FEAT-#7139: Use ray-core instead of ray-default

README.md

@@ -76,6 +76,10 @@ Otherwise, installation of `modin[mpi]` may fail. Refer to
 [Installing with pip](https://unidist.readthedocs.io/en/latest/installation.html#installing-with-pip)
 section of the unidist documentation for more details about installation.
 
+**Note:** Since Modin 0.30.0 we use a reduced set of Ray dependencies: `ray` instead of `ray[default]`.
+This means that the dashboard and cluster launcher are no longer installed by default.
+If you need those, consider installing `ray[default]` along with `modin[ray]`.
+
 Modin automatically detects which engine(s) you have installed and uses that for scheduling computation.
 
 #### From conda-forge
@@ -97,6 +101,10 @@ conda install -c conda-forge modin-mpi # Install Modin dependencies and MPI thro
 conda install -c conda-forge modin-hdk # Install Modin dependencies and HDK.
 ```
 
+**Note:** Since Modin 0.30.0 we use a reduced set of Ray dependencies: `ray-core` instead of `ray-default`.
+This means that the dashboard and cluster launcher are no longer installed by default.
+If you need those, consider installing `ray-default` along with `modin-ray`.
+
 Refer to
 [Installing with conda](https://unidist.readthedocs.io/en/latest/installation.html#installing-with-conda)
 section of the unidist documentation for more details on how to install a specific MPI implementation to run on.

docs/getting_started/installation.rst

@@ -40,6 +40,10 @@ it is required to have a working MPI implementation installed beforehand.
 Otherwise, installation of ``modin[mpi]`` may fail. Refer to
 `Installing with pip`_ section of the unidist documentation for more details about installation.
 
+**Note:** Since Modin 0.30.0 we use a reduced set of Ray dependencies: `ray` instead of `ray[default]`.
+This means that the dashboard and cluster launcher are no longer installed by default.
+If you need those, consider installing `ray[default]` along with `modin[ray]`.
+
 Modin will automatically detect which engine you have installed and use that for
 scheduling computation! See below for HDK engine installation.
 
@@ -129,6 +133,10 @@ it is possible to install modin with chosen engine(s) alongside. Current options
 | modin-all                       | Dask, Ray, Unidist, HDK   |          Linux              |
 +---------------------------------+---------------------------+-----------------------------+
 
+**Note:** Since Modin 0.30.0 we use a reduced set of Ray dependencies: `ray-core` instead of `ray-default`.
+This means that the dashboard and cluster launcher are no longer installed by default.
+If you need those, consider installing `ray-default` along with `modin-ray`.
+
 For installing Dask, Ray and MPI through unidist engines into conda environment following command should be used:
 
 .. code-block:: bash

docs/requirements-doc.txt

@@ -13,7 +13,7 @@ recommonmark
 sphinx<6.0.0
 sphinx-click
 # ray==2.5.0 broken: https://github.com/conda-forge/ray-packages-feedstock/issues/100
-ray[default]>=2.1.0,!=2.5.0
+ray>=2.1.0,!=2.5.0
 # Override to latest version of modin-spreadsheet
 git+https://github.com/modin-project/modin-spreadsheet.git@49ffd89f683f54c311867d602c55443fb11bf2a5
 sphinxcontrib_plantuml

environment-dev.yml

@@ -13,7 +13,7 @@ dependencies:
 
   # optional dependencies
   # ray==2.5.0 broken: https://github.com/conda-forge/ray-packages-feedstock/issues/100
-  - ray-default>=2.1.0,!=2.5.0
+  - ray-core>=2.1.0,!=2.5.0
   - pyarrow>=7.0.0
   # workaround for https://github.com/conda/conda/issues/11744
   - grpcio!=1.45.*

modin/core/execution/ray/common/deferred_execution.py

@@ -30,13 +30,12 @@
 import pandas
 import ray
 from ray._private.services import get_node_ip_address
-from ray.util.client.common import ClientObjectRef
 
 from modin.config import RayTaskCustomResources
 from modin.core.execution.ray.common import MaterializationHook, RayWrapper
 from modin.logging import get_logger
 
-ObjectRefType = Union[ray.ObjectRef, ClientObjectRef, None]
+ObjectRefType = Union[ray.ObjectRef, None]
 ObjectRefOrListType = Union[ObjectRefType, List[ObjectRefType]]
 ListOrTuple = (list, tuple)
 
@@ -478,7 +477,7 @@ class MetaList:
     obj : ray.ObjectID or list
     """
 
-    def __init__(self, obj: Union[ray.ObjectID, ClientObjectRef, List]):
+    def __init__(self, obj: Union[ray.ObjectID, List]):
         self._obj = obj
 
     def __getitem__(self, index):

modin/core/execution/ray/common/engine_wrapper.py

@@ -24,7 +24,6 @@
 
 import pandas
 import ray
-from ray.util.client.common import ClientObjectRef
 
 from modin.config import RayTaskCustomResources
 from modin.error_message import ErrorMessage
@@ -129,14 +128,14 @@ def materialize(cls, obj_id):
             obj = obj_id.pre_materialize()
             return (
                 obj_id.post_materialize(ray.get(obj))
-                if isinstance(obj, RayObjectRefTypes)
+                if isinstance(obj, ray.ObjectRef)
                 else obj
             )
 
         if not isinstance(obj_id, Sequence):
-            return ray.get(obj_id) if isinstance(obj_id, RayObjectRefTypes) else obj_id
+            return ray.get(obj_id) if isinstance(obj_id, ray.ObjectRef) else obj_id
 
-        if all(isinstance(obj, RayObjectRefTypes) for obj in obj_id):
+        if all(isinstance(obj, ray.ObjectRef) for obj in obj_id):
             return ray.get(obj_id)
 
         ids = {}
@@ -147,7 +146,7 @@ def materialize(cls, obj_id):
                 continue
             if isinstance(obj, MaterializationHook):
                 oid = obj.pre_materialize()
-                if isinstance(oid, RayObjectRefTypes):
+                if isinstance(oid, ray.ObjectRef):
                     hook = obj
                     obj = oid
                 else:
@@ -231,7 +230,7 @@ def wait(cls, obj_ids, num_returns=None):
         for obj in obj_ids:
             if isinstance(obj, MaterializationHook):
                 obj = obj.pre_materialize()
-            if isinstance(obj, RayObjectRefTypes):
+            if isinstance(obj, ray.ObjectRef):
                 ids.add(obj)
 
         if num_ids := len(ids):
@@ -332,5 +331,4 @@ def __reduce__(self):
         return int, (data,)
 
 
-RayObjectRefTypes = (ray.ObjectRef, ClientObjectRef)
-ObjectRefTypes = (*RayObjectRefTypes, MaterializationHook)
+ObjectRefTypes = (ray.ObjectRef, MaterializationHook)

modin/core/execution/ray/implementations/pandas_on_ray/partitioning/partition.py

@@ -13,14 +13,11 @@
 
 """Module houses class that wraps data (block partition) and its metadata."""
 
-from typing import TYPE_CHECKING, Callable, Union
+from typing import Callable, Union
 
 import pandas
 import ray
 
-if TYPE_CHECKING:
-    from ray.util.client.common import ClientObjectRef
-
 from modin.config import LazyExecution, RayTaskCustomResources
 from modin.core.dataframe.pandas.partitioning.partition import PandasDataframePartition
 from modin.core.execution.ray.common import MaterializationHook, RayWrapper
@@ -60,7 +57,7 @@ class PandasOnRayDataframePartition(PandasDataframePartition):
 
     def __init__(
         self,
-        data: Union[ray.ObjectRef, "ClientObjectRef", DeferredExecution],
+        data: Union[ray.ObjectRef, DeferredExecution],
         length: int = None,
         width: int = None,
         ip: str = None,
@@ -328,7 +325,7 @@ def ip(self, materialize=True):
         return ip
 
     @property
-    def _data(self) -> Union[ray.ObjectRef, "ClientObjectRef"]:  # noqa: GL08
+    def _data(self) -> ray.ObjectRef:  # noqa: GL08
         self.drain_call_queue()
         return self._data_ref
 

requirements-dev.txt

@@ -7,7 +7,7 @@ psutil>=5.8.0
 
 ## optional dependencies
 # ray==2.5.0 broken: https://github.com/conda-forge/ray-packages-feedstock/issues/100
-ray[default]>=2.1.0,!=2.5.0
+ray>=2.1.0,!=2.5.0
 pyarrow>=7.0.0
 dask[complete]>=2.22.0
 distributed>=2.22.0

setup.py

@@ -7,7 +7,7 @@
 
 dask_deps = ["dask>=2.22.0", "distributed>=2.22.0"]
 # ray==2.5.0 broken: https://github.com/conda-forge/ray-packages-feedstock/issues/100
-ray_deps = ["ray[default]>=2.1.0,!=2.5.0", "pyarrow>=7.0.0"]
+ray_deps = ["ray>=2.1.0,!=2.5.0", "pyarrow>=7.0.0"]
 mpi_deps = ["unidist[mpi]>=0.2.1"]
 consortium_standard_deps = ["dataframe-api-compat>=0.2.7"]
 spreadsheet_deps = ["modin-spreadsheet>=0.1.0"]