Perf improvement to graph processing

core/dbt/graph/graph.py

@@ -1,6 +1,7 @@
 from typing import (
     Set, Iterable, Iterator, Optional, NewType
 )
+from itertools import product
 import networkx as nx  # type: ignore
 
 from dbt.exceptions import InternalException
@@ -77,17 +78,26 @@ def select_successors(self, selected: Set[UniqueId]) -> Set[UniqueId]:
             successors.update(self.graph.successors(node))
         return successors
 
-    def get_subset_graph(self, selected: Iterable[UniqueId]) -> 'Graph':
+    def get_subset_graph(self, selected: Iterable[UniqueId]) -> "Graph":
         """Create and return a new graph that is a shallow copy of the graph,
         but with only the nodes in include_nodes. Transitive edges across
         removed nodes are preserved as explicit new edges.
         """
-        new_graph = nx.algorithms.transitive_closure(self.graph)
 
+        new_graph = self.graph.copy()
         include_nodes = set(selected)
 
         for node in self:
             if node not in include_nodes:
+                source_nodes = [x for x, _ in new_graph.in_edges(node)]
+                target_nodes = [x for _, x in new_graph.out_edges(node)]
+
+                new_edges = product(source_nodes, target_nodes)
+                new_edges = [
+                    (source, target) for source, target in new_edges if source != target
+                ]  # removes cyclic refs
+
+                new_graph.add_edges_from(new_edges)
                 new_graph.remove_node(node)
 
         for node in include_nodes:
@@ -96,6 +106,7 @@ def get_subset_graph(self, selected: Iterable[UniqueId]) -> 'Graph':
                     "Couldn't find model '{}' -- does it exist or is "
                     "it disabled?".format(node)
                 )
+
         return Graph(new_graph)
 
     def subgraph(self, nodes: Iterable[UniqueId]) -> 'Graph':