personalized pagerank

pkg/pagerank/cache.go

@@ -0,0 +1,85 @@
+package pagerank
+
+import (
+	"context"
+	"github/pippellia-btc/crawler/pkg/graph"
+	"github/pippellia-btc/crawler/pkg/walks"
+)
+
+type walkerWithFallback struct {
+	follows  map[graph.ID][]graph.ID
+	fallback walks.Walker
+}
+
+func newWalkerWithFallback(followsMap map[graph.ID][]graph.ID, fallback walks.Walker) *walkerWithFallback {
+	return &walkerWithFallback{
+		follows:  followsMap,
+		fallback: fallback,
+	}
+}
+
+func (w *walkerWithFallback) Follows(ctx context.Context, node graph.ID) ([]graph.ID, error) {
+	follows, exists := w.follows[node]
+	if !exists {
+		var err error
+		follows, err = w.fallback.Follows(ctx, node)
+		if err != nil {
+			return nil, err
+		}
+
+		w.follows[node] = follows
+	}
+
+	return follows, nil
+}
+
+type walkPool struct {
+	walks []walks.Walk
+
+	// walkIndexes maps each node to the list of indices in walks where that node appears.
+	// That is, if walkIndexes[v] = [0, 2], then v is visited by walks[0] and walks[2].
+	walkIndexes map[graph.ID][]int
+}
+
+func newWalkPool(walks []walks.Walk) *walkPool {
+	walkIndexes := make(map[graph.ID][]int, len(walks)/100)
+
+	// add the index of the walk to each node that it visits
+	// excluding the last one which will be cropped out anyway.
+	for i, walk := range walks {
+		for j := range walk.Len() - 1 {
+			node := walk.Path[j]
+			walkIndexes[node] = append(walkIndexes[node], i)
+		}
+	}
+
+	return &walkPool{
+		walks:       walks,
+		walkIndexes: walkIndexes,
+	}
+}
+
+func (w *walkPool) Next(node graph.ID) ([]graph.ID, bool) {
+	indexes, exists := w.walkIndexes[node]
+	if !exists || len(indexes) == 0 {
+		return nil, false
+	}
+
+	for i, index := range indexes {
+		walk := w.walks[index]
+		if walk.Len() == 0 {
+			// walk already used, skip
+			continue
+		}
+
+		// zero the walk so it can't be reused, and reslice the walk indexes
+		// so we don't spend time looking at walks already used.
+		w.walks[index].Path = nil
+		w.walkIndexes[node] = indexes[i+1:]
+		return walk.Path, true
+	}
+
+	// all walks where already used
+	delete(w.walkIndexes, node)
+	return nil, false
+}

pkg/pagerank/pagerank.go

@@ -17,10 +17,11 @@ type VisitCounter interface {
 
 	// Visits returns the number of times each specified node was visited during the walks.
 	// The returned slice contains counts in the same order as the input nodes.
+	// If a node is not found, it returns 0 visits.
 	Visits(ctx context.Context, nodes ...graph.ID) ([]int, error)
 }
 
-// Global computes the global pagerank score for the specified nodes.
+// Global computes the global pagerank score for each target node, as the frequency of visits.
 // If a node is not found, its pagerank is assumed to be 0.
 func Global(ctx context.Context, count VisitCounter, nodes ...graph.ID) ([]float64, error) {
 	if len(nodes) == 0 {
@@ -50,6 +51,76 @@ func Global(ctx context.Context, count VisitCounter, nodes ...graph.ID) ([]float
 	return pageranks, nil
 }
 
+type PersonalizedLoader interface {
+	// Follows returns the follow-list of the node
+	Follows(ctx context.Context, node graph.ID) ([]graph.ID, error)
+
+	// BulkFollows returns the follow-lists of the specified nodes
+	BulkFollows(ctx context.Context, nodes []graph.ID) (map[graph.ID][]graph.ID, error)
+
+	// WalksVisitingAny returns up to limit IDs of walks that visit the specified nodes.
+	// The walks are distributed evenly among the nodes:
+	// - if limit == -1, all walks are returned.
+	// - if limit < len(nodes), no walks are returned
+	WalksVisitingAny(ctx context.Context, nodes []graph.ID, limit int) ([]walks.ID, error)
+
+	// Walks returns the walks associated with the given IDs.
+	Walks(ctx context.Context, IDs ...walks.ID) ([]walks.Walk, error)
+}
+
+/*
+Personalized computes the personalized pagerank of node by simulating a
+long random walk starting at and resetting to itself. This long walk is generated
+from the random walks stored in the storage layer.
+
+# REFERENCES
+
+[1] B. Bahmani, A. Chowdhury, A. Goel; "Fast Incremental and Personalized PageRank"
+URL: http://snap.stanford.edu/class/cs224w-readings/bahmani10pagerank.pdf
+*/
+func Personalized(
+	ctx context.Context,
+	loader PersonalizedLoader,
+	source graph.ID,
+	targetLenght int) (map[graph.ID]float64, error) {
+
+	follows, err := loader.Follows(ctx, source)
+	if err != nil {
+		return nil, fmt.Errorf("Personalized: failed to fetch the follows of source: %w", err)
+	}
+
+	if len(follows) == 0 {
+		// the special distribution of a dandling node
+		return map[graph.ID]float64{source: 1.0}, nil
+	}
+
+	followMap, err := loader.BulkFollows(ctx, follows)
+	if err != nil {
+		return nil, fmt.Errorf("Personalized: failed to fetch the two-hop network of source: %w", err)
+	}
+
+	targetWalks := int(float64(targetLenght) * (1 - walks.Alpha))
+	IDs, err := loader.WalksVisitingAny(ctx, append(follows, source), targetWalks)
+	if err != nil {
+		return nil, fmt.Errorf("Personalized: failed to fetch the walk IDs: %w", err)
+	}
+
+	walks, err := loader.Walks(ctx, IDs...)
+	if err != nil {
+		return nil, fmt.Errorf("Personalized: failed to fetch the walks: %w", err)
+	}
+
+	walker := newWalkerWithFallback(followMap, loader)
+	pool := newWalkPool(walks)
+
+	walk, err := personalizedWalk(ctx, walker, pool, source, targetLenght)
+	if err != nil {
+		return nil, err
+	}
+
+	return frequencies(walk), nil
+}
+
 // pWalk is a personalized walk, which is a random walk that resets to a specified node
 // and continues until it reaches a specified target lenght.
 type pWalk struct {
@@ -144,6 +215,22 @@ func personalizedWalk(
 	}
 }
 
+// frequencies returns the number of times each node is visited divided by the lenght of the path.
+func frequencies(path []graph.ID) map[graph.ID]float64 {
+	if len(path) == 0 {
+		return nil
+	}
+
+	total := len(path)
+	freq := 1.0 / float64(total)
+	pp := make(map[graph.ID]float64, total/100)
+	for _, node := range path {
+		pp[node] += freq
+	}
+
+	return pp
+}
+
 // returns a random element of a slice. It panics if the slice is empty or nil.
 func randomElement[S []E, E any](s S) E {
 	return s[rand.IntN(len(s))]