FIX-modin-project#3413: align documentation with updated project stru…

…cture

Signed-off-by: Dmitry Chigarev <[email protected]>

docs/UsingOmnisci/index.rst

@@ -10,7 +10,7 @@ To enable this engine you could set the following environment variables:
 .. code-block:: bash
 
    export MODIN_ENGINE=native
-   export MODIN_BACKEND=omnisci
+   export MODIN_STORAGE_FORMAT=omnisci
    export MODIN_EXPERIMENTAL=true
 
 or turn it on in source code:
@@ -19,7 +19,7 @@ or turn it on in source code:
 
    import modin.config as cfg
    cfg.Engine.put('native')
-   cfg.Backend.put('omnisci')
+   cfg.StorageFormat.put('omnisci')
    cfg.IsExperimental.put(True)
 
 

docs/UsingPandasonRay/index.rst

@@ -15,12 +15,12 @@ If you want to be explicit, you could set the following environment variables:
 .. code-block:: bash
 
    export MODIN_ENGINE=ray
-   export MODIN_BACKEND=pandas
+   export MODIN_STORAGE_FORMAT=pandas
 
 or turn it on in source code:
 
 .. code-block:: python
 
    import modin.config as cfg
    cfg.Engine.put('ray')
-   cfg.Backend.put('pandas')
+   cfg.StorageFormat.put('pandas')

docs/developer/architecture.rst

@@ -56,23 +56,23 @@ For the simplicity the other backend systems - Dask and MPI are omitted and only
 * Query Executor is responsible for getting the Dataframe Algebra DAG, performing further optimizations based
   on a selected backend execution subsystem and mapping or compiling the Dataframe Algebra DAG to and actual
   execution sequence.
-* Backends module is responsible for mapping the abstract operation to an actual executor call, e.g. Pandas,
-  PyArrow, custom backend.
+* Storage formats module is responsible for mapping the abstract operation to an actual executor call, e.g. Pandas,
+  PyArrow, custom formats.
 * Orchestration subsystem is responsible for spawning and controlling the actual execution environment for the
   selected backend. It spawns the actual nodes, fires up the execution environment, e.g. Ray, monitors the state
   of executors and provides telemetry
 
 Component View
 --------------
 .. toctree::
-   ../flow/modin/engines/base/frame/index
-   ../flow/modin/engines/ray/generic
-   ../flow/modin/engines/ray/pandas_on_ray/frame/index
-   ../flow/modin/engines/ray/cudf_on_ray/frame/index
-   ../flow/modin/engines/dask/pandas_on_dask/frame/index
+   ../flow/modin/core/dataframe/pandas/index
+   ../flow/modin/core/execution/ray/generic
+   ../flow/modin/core/execution/ray/implementations/pandas_on_ray/index
+   ../flow/modin/core/execution/ray/implementations/cudf_on_ray/index
+   ../flow/modin/core/execution/dask/implementations/pandas_on_dask/index
    ../flow/modin/experimental/index
-   ../flow/modin/backends/index
-   ../flow/modin/engines/python/pandas_on_python/frame/index
+   ../flow/modin/core/storage_formats/index
+   ../flow/modin/core/execution/python/implementations/pandas_on_python/index
 
 
 DataFrame Partitioning
@@ -285,65 +285,68 @@ by documentation for now, the rest is coming soon...).
    ├───docs
    ├───examples
    ├───modin
-   │   ├─── :doc:`backends </flow/modin/backends/index>`
-   │   │   ├───base
-   │   │   │   └─── :doc:`query_compiler </flow/modin/backends/base/query_compiler>`
-   │   │   ├─── :doc:`pandas </flow/modin/backends/pandas/index>`
-   │   │   |   ├─── :doc:`parsers </flow/modin/backends/pandas/parsers>`
-   │   │   │   └─── :doc:`query_compiler </flow/modin/backends/pandas/query_compiler>`
-   │   │   └─── :doc:`pyarrow </flow/modin/backends/pyarrow/index>`
-   │   │   |   ├─── :doc:`parsers </flow/modin/backends/pyarrow/parsers>`
-   │   │   │   └─── :doc:`query_compiler </flow/modin/backends/pyarrow/query_compiler>`
    │   ├─── :doc:`config </flow/modin/config>`
-   │   ├───data_management
-   │   │   ├─── :doc:`factories </flow/modin/data_management/factories>`
-   │   │   └─── :doc:`functions </flow/modin/data_management/functions>`
+   │   ├───core
+   │   │   ├─── :doc:`dataframe </flow/modin/core/dataframe/index>`
+   │   │   │   ├─── :doc:`algebra </flow/modin/core/dataframe/algebra>`
+   │   │   │   ├─── :doc:`base </flow/modin/core/dataframe/base/index>`
+   │   │   │   │   ├───dataframe
+   │   │   │   │   └───partitioning
+   │   │   │   └─── :doc:`pandas </flow/modin/core/dataframe/pandas/index>`
+   │   │   ├───execution
+   │   │   │   ├───dask
+   │   │   │   │   ├───common
+   │   │   │   │   └───implementations
+   │   │   │   │       └─── :doc:`pandas_on_dask </flow/modin/core/execution/dask/implementations/pandas_on_dask/index>`
+   │   │   │   ├─── :doc:`dispatching </flow/modin/core/execution/dispatching>`
+   │   │   │   ├───python
+   │   │   │   │   └───implementations
+   │   │   │   │       └─── :doc:`pandas_on_python </flow/modin/core/execution/python/implementations/pandas_on_python/index>`
+   │   │   │   └───ray
+   │   │   │       ├───common
+   │   │   │       ├─── :doc:`generic </flow/modin/core/execution/ray/generic>`
+   │   │   │       └───implementations
+   │   │   │           ├─── :doc:`cudf_on_ray </flow/modin/core/execution/ray/implementations/cudf_on_ray/index>`
+   │   │   │           └─── :doc:`pandas_on_ray </flow/modin/core/execution/ray/implementations/pandas_on_ray/index>`
+   │   │   ├─── :doc:`io </flow/modin/core/io/index>`
+   │   │   └─── :doc:`storage_formats </flow/modin/core/storage_formats/index>`
+   │   │       ├─── :doc:`base </flow/modin/core/storage_formats/base/query_compiler>`
+   │   │       ├───cudf
+   │   │       ├─── :doc:`pandas </flow/modin/core/storage_formats/pandas/index>`             
+   │   │       └─── :doc:`pyarrow </flow/modin/core/storage_formats/pyarrow/index>`
    │   ├───distributed
-   │   │   └───dataframe
-   │   │       └─── :doc:`pandas </flow/modin/distributed/dataframe/pandas>`
-   │   ├───engines
-   │   │   ├───base
-   │   │   │   ├─── :doc:`frame </flow/modin/engines/base/frame/index>`
-   │   │   │   └─── :doc:`io </flow/modin/engines/base/io>`
-   │   │   ├───dask
-   │   │   │   └───pandas_on_dask
-   │   │   |       └─── :doc:`frame </flow/modin/engines/dask/pandas_on_dask/frame/index>`
-   │   │   ├───python
-   │   │   │   └───pandas_on_python
-   │   │   │       └─── :doc:`frame </flow/modin/engines/python/pandas_on_python/frame/index>`
-   │   │   └───ray
-   │   │       ├─── :doc:`generic </flow/modin/engines/ray/generic>`
-   │   │       ├───cudf_on_ray
-   │   │       │   ├─── :doc:`frame </flow/modin/engines/ray/cudf_on_ray/frame/index>`
-   │   │       │   └─── :doc:`io </flow/modin/engines/ray/cudf_on_ray/io>`
-   │   │       └───pandas_on_ray
-   │   │           └─── :doc:`frame </flow/modin/engines/ray/pandas_on_ray/frame/index>`
-   │   ├── :doc:`experimental </flow/modin/experimental/experimental>`
-   │   │   ├─── :doc:`backends </flow/modin/experimental/backends/index>`
-   │   │   │   └─── :doc:`omnisci </flow/modin/experimental/backends/omnisci/index>`
-   │   │   │       └─── :doc:`query_compiler </flow/modin/experimental/backends/omnisci/query_compiler>`
+   │   │   ├───dataframe
+   │   │   │   └─── :doc:`pandas </flow/modin/distributed/dataframe/pandas>`
+   │   ├─── :doc:`experimental </flow/modin/experimental/experimental>`
    │   │   ├───cloud
-   │   │   ├───engines
-   │   │   │   ├─── :doc:`omnisci_on_native </flow/modin/experimental/engines/omnisci_on_native/frame/index>`
-   │   │   │   ├─── :doc:`pandas_on_ray </flow/modin/experimental/engines/pandas_on_ray>`
-   │   │   │   └─── :doc:`pyarrow_on_ray </flow/modin/experimental/engines/pyarrow_on_ray>`
+   │   │   ├───core
+   │   │   │   ├───execution
+   │   │   │   │   ├───native
+   │   │   │   │   │   └───implementations
+   │   │   │   │   │       └─── :doc:`omnisci_on_native </flow/modin/experimental/core/execution/native/implementations/omnisci_on_native/index>`
+   │   │   │   │   └───ray
+   │   │   │   │       └───implementations
+   │   │   │   │           ├─── :doc:`pandas_on_ray </flow/modin/experimental/core/execution/ray/implementations/pandas_on_ray>`
+   │   │   │   │           └─── :doc:`pyarrow_on_ray </flow/modin/experimental/core/execution/ray/implementations/pyarrow_on_ray>`
+   │   │   │   └─── :doc:`storage_formats </flow/modin/experimental/core/storage_formats/index>`
+   │   │   │       └─── :doc:`omnisci </flow/modin/experimental/core/storage_formats/omnisci/index>`
    │   │   ├─── :doc:`pandas </flow/modin/experimental/pandas>`
    │   │   ├─── :doc:`sklearn </flow/modin/experimental/sklearn>`
+   │   │   ├───spreadsheet
    │   │   ├───sql
    │   │   └─── :doc:`xgboost </flow/modin/experimental/xgboost>`
    │   ├───pandas
    │   │   ├─── :doc:`dataframe </flow/modin/pandas/dataframe>`
    │   │   └─── :doc:`series </flow/modin/pandas/series>`
-   │   ├───spreadsheet
-   │   └───sql
+   │   └───spreadsheet
    ├───requirements
    ├───scripts
    └───stress_tests
 
 .. _pandas Dataframe: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html
 .. _Arrow tables: https://arrow.apache.org/docs/python/generated/pyarrow.Table.html
 .. _Ray: https://github.com/ray-project/ray
-.. _code: https://github.com/modin-project/modin/blob/master/modin/engines/base/frame/data.py
+.. _code: https://github.com/modin-project/modin/blob/master/modin/core/dataframe
 .. _Dask Futures: https://docs.dask.org/en/latest/futures.html
 .. _issue: https://github.com/modin-project/modin/issues
 .. _Discourse: https://discuss.modin.org

docs/developer/partition_api.rst

@@ -23,15 +23,15 @@ You can find the specific implementation of Modin's Partition Interface in :doc:
 
 Ray engine
 ----------
-However, it is worth noting that for Modin on ``Ray`` engine with ``pandas`` backend IPs of the remote partitions may not match
+However, it is worth noting that for Modin on ``Ray`` engine with ``pandas`` in-memory format IPs of the remote partitions may not match
 actual locations if the partitions are lower than 100 kB. Ray saves such objects (<= 100 kB, by default) in in-process store
 of the calling process (please, refer to `Ray documentation`_ for more information). We can't get IPs for such objects while maintaining good performance.
 So, you should keep in mind this for unwrapping of the remote partitions with their IPs. Several options are provided to handle the case in
 ``How to handle Ray objects that are lower 100 kB`` section.
 
 Dask engine
 -----------
-There is no mentioned above issue for Modin on ``Dask`` engine with ``pandas`` backend because ``Dask`` saves any objects
+There is no mentioned above issue for Modin on ``Dask`` engine with ``pandas`` in-memory format because ``Dask`` saves any objects
 in the worker process that processes a function (please, refer to `Dask documentation`_ for more information).
 
 How to handle Ray objects that are lower than 100 kB

docs/experimental_features/modin_xgboost.rst

@@ -9,8 +9,8 @@ Install XGBoost on Modin
 ------------------------
 
 Modin comes with all the dependencies except ``xgboost`` package by default.
-Currently, distributed XGBoost on Modin is only supported on the Ray backend, therefore, see
-the :doc:`installation page </installation>` for more information on installing Modin with the Ray backend.
+Currently, distributed XGBoost on Modin is only supported on the Ray execution engine, therefore, see
+the :doc:`installation page </installation>` for more information on installing Modin with the Ray engine.
 To install ``xgboost`` package you can use ``pip``:
 
 .. code-block:: bash

docs/flow/modin/config.rst

@@ -36,17 +36,17 @@ API.
 
     import os
 
-    # Setting `MODIN_BACKEND` environment variable.
+    # Setting `MODIN_STORAGE_FORMAT` environment variable.
     # Also can be set outside the script.
-    os.environ["MODIN_BACKEND"] = "OmniSci"
+    os.environ["MODIN_STORAGE_FORMAT"] = "OmniSci"
 
     import modin.config
     import modin.pandas as pd
 
-    # Checking initially set `Backend` config,
-    # which corresponds to `MODIN_BACKEND` environment
+    # Checking initially set `StorageFormat` config,
+    # which corresponds to `MODIN_STORAGE_FORMAT` environment
     # variable
-    print(modin.config.Backend.get()) # prints 'Omnisci'
+    print(modin.config.StorageFormat.get()) # prints 'Omnisci'
 
     # Checking default value of `NPartitions`
     print(modin.config.NPartitions.get()) # prints '8'