optimize mark dnr nodes algorithm

* Compute largest depth of each node and traverse graph by depth. This
allows us to check a node once, and only once, to determine if it needs
to be marked for do not run.

awx/main/scheduler/dag_simple.py

@@ -1,8 +1,11 @@
 
+
 class SimpleDAG(object):
     ''' A simple implementation of a directed acyclic graph '''
 
     def __init__(self):
+        # Depth
+        self.depth = [set([])]
         self.nodes = []
         self.root_nodes = set([])
 
@@ -99,6 +102,8 @@ class SimpleDAG(object):
         gv_file.close()
 
     def add_node(self, obj, metadata=None):
+        if not metadata:
+            metadata = dict()
         if self.find_ord(obj) is None:
             '''
             Assume node is a root node until a child is added
@@ -109,6 +114,11 @@ class SimpleDAG(object):
             entry = dict(node_object=obj, metadata=metadata)
             self.nodes.append(entry)
 
+            # Depth
+            metadata['depth'] = 0
+            self.depth[0].add(node_index)
+            return node_index
+
     def add_edge(self, from_obj, to_obj, label):
         from_obj_ord = self.find_ord(from_obj)
         to_obj_ord = self.find_ord(to_obj)
@@ -133,6 +143,19 @@ class SimpleDAG(object):
         self.node_from_edges_by_label[label][from_obj_ord].append(to_obj_ord)
         self.node_to_edges_by_label[label][to_obj_ord].append(from_obj_ord)
 
+        # Depth
+        parent_depth = self.nodes[from_obj_ord]['metadata']['depth']
+        current_depth = self.nodes[to_obj_ord]['metadata']['depth']
+        if parent_depth >= current_depth:
+            if len(self.depth) <= parent_depth + 1:
+                self.depth.append(set([]))
+
+            self.nodes[to_obj_ord]['metadata']['depth'] = parent_depth + 1
+
+            self.depth[current_depth].remove(to_obj_ord)
+            self.depth[parent_depth + 1].add(to_obj_ord)
+
+
     def find_ord(self, obj):
         return self.node_obj_to_node_index.get(obj, None)
 

awx/main/scheduler/dag_workflow.py

@@ -1,6 +1,5 @@
 
 # Python
-import copy
 from awx.main.models import (
     WorkflowJobTemplateNode,
     WorkflowJobNode,
@@ -201,13 +200,12 @@ class WorkflowDAG(SimpleDAG):
 
     def mark_dnr_nodes(self):
         root_nodes = self.get_root_nodes()
-        nodes = copy.copy(root_nodes)
         nodes_marked_do_not_run = []
 
-        for index, node in enumerate(nodes):
-            obj = node['node_object']
-
-            if obj.do_not_run is False and not obj.job:
+        for node_indexes in self.depth:
+            for node_index in node_indexes:
+                node = self.nodes[node_index]
+                obj = node['node_object']
                 parent_nodes = [p['node_object'] for p in self.get_dependents(obj)]
                 if self._are_all_nodes_dnr_decided(parent_nodes):
                     if obj.unified_job_template is None:
@@ -216,8 +214,4 @@ class WorkflowDAG(SimpleDAG):
                     elif node not in root_nodes and self._should_mark_node_dnr(node, parent_nodes):
                         obj.do_not_run = True
                         nodes_marked_do_not_run.append(node)
-
-            nodes.extend(self.get_dependencies(obj, 'success_nodes') +
-                         self.get_dependencies(obj, 'failure_nodes') +
-                         self.get_dependencies(obj, 'always_nodes'))
         return [n['node_object'] for n in nodes_marked_do_not_run]