Optimize the drop-duplicate functionality

python/cugraph/cugraph/structure/graph_implementation/simpleDistributedGraph.py

@@ -39,6 +39,7 @@
 )
 from cugraph.dask.common.mg_utils import run_gc_on_dask_cluster
 import cugraph.dask.comms.comms as Comms
+from cugraph.structure.symmetrize import _memory_efficient_drop_duplicates
 
 
 class simpleDistributedGraphImpl:
@@ -95,6 +96,7 @@ def _make_plc_graph(
         weight_type,
         edge_id_type,
         edge_type_id,
+        drop_multi_edges,
     ):
         weights = None
         edge_ids = None
@@ -149,6 +151,7 @@ def _make_plc_graph(
             num_arrays=num_arrays,
             store_transposed=store_transposed,
             do_expensive_check=False,
+            drop_multi_edges=drop_multi_edges,
         )
         del edata_x
         gc.collect()
@@ -267,7 +270,7 @@ def __from_edgelist(
                 input_ddf,
                 source,
                 destination,
-                multi=self.properties.multi_edge,
+                multi=True,  # Deprecated parameter
                 symmetrize=not self.properties.directed,
             )
             value_col = None
@@ -277,7 +280,7 @@ def __from_edgelist(
                 source,
                 destination,
                 value_col_names,
-                multi=self.properties.multi_edge,
+                multi=True,  # Deprecated parameter
                 symmetrize=not self.properties.directed,
             )
 
@@ -364,6 +367,7 @@ def __from_edgelist(
                 self.weight_type,
                 self.edge_id_type,
                 self.edge_type_id_type,
+                not self.properties.multi_edge,
             )
             for w, edata in persisted_keys_d.items()
         }
@@ -455,6 +459,15 @@ def view_edge_list(self):
                 else:
                     is_multi_column = True
 
+            if not self.properties.multi_edge:
+                # Drop parallel edges for non MultiGraph
+                # FIXME: Drop multi edges with the CAPI instead.
+                _client = default_client()
+                workers = _client.scheduler_info()["workers"]
+                edgelist_df = _memory_efficient_drop_duplicates(
+                    edgelist_df, [srcCol, dstCol], len(workers)
+                )
+
             edgelist_df[srcCol], edgelist_df[dstCol] = edgelist_df[
                 [srcCol, dstCol]
             ].min(axis=1), edgelist_df[[srcCol, dstCol]].max(axis=1)

python/cugraph/cugraph/structure/graph_implementation/simpleGraph.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2021-2023, NVIDIA CORPORATION.
+# Copyright (c) 2021-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -264,7 +264,7 @@ def __from_edgelist(
                 source,
                 destination,
                 edge_attr,
-                multi=self.properties.multi_edge,
+                multi=self.properties.multi_edge,  # Deprecated parameter
                 symmetrize=not self.properties.directed,
             )
 
@@ -279,7 +279,7 @@ def __from_edgelist(
                 elist,
                 source,
                 destination,
-                multi=self.properties.multi_edge,
+                multi=self.properties.multi_edge,  # Deprecated parameter
                 symmetrize=not self.properties.directed,
             )
 
@@ -298,7 +298,10 @@ def __from_edgelist(
             self._replicate_edgelist()
 
         self._make_plc_graph(
-            value_col=value_col, store_transposed=store_transposed, renumber=renumber
+            value_col=value_col,
+            store_transposed=store_transposed,
+            renumber=renumber,
+            drop_multi_edges=not self.properties.multi_edge,
         )
 
     def to_pandas_edgelist(
@@ -477,13 +480,15 @@ def view_edge_list(self):
                     edgelist_df[simpleGraphImpl.srcCol]
                     <= edgelist_df[simpleGraphImpl.dstCol]
                 ]
+
         elif not use_initial_input_df and self.properties.renumbered:
             # Do not unrenumber the vertices if the initial input df was used
             if not self.properties.directed:
                 edgelist_df = edgelist_df[
                     edgelist_df[simpleGraphImpl.srcCol]
                     <= edgelist_df[simpleGraphImpl.dstCol]
                 ]
+
             edgelist_df = self.renumber_map.unrenumber(
                 edgelist_df, simpleGraphImpl.srcCol
             )
@@ -1084,6 +1089,7 @@ def _make_plc_graph(
         value_col: Dict[str, cudf.DataFrame] = None,
         store_transposed: bool = False,
         renumber: bool = True,
+        drop_multi_edges: bool = False,
     ):
         """
         Parameters
@@ -1100,6 +1106,8 @@ def _make_plc_graph(
             Whether to renumber the vertices of the graph.
             Required if inputted vertex ids are not of
             int32 or int64 type.
+        drop_multi_edges: bool (default=False)
+            Whether to drop multi edges
         """
 
         if value_col is None:
@@ -1163,6 +1171,7 @@ def _make_plc_graph(
             renumber=renumber,
             do_expensive_check=True,
             input_array_format=input_array_format,
+            drop_multi_edges=drop_multi_edges,
         )
 
     def to_directed(self, DiG, store_transposed=False):

python/cugraph/cugraph/structure/symmetrize.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019-2023, NVIDIA CORPORATION.
+# Copyright (c) 2019-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -15,6 +15,7 @@
 import cudf
 import dask_cudf
 from dask.distributed import default_client
+import warnings
 
 
 def symmetrize_df(
@@ -54,6 +55,11 @@ def symmetrize_df(
         Name of the column in the data frame containing the weight ids
 
     multi : bool, optional (default=False)
+        [Deprecated,  Multi will be removed in future version,  and the removal
+        of multi edges will no longer be supported from 'symmetrize'.
+        Multi edges will be removed upon  creation of graph instance directly
+        based on if the graph is `curgaph.MultiGraph` or `cugraph.Graph`.]
+
         Set to True if graph is a Multi(Di)Graph. This allows multiple
         edges instead of dropping them.
 
@@ -84,6 +90,12 @@ def symmetrize_df(
     if multi:
         return result
     else:
+        warnings.warn(
+            "Multi is deprecated and the removal of multi edges will no longer be "
+            "supported from 'symmetrize'. Multi edges will be removed upon creation "
+            "of graph instance.",
+            FutureWarning,
+        )
         vertex_col_name = src_name + dst_name
         result = result.groupby(by=[*vertex_col_name], as_index=False).min()
         return result
@@ -128,6 +140,11 @@ def symmetrize_ddf(
         Name of the column in the data frame containing the weight ids
 
     multi : bool, optional (default=False)
+        [Deprecated,  Multi will be removed in future version,  and the removal
+        of multi edges will no longer be supported from 'symmetrize'.
+        Multi edges will be removed upon  creation of graph instance directly
+        based on if the graph is `curgaph.MultiGraph` or `cugraph.Graph`.]
+
         Set to True if graph is a Multi(Di)Graph. This allows multiple
         edges instead of dropping them.
 
@@ -165,8 +182,15 @@ def symmetrize_ddf(
     else:
         result = ddf
     if multi:
+        result = result.reset_index(drop=True).repartition(npartitions=len(workers) * 2)
         return result
     else:
+        warnings.warn(
+            "Multi is deprecated and the removal of multi edges will no longer be "
+            "supported from 'symmetrize'. Multi edges will be removed upon creation "
+            "of graph instance.",
+            FutureWarning,
+        )
         vertex_col_name = src_name + dst_name
         result = _memory_efficient_drop_duplicates(
             result, vertex_col_name, len(workers)
@@ -181,6 +205,7 @@ def symmetrize(
     value_col_name=None,
     multi=False,
     symmetrize=True,
+    do_expensive_check=False,
 ):
     """
     Take a dataframe of source destination pairs along with associated
@@ -208,6 +233,11 @@ def symmetrize(
         weights column name.
 
     multi : bool, optional (default=False)
+        [Deprecated,  Multi will be removed in future version,  and the removal
+        of multi edges will no longer be supported from 'symmetrize'.
+        Multi edges will be removed upon  creation of graph instance directly
+        based on if the graph is `curgaph.MultiGraph` or `cugraph.Graph`.]
+
         Set to True if graph is a Multi(Di)Graph. This allows multiple
         edges instead of dropping them.
 
@@ -234,8 +264,9 @@ def symmetrize(
     if "edge_id" in input_df.columns and symmetrize:
         raise ValueError("Edge IDs are not supported on undirected graphs")
 
-    csg.null_check(input_df[source_col_name])
-    csg.null_check(input_df[dest_col_name])
+    if do_expensive_check:  # FIXME: Optimize this check as it is currently expensive
+        csg.null_check(input_df[source_col_name])
+        csg.null_check(input_df[dest_col_name])
 
     if isinstance(input_df, dask_cudf.DataFrame):
         output_df = symmetrize_ddf(

python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample_mg.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2023, NVIDIA CORPORATION.
+# Copyright (c) 2022-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -26,6 +26,7 @@
 from cugraph.testing import UNDIRECTED_DATASETS
 from cugraph.dask import uniform_neighbor_sample
 from cugraph.dask.common.mg_utils import is_single_gpu
+from cugraph.structure.symmetrize import _memory_efficient_drop_duplicates
 from cugraph.datasets import email_Eu_core, small_tree
 from pylibcugraph.testing.utils import gen_fixture_params_product
 
@@ -135,6 +136,14 @@ def test_mg_uniform_neighbor_sample_simple(dask_client, input_combo):
     dg = input_combo["MGGraph"]
 
     input_df = dg.input_df
+    # Drop parallel edges for non MultiGraph
+    # FIXME: Drop multi edges with the CAPI instead.
+    vertex_col_name = ["src", "dst"]
+    workers = dask_client.scheduler_info()["workers"]
+    input_df = _memory_efficient_drop_duplicates(
+        input_df, vertex_col_name, len(workers)
+    )
+
     result_nbr = uniform_neighbor_sample(
         dg,
         input_combo["start_list"],

python/pylibcugraph/pylibcugraph/graphs.pyx

@@ -463,9 +463,9 @@ cdef class MGGraph(_GPUGraph):
             edge_type_view_ptr_ptr,
             store_transposed,
             num_arrays,
-            do_expensive_check,
             drop_self_loops,
             drop_multi_edges,
+            do_expensive_check,
             &(self.c_graph_ptr),
             &error_ptr)