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In the case of highly-connected graphs, the TransitiveReduction process was far too computationally intensive. Since no operations are applied to the nodes, and the walk order is not even user visible, we don't need to sort them n^2 times.
300 lines
7.8 KiB
Go
300 lines
7.8 KiB
Go
package dag
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import (
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"fmt"
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"sort"
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"strings"
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"github.com/hashicorp/go-multierror"
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)
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// AcyclicGraph is a specialization of Graph that cannot have cycles. With
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// this property, we get the property of sane graph traversal.
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type AcyclicGraph struct {
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Graph
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}
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// WalkFunc is the callback used for walking the graph.
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type WalkFunc func(Vertex) error
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// DepthWalkFunc is a walk function that also receives the current depth of the
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// walk as an argument
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type DepthWalkFunc func(Vertex, int) error
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func (g *AcyclicGraph) DirectedGraph() Grapher {
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return g
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}
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// Returns a Set that includes every Vertex yielded by walking down from the
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// provided starting Vertex v.
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func (g *AcyclicGraph) Ancestors(v Vertex) (*Set, error) {
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s := new(Set)
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start := AsVertexList(g.DownEdges(v))
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memoFunc := func(v Vertex, d int) error {
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s.Add(v)
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return nil
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}
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if err := g.DepthFirstWalk(start, memoFunc); err != nil {
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return nil, err
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}
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return s, nil
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}
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// Returns a Set that includes every Vertex yielded by walking up from the
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// provided starting Vertex v.
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func (g *AcyclicGraph) Descendents(v Vertex) (*Set, error) {
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s := new(Set)
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start := AsVertexList(g.UpEdges(v))
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memoFunc := func(v Vertex, d int) error {
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s.Add(v)
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return nil
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}
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if err := g.ReverseDepthFirstWalk(start, memoFunc); err != nil {
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return nil, err
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}
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return s, nil
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}
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// Root returns the root of the DAG, or an error.
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//
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// Complexity: O(V)
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func (g *AcyclicGraph) Root() (Vertex, error) {
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roots := make([]Vertex, 0, 1)
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for _, v := range g.Vertices() {
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if g.UpEdges(v).Len() == 0 {
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roots = append(roots, v)
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}
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}
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if len(roots) > 1 {
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// TODO(mitchellh): make this error message a lot better
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return nil, fmt.Errorf("multiple roots: %#v", roots)
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}
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if len(roots) == 0 {
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return nil, fmt.Errorf("no roots found")
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}
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return roots[0], nil
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}
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// TransitiveReduction performs the transitive reduction of graph g in place.
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// The transitive reduction of a graph is a graph with as few edges as
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// possible with the same reachability as the original graph. This means
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// that if there are three nodes A => B => C, and A connects to both
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// B and C, and B connects to C, then the transitive reduction is the
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// same graph with only a single edge between A and B, and a single edge
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// between B and C.
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//
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// The graph must be valid for this operation to behave properly. If
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// Validate() returns an error, the behavior is undefined and the results
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// will likely be unexpected.
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//
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// Complexity: O(V(V+E)), or asymptotically O(VE)
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func (g *AcyclicGraph) TransitiveReduction() {
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// For each vertex u in graph g, do a DFS starting from each vertex
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// v such that the edge (u,v) exists (v is a direct descendant of u).
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//
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// For each v-prime reachable from v, remove the edge (u, v-prime).
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defer g.debug.BeginOperation("TransitiveReduction", "").End("")
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for _, u := range g.Vertices() {
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uTargets := g.DownEdges(u)
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vs := AsVertexList(g.DownEdges(u))
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g.depthFirstWalk(vs, false, func(v Vertex, d int) error {
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shared := uTargets.Intersection(g.DownEdges(v))
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for _, vPrime := range AsVertexList(shared) {
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g.RemoveEdge(BasicEdge(u, vPrime))
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}
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return nil
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})
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}
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}
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// Validate validates the DAG. A DAG is valid if it has a single root
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// with no cycles.
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func (g *AcyclicGraph) Validate() error {
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if _, err := g.Root(); err != nil {
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return err
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}
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// Look for cycles of more than 1 component
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var err error
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cycles := g.Cycles()
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if len(cycles) > 0 {
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for _, cycle := range cycles {
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cycleStr := make([]string, len(cycle))
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for j, vertex := range cycle {
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cycleStr[j] = VertexName(vertex)
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}
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err = multierror.Append(err, fmt.Errorf(
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"Cycle: %s", strings.Join(cycleStr, ", ")))
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}
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}
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// Look for cycles to self
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for _, e := range g.Edges() {
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if e.Source() == e.Target() {
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err = multierror.Append(err, fmt.Errorf(
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"Self reference: %s", VertexName(e.Source())))
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}
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}
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return err
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}
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func (g *AcyclicGraph) Cycles() [][]Vertex {
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var cycles [][]Vertex
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for _, cycle := range StronglyConnected(&g.Graph) {
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if len(cycle) > 1 {
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cycles = append(cycles, cycle)
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}
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}
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return cycles
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}
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// Walk walks the graph, calling your callback as each node is visited.
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// This will walk nodes in parallel if it can. Because the walk is done
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// in parallel, the error returned will be a multierror.
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func (g *AcyclicGraph) Walk(cb WalkFunc) error {
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defer g.debug.BeginOperation(typeWalk, "").End("")
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w := &Walker{Callback: cb, Reverse: true}
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w.Update(g)
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return w.Wait()
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}
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// simple convenience helper for converting a dag.Set to a []Vertex
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func AsVertexList(s *Set) []Vertex {
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rawList := s.List()
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vertexList := make([]Vertex, len(rawList))
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for i, raw := range rawList {
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vertexList[i] = raw.(Vertex)
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}
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return vertexList
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}
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type vertexAtDepth struct {
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Vertex Vertex
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Depth int
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}
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// depthFirstWalk does a depth-first walk of the graph starting from
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// the vertices in start.
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func (g *AcyclicGraph) DepthFirstWalk(start []Vertex, f DepthWalkFunc) error {
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return g.depthFirstWalk(start, true, f)
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}
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// This internal method provides the option of not sorting the vertices during
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// the walk, which we use for the Transitive reduction.
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// Some configurations can lead to fully-connected subgraphs, which makes our
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// transitive reduction algorithm O(n^3). This is still passable for the size
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// of our graphs, but the additional n^2 sort operations would make this
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// uncomputable in a reasonable amount of time.
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func (g *AcyclicGraph) depthFirstWalk(start []Vertex, sorted bool, f DepthWalkFunc) error {
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defer g.debug.BeginOperation(typeDepthFirstWalk, "").End("")
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seen := make(map[Vertex]struct{})
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frontier := make([]*vertexAtDepth, len(start))
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for i, v := range start {
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frontier[i] = &vertexAtDepth{
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Vertex: v,
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Depth: 0,
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}
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}
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for len(frontier) > 0 {
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// Pop the current vertex
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n := len(frontier)
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current := frontier[n-1]
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frontier = frontier[:n-1]
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// Check if we've seen this already and return...
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if _, ok := seen[current.Vertex]; ok {
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continue
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}
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seen[current.Vertex] = struct{}{}
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// Visit the current node
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if err := f(current.Vertex, current.Depth); err != nil {
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return err
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}
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// Visit targets of this in a consistent order.
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targets := AsVertexList(g.DownEdges(current.Vertex))
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if sorted {
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sort.Sort(byVertexName(targets))
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}
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for _, t := range targets {
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frontier = append(frontier, &vertexAtDepth{
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Vertex: t,
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Depth: current.Depth + 1,
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})
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}
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}
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return nil
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}
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// reverseDepthFirstWalk does a depth-first walk _up_ the graph starting from
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// the vertices in start.
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func (g *AcyclicGraph) ReverseDepthFirstWalk(start []Vertex, f DepthWalkFunc) error {
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defer g.debug.BeginOperation(typeReverseDepthFirstWalk, "").End("")
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seen := make(map[Vertex]struct{})
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frontier := make([]*vertexAtDepth, len(start))
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for i, v := range start {
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frontier[i] = &vertexAtDepth{
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Vertex: v,
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Depth: 0,
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}
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}
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for len(frontier) > 0 {
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// Pop the current vertex
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n := len(frontier)
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current := frontier[n-1]
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frontier = frontier[:n-1]
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// Check if we've seen this already and return...
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if _, ok := seen[current.Vertex]; ok {
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continue
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}
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seen[current.Vertex] = struct{}{}
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// Add next set of targets in a consistent order.
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targets := AsVertexList(g.UpEdges(current.Vertex))
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sort.Sort(byVertexName(targets))
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for _, t := range targets {
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frontier = append(frontier, &vertexAtDepth{
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Vertex: t,
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Depth: current.Depth + 1,
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})
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}
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// Visit the current node
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if err := f(current.Vertex, current.Depth); err != nil {
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return err
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}
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}
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return nil
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}
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// byVertexName implements sort.Interface so a list of Vertices can be sorted
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// consistently by their VertexName
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type byVertexName []Vertex
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func (b byVertexName) Len() int { return len(b) }
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func (b byVertexName) Swap(i, j int) { b[i], b[j] = b[j], b[i] }
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func (b byVertexName) Less(i, j int) bool {
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return VertexName(b[i]) < VertexName(b[j])
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}
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