
 If you want to choose the Unidist engine, you should set the additional environment 
-variable ``UNIDIST_BACKEND``, because currently Modin only supports Unidist on MPI:
+variable ``UNIDIST_BACKEND``, because currently Modin only supports MPI through Unidist:
 
 ```bash
 export UNIDIST_BACKEND=mpi # Unidist will use MPI backend

docs/development/architecture.rst

@@ -216,8 +216,8 @@ documentation page on :doc:`contributing </development/contributing>`.
     - Uses the `Dask Futures`_ execution framework.
     - The storage format is `pandas` and the in-memory partition type is a pandas DataFrame.
     - For more information on the execution path, see the :doc:`pandas on Dask </flow/modin/core/execution/dask/implementations/pandas_on_dask/index>` page.
-- :doc:`pandas on Unidist </development/using_pandas_on_unidist>`
-    - Uses the Unidist_ execution framework.
+- :doc:`pandas on MPI </development/using_pandas_on_mpi>`
+    - Uses MPI_ through the Unidist_ execution framework.
     - The storage format is `pandas` and the in-memory partition type is a pandas DataFrame.
     - For more information on the execution path, see the :doc:`pandas on Unidist </flow/modin/core/execution/unidist/implementations/pandas_on_unidist/index>` page.
 - :doc:`pandas on Python </development/using_pandas_on_python>`
@@ -228,8 +228,8 @@ documentation page on :doc:`contributing </development/contributing>`.
     - Uses the Ray_ execution framework.
     - The storage format is `pandas` and the in-memory partition type is a pandas DataFrame.
     - For more information on the execution path, see the :doc:`experimental pandas on Ray </flow/modin/experimental/core/execution/ray/implementations/pandas_on_ray/index>` page.
-- pandas on Unidist (experimental)
-    - Uses the Unidist_ execution framework.
+- pandas on MPI (experimental)
+    - Uses MPI_ through the Unidist_ execution framework.
     - The storage format is `pandas` and the in-memory partition type is a pandas DataFrame.
     - For more information on the execution path, see the :doc:`experimental pandas on Unidist </flow/modin/experimental/core/execution/unidist/implementations/pandas_on_unidist/index>` page.
 - pandas on Dask (experimental)
@@ -375,6 +375,7 @@ details. The documentation covers most modules, with more docs being added every
 .. _Arrow tables: https://arrow.apache.org/docs/python/generated/pyarrow.Table.html
 .. _Ray: https://github.com/ray-project/ray
 .. _Unidist: https://github.com/modin-project/unidist
+.. _MPI: https://www.mpi-forum.org/
 .. _code: https://github.com/modin-project/modin/blob/master/modin/core/dataframe
 .. _Dask: https://github.com/dask/dask
 .. _Dask Futures: https://docs.dask.org/en/latest/futures.html

docs/development/index.rst

@@ -10,7 +10,7 @@ Development
     using_pandas_on_ray
     using_pandas_on_dask
     using_pandas_on_python
-    using_pandas_on_unidist
+    using_pandas_on_mpi
     using_hdk
     using_pyarrow_on_ray
 

docs/development/partition_api.rst

@@ -36,7 +36,7 @@ in the worker process that processes a function (please, refer to `Dask document
 
 Unidist engine
 --------------
-Currently, Modin only supports unidist on MPI backend. There is no mentioned above issue for
+Currently, Modin only supports MPI through Unidist. There is no mentioned above issue for
 Modin on ``Unidist`` engine using ``MPI`` backend with ``pandas`` in-memory format
 because ``Unidist`` saves any objects in the MPI worker process that processes a function
 (please, refer to `Unidist documentation`_ for more information).

docs/development/using_pandas_on_unidist.rst → docs/development/using_pandas_on_mpi.rst

@@ -1,14 +1,14 @@
-pandas on Unidist
-=================
+pandas on MPI through unidist
+=============================
 
-This section describes usage related documents for the pandas on Unidist component of Modin.
+This section describes usage related documents for the pandas on MPI through unidist component of Modin.
 
 Modin uses pandas as a primary memory format of the underlying partitions and optimizes queries
 ingested from the API layer in a specific way to this format. Thus, there is no need to care of choosing it
 but you can explicitly specify it anyway as shown below.
 
-One of the execution engines that Modin uses is Unidist. Currently, Modin only supports Unidist on MPI backend.
-To enable the pandas on Unidist execution using MPI backend you should set the following environment variables:
+One of the execution engines that Modin uses is MPI through unidist.
+To enable the pandas on MPI through unidist execution you should set the following environment variables:
 
 .. code-block:: bash
 

docs/flow/modin/core/execution/unidist/implementations/pandas_on_unidist/index.rst

@@ -6,7 +6,7 @@ PandasOnUnidist Execution
 Queries that perform data transformation, data ingress or data egress using the `pandas on Unidist` execution
 pass through the Modin components detailed below.
 
-To enable `pandas on Unidist` execution, please refer to the usage section in :doc:`pandas on Unidist </development/using_pandas_on_unidist>`.
+To enable `pandas on MPI through unidist` execution, please refer to the usage section in :doc:`pandas on Unidist </development/using_pandas_on_mpi>`.
 
 Data Transformation
 '''''''''''''''''''

docs/getting_started/faq.rst

@@ -119,7 +119,7 @@ and Modin will do computation with that engine:
     pip install "modin[dask]" # Install Modin dependencies and Dask to run on Dask
     export MODIN_ENGINE=dask  # Modin will use Dask
 
-    pip install "modin[unidist]" # Install Modin dependencies and Unidist to run on Unidist.
+    pip install "modin[mpi]" # Install Modin dependencies and MPI to run on MPI through unidist.
     export MODIN_ENGINE=unidist  # Modin will use Unidist
     export UNIDIST_BACKEND=mpi   # Unidist will use MPI backend.
 

docs/getting_started/installation.rst

@@ -30,7 +30,7 @@ Modin can be used with :doc:`Ray</development/using_pandas_on_ray>`, :doc:`Dask<
 
   pip install "modin[ray]" # Install Modin dependencies and Ray to run on Ray
   pip install "modin[dask]" # Install Modin dependencies and Dask to run on Dask
-  pip install "modin[unidist]" # Install Modin dependencies and Unidist to run on Unidist
+  pip install "modin[mpi]" # Install Modin dependencies and Unidist to run on Unidist
   pip install "modin[all]" # Install all of the above
 
 Modin will automatically detect which engine you have installed and use that for
@@ -65,7 +65,7 @@ storage formats or for different functionalities of Modin. Here is a list of dep
 
 .. code-block:: bash
 
-  pip install "modin[unidist]" # If you want to use the Unidist execution engine
+  pip install "modin[mpi]" # If you want to use the Unidist execution engine
 
 Installing on Google Colab
 """""""""""""""""""""""""""
@@ -106,7 +106,7 @@ it is possible to install modin with chosen engine(s) alongside. Current options
 +---------------------------------+---------------------------+-----------------------------+
 | modin-ray                       | Ray_                      |       Linux, Windows        |
 +---------------------------------+---------------------------+-----------------------------+
-| modin-unidist                   | Unidist_                  |   Linux, Windows, MacOS     |
+| modin-mpi                       | MPI_ through Unidist_      |   Linux, Windows, MacOS     |
 +---------------------------------+---------------------------+-----------------------------+
 | modin-hdk                       | HDK_                      |          Linux              |
 +---------------------------------+---------------------------+-----------------------------+
@@ -117,7 +117,7 @@ For installing Dask, Ray and Unidist engines into conda environment following co
 
 .. code-block:: bash
 
-  conda install -c conda-forge modin-ray modin-dask modin-unidist
+  conda install -c conda-forge modin-ray modin-dask modin-mpi
 
 All set of engines could be available in conda environment by specifying:
 
@@ -129,7 +129,7 @@ or explicitly:
 
 .. code-block:: bash
 
-  conda install -c conda-forge modin-ray modin-dask modin-unidist modin-hdk
+  conda install -c conda-forge modin-ray modin-dask modin-mpi modin-hdk
 
 ``conda`` may be slow installing ``modin-all`` or combitations of execution engines so we currently recommend using libmamba solver for the installation process.
 To do this install it in a base environment:
@@ -171,7 +171,7 @@ also use ``pip``.
 This will install directly from the repo without you having to manually clone it! Please be aware
 that these changes have not made it into a release and may not be completely stable.
 
-If you would like to install Modin with a specific engine, you can use ``modin[ray]`` or ``modin[dask]`` or ``modin[unidist]`` instead of ``modin[all]`` in the command above.
+If you would like to install Modin with a specific engine, you can use ``modin[ray]`` or ``modin[dask]`` or ``modin[mpi]`` instead of ``modin[all]`` in the command above.
 
 Windows
 -------
@@ -214,6 +214,7 @@ Once cloned, ``cd`` into the ``modin`` directory and use ``pip`` to install:
 .. _WSL: https://docs.microsoft.com/en-us/windows/wsl/install-win10
 .. _Ray: http://ray.readthedocs.io
 .. _Dask: https://github.com/dask/dask
+.. _MPI: https://www.mpi-forum.org/
 .. _Unidist: https://github.com/modin-project/unidist
 .. _HDK: https://github.com/intel-ai/hdk
 .. _`Intel Distribution of Modin`: https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/distribution-of-modin.html#gs.86stqv

docs/index.rst

@@ -61,7 +61,7 @@ of the targets:
 
    pip install "modin[ray]" # Install Modin dependencies and Ray to run on Ray
    pip install "modin[dask]" # Install Modin dependencies and Dask to run on Dask
-   pip install "modin[unidist]" # Install Modin dependencies and Unidist to run on Unidist
+   pip install "modin[mpi]" # Install Modin dependencies and MPI to run on MPI through Unidist
    pip install "modin[all]" # Install all of the above
 
 Modin will automatically detect which engine you have installed and use that for
@@ -77,7 +77,7 @@ variable ``MODIN_ENGINE`` and Modin will do computation with that engine:
    export MODIN_ENGINE=unidist # Modin will use Unidist
 
 If you want to choose the Unidist engine, you should set the additional environment 
-variable ``UNIDIST_BACKEND``, because currently Modin only supports Unidist on MPI:
+variable ``UNIDIST_BACKEND``, because currently Modin only supports MPI through Unidist:
 
 .. code-block:: bash
 

examples/tutorial/jupyter/README.md

@@ -4,7 +4,7 @@ Currently we provide tutorial notebooks for the following execution backends:
 
 - [PandasOnRay](https://modin.readthedocs.io/en/latest/development/using_pandas_on_ray.html)
 - [PandasOnDask](https://modin.readthedocs.io/en/latest/development/using_pandas_on_dask.html)
-- [PandasOnUnidist](https://modin.readthedocs.io/en/latest/development/using_pandas_on_unidist.html)
+- [PandasOnMPI through unidist](https://modin.readthedocs.io/en/latest/development/using_pandas_on_mpi.html)
 - [HdkOnNative](https://modin.readthedocs.io/en/latest/development/using_hdk.html)
 
 ## Creating a development environment

examples/tutorial/jupyter/execution/pandas_on_unidist/local/exercise_1.ipynb

@@ -64,7 +64,7 @@
     "\n",
     "Modin uses Ray as an execution engine by default so no additional action is required to start to use it. Alternatively, if you need to use another engine, it should be specified either by setting the Modin config or by setting Modin environment variable before the first operation with Modin as it is shown below. Also, note that the full list of Modin configs and corresponding environment variables can be found in the [Modin Configuration Settings](https://modin.readthedocs.io/en/stable/flow/modin/config.html#modin-configs-list) section of the Modin documentation.\n",
     "\n",
-    "One of the execution engines that Modin uses is Unidist. Currently, Modin only supports Unidist on MPI backend, so it should be specified either by setting the Unidist config or by setting Unidist environment variable. The full list of Unidist configs and corresponding environment variables can be found in the [Unidist Configuration Settings](https://unidist.readthedocs.io/en/latest/flow/unidist/config.html#unidist-configuration-settings-list) section of the Unidist documentation."
+    "One of the execution engines that Modin uses is Unidist. Currently, Modin only supports MPI through Unidist, so it should be specified either by setting the Unidist config or by setting Unidist environment variable. The full list of Unidist configs and corresponding environment variables can be found in the [Unidist Configuration Settings](https://unidist.readthedocs.io/en/latest/flow/unidist/config.html#unidist-configuration-settings-list) section of the Unidist documentation."
    ]
   },
   {

examples/tutorial/jupyter/execution/pandas_on_unidist/requirements.txt

@@ -1,5 +1,5 @@
 fsspec>=2022.05.0
 jupyterlab
 ipywidgets
-modin[unidist]
+modin[mpi]
 modin[spreadsheet]

modin/core/execution/unidist/common/utils.py

@@ -29,7 +29,7 @@ def initialize_unidist():
 
     if unidist_cfg.Backend.get() != "mpi":
         raise RuntimeError(
-            f"Modin only supports unidist on MPI for now, got unidist backend '{unidist_cfg.Backend.get()}'"
+            f"Modin only supports MPI through unidist for now, got unidist backend '{unidist_cfg.Backend.get()}'"
         )
 
     if not unidist.is_initialized():

setup.py

@@ -9,9 +9,13 @@
 # ray==2.5.0 broken: https://github.com/conda-forge/ray-packages-feedstock/issues/100
 # pydantic<2: https://github.com/modin-project/modin/issues/6336
 ray_deps = ["ray[default]>=1.13.0,!=2.5.0", "pyarrow>=7.0.0", "pydantic<2"]
-unidist_deps = ["unidist[mpi]>=0.2.1"]
+mpi_deps = ["unidist[mpi]>=0.2.1"]
 spreadsheet_deps = ["modin-spreadsheet>=0.1.0"]
-all_deps = dask_deps + ray_deps + unidist_deps + spreadsheet_deps
+# Currently, Modin does not include `mpi` option in `all`.
+# Otherwise, installation of modin[all] would fail because
+# users need to have a working MPI implementation and
+# certain software installed beforehand.
+all_deps = dask_deps + ray_deps + spreadsheet_deps
 
 # Distribute 'modin-autoimport-pandas.pth' along with binary and source distributions.
 # This file provides the "import pandas before Ray init" feature if specific
@@ -58,7 +62,7 @@ def make_distribution(self):
         # can be installed by pip install modin[dask]
         "dask": dask_deps,
         "ray": ray_deps,
-        "unidist": unidist_deps,
+        "mpi": mpi_deps,
         "spreadsheet": spreadsheet_deps,
         "all": all_deps,
     },