chore(server): Import layer grouping logic into server component

2 files changed, 361 insertions, 0 deletions

diff --git a/tools/nixery/server/go-deps.nix b/tools/nixery/server/go-deps.nix
index a223ef0a7021..7c40c6dde0f1 100644
--- a/tools/nixery/server/go-deps.nix
+++ b/tools/nixery/server/go-deps.nix
@@ -108,4 +108,13 @@
       sha256 = "05wig23l2sil3bfdv19gq62sya7hsabqj9l8pzr1sm57qsvj218d";
     };
   }
+  {
+    goPackagePath = "gonum.org/v1/gonum";
+    fetch = {
+      type = "git";
+      url = "https://github.com/gonum/gonum";
+      rev = "ced62fe5104b907b6c16cb7e575c17b2e62ceddd";
+      sha256 = "1b7q6haabnp53igpmvr6a2414yralhbrldixx4kbxxg1apy8jdjg";
+    };
+  }
 ]
diff --git a/tools/nixery/server/layers/grouping.go b/tools/nixery/server/layers/grouping.go
new file mode 100644
index 000000000000..a75046e0fa3e
--- /dev/null
+++ b/tools/nixery/server/layers/grouping.go
@@ -0,0 +1,352 @@
+// This program reads an export reference graph (i.e. a graph representing the
+// runtime dependencies of a set of derivations) created by Nix and groups them
+// in a way that is likely to match the grouping for other derivation sets with
+// overlapping dependencies.
+//
+// This is used to determine which derivations to include in which layers of a
+// container image.
+//
+// # Inputs
+//
+// * a graph of Nix runtime dependencies, generated via exportReferenceGraph
+// * a file containing absolute popularity values of packages in the
+//   Nix package set (in the form of a direct reference count)
+// * a maximum number of layers to allocate for the image (the "layer budget")
+//
+// # Algorithm
+//
+// It works by first creating a (directed) dependency tree:
+//
+// img (root node)
+// │
+// ├───> A ─────┐
+// │            v
+// ├───> B ───> E
+// │            ^
+// ├───> C ─────┘
+// │     │
+// │     v
+// └───> D ───> F
+//       │
+//       └────> G
+//
+// Each node (i.e. package) is then visited to determine how important
+// it is to separate this node into its own layer, specifically:
+//
+// 1. Is the node within a certain threshold percentile of absolute
+//    popularity within all of nixpkgs? (e.g. `glibc`, `openssl`)
+//
+// 2. Is the node's runtime closure above a threshold size? (e.g. 100MB)
+//
+// In either case, a bit is flipped for this node representing each
+// condition and an edge to it is inserted directly from the image
+// root, if it does not already exist.
+//
+// For the rest of the example we assume 'G' is above the threshold
+// size and 'E' is popular.
+//
+// This tree is then transformed into a dominator tree:
+//
+// img
+// │
+// ├───> A
+// ├───> B
+// ├───> C
+// ├───> E
+// ├───> D ───> F
+// └───> G
+//
+// Specifically this means that the paths to A, B, C, E, G, and D
+// always pass through the root (i.e. are dominated by it), whilst F
+// is dominated by D (all paths go through it).
+//
+// The top-level subtrees are considered as the initially selected
+// layers.
+//
+// If the list of layers fits within the layer budget, it is returned.
+//
+// Otherwise, a merge rating is calculated for each layer. This is the
+// product of the layer's total size and its root node's popularity.
+//
+// Layers are then merged in ascending order of merge ratings until
+// they fit into the layer budget.
+//
+// # Threshold values
+//
+// Threshold values for the partitioning conditions mentioned above
+// have not yet been determined, but we will make a good first guess
+// based on gut feeling and proceed to measure their impact on cache
+// hits/misses.
+//
+// # Example
+//
+// Using the logic described above as well as the example presented in
+// the introduction, this program would create the following layer
+// groupings (assuming no additional partitioning):
+//
+// Layer budget: 1
+// Layers: { A, B, C, D, E, F, G }
+//
+// Layer budget: 2
+// Layers: { G }, { A, B, C, D, E, F }
+//
+// Layer budget: 3
+// Layers: { G }, { E }, { A, B, C, D, F }
+//
+// Layer budget: 4
+// Layers: { G }, { E }, { D, F }, { A, B, C }
+//
+// ...
+//
+// Layer budget: 10
+// Layers: { E }, { D, F }, { A }, { B }, { C }
+package layers
+
+import (
+	"encoding/json"
+	"flag"
+	"io/ioutil"
+	"log"
+	"regexp"
+	"sort"
+
+	"gonum.org/v1/gonum/graph/flow"
+	"gonum.org/v1/gonum/graph/simple"
+)
+
+// closureGraph represents the structured attributes Nix outputs when asking it
+// for the exportReferencesGraph of a list of derivations.
+type exportReferences struct {
+	References struct {
+		Graph []string `json:"graph"`
+	} `json:"exportReferencesGraph"`
+
+	Graph []struct {
+		Size uint64   `json:"closureSize"`
+		Path string   `json:"path"`
+		Refs []string `json:"references"`
+	} `json:"graph"`
+}
+
+// Popularity data for each Nix package that was calculated in advance.
+//
+// Popularity is a number from 1-100 that represents the
+// popularity percentile in which this package resides inside
+// of the nixpkgs tree.
+type Popularity = map[string]int
+
+// layer represents the data returned for each layer that Nix should
+// build for the container image.
+type layer struct {
+	Contents    []string `json:"contents"`
+	mergeRating uint64
+}
+
+func (a layer) merge(b layer) layer {
+	a.Contents = append(a.Contents, b.Contents...)
+	a.mergeRating += b.mergeRating
+	return a
+}
+
+// closure as pointed to by the graph nodes.
+type closure struct {
+	GraphID    int64
+	Path       string
+	Size       uint64
+	Refs       []string
+	Popularity int
+}
+
+func (c *closure) ID() int64 {
+	return c.GraphID
+}
+
+var nixRegexp = regexp.MustCompile(`^/nix/store/[a-z0-9]+-`)
+
+func (c *closure) DOTID() string {
+	return nixRegexp.ReplaceAllString(c.Path, "")
+}
+
+// bigOrPopular checks whether this closure should be considered for
+// separation into its own layer, even if it would otherwise only
+// appear in a subtree of the dominator tree.
+func (c *closure) bigOrPopular() bool {
+	const sizeThreshold = 100 * 1000000 // 100MB
+
+	if c.Size > sizeThreshold {
+		return true
+	}
+
+	// The threshold value used here is currently roughly the
+	// minimum number of references that only 1% of packages in
+	// the entire package set have.
+	//
+	// TODO(tazjin): Do this more elegantly by calculating
+	// percentiles for each package and using those instead.
+	if c.Popularity >= 1000 {
+		return true
+	}
+
+	return false
+}
+
+func insertEdges(graph *simple.DirectedGraph, cmap *map[string]*closure, node *closure) {
+	// Big or popular nodes get a separate edge from the top to
+	// flag them for their own layer.
+	if node.bigOrPopular() && !graph.HasEdgeFromTo(0, node.ID()) {
+		edge := graph.NewEdge(graph.Node(0), node)
+		graph.SetEdge(edge)
+	}
+
+	for _, c := range node.Refs {
+		// Nix adds a self reference to each node, which
+		// should not be inserted.
+		if c != node.Path {
+			edge := graph.NewEdge(node, (*cmap)[c])
+			graph.SetEdge(edge)
+		}
+	}
+}
+
+// Create a graph structure from the references supplied by Nix.
+func buildGraph(refs *exportReferences, pop *Popularity) *simple.DirectedGraph {
+	cmap := make(map[string]*closure)
+	graph := simple.NewDirectedGraph()
+
+	// Insert all closures into the graph, as well as a fake root
+	// closure which serves as the top of the tree.
+	//
+	// A map from store paths to IDs is kept to actually insert
+	// edges below.
+	root := &closure{
+		GraphID: 0,
+		Path:    "image_root",
+	}
+	graph.AddNode(root)
+
+	for idx, c := range refs.Graph {
+		node := &closure{
+			GraphID: int64(idx + 1), // inc because of root node
+			Path:    c.Path,
+			Size:    c.Size,
+			Refs:    c.Refs,
+		}
+
+		if p, ok := (*pop)[node.DOTID()]; ok {
+			node.Popularity = p
+		} else {
+			node.Popularity = 1
+		}
+
+		graph.AddNode(node)
+		cmap[c.Path] = node
+	}
+
+	// Insert the top-level closures with edges from the root
+	// node, then insert all edges for each closure.
+	for _, p := range refs.References.Graph {
+		edge := graph.NewEdge(root, cmap[p])
+		graph.SetEdge(edge)
+	}
+
+	for _, c := range cmap {
+		insertEdges(graph, &cmap, c)
+	}
+
+	return graph
+}
+
+// Extracts a subgraph starting at the specified root from the
+// dominator tree. The subgraph is converted into a flat list of
+// layers, each containing the store paths and merge rating.
+func groupLayer(dt *flow.DominatorTree, root *closure) layer {
+	size := root.Size
+	contents := []string{root.Path}
+	children := dt.DominatedBy(root.ID())
+
+	// This iteration does not use 'range' because the list being
+	// iterated is modified during the iteration (yes, I'm sorry).
+	for i := 0; i < len(children); i++ {
+		child := children[i].(*closure)
+		size += child.Size
+		contents = append(contents, child.Path)
+		children = append(children, dt.DominatedBy(child.ID())...)
+	}
+
+	return layer{
+		Contents: contents,
+		// TODO(tazjin): The point of this is to factor in
+		// both the size and the popularity when making merge
+		// decisions, but there might be a smarter way to do
+		// it than a plain multiplication.
+		mergeRating: uint64(root.Popularity) * size,
+	}
+}
+
+// Calculate the dominator tree of the entire package set and group
+// each top-level subtree into a layer.
+//
+// Layers are merged together until they fit into the layer budget,
+// based on their merge rating.
+func dominate(budget int, graph *simple.DirectedGraph) []layer {
+	dt := flow.Dominators(graph.Node(0), graph)
+
+	var layers []layer
+	for _, n := range dt.DominatedBy(dt.Root().ID()) {
+		layers = append(layers, groupLayer(&dt, n.(*closure)))
+	}
+
+	sort.Slice(layers, func(i, j int) bool {
+		return layers[i].mergeRating < layers[j].mergeRating
+	})
+
+	if len(layers) > budget {
+		log.Printf("Ideal image has %v layers, but budget is %v\n", len(layers), budget)
+	}
+
+	for len(layers) > budget {
+		merged := layers[0].merge(layers[1])
+		layers[1] = merged
+		layers = layers[1:]
+	}
+
+	return layers
+}
+
+func main() {
+	graphFile := flag.String("graph", ".attrs.json", "Input file containing graph")
+	popFile := flag.String("pop", "popularity.json", "Package popularity data")
+	outFile := flag.String("out", "layers.json", "File to write layers to")
+	layerBudget := flag.Int("budget", 94, "Total layer budget available")
+	flag.Parse()
+
+	// Parse graph data
+	file, err := ioutil.ReadFile(*graphFile)
+	if err != nil {
+		log.Fatalf("Failed to load input: %s\n", err)
+	}
+
+	var refs exportReferences
+	err = json.Unmarshal(file, &refs)
+	if err != nil {
+		log.Fatalf("Failed to deserialise input: %s\n", err)
+	}
+
+	// Parse popularity data
+	popBytes, err := ioutil.ReadFile(*popFile)
+	if err != nil {
+		log.Fatalf("Failed to load input: %s\n", err)
+	}
+
+	var pop Popularity
+	err = json.Unmarshal(popBytes, &pop)
+	if err != nil {
+		log.Fatalf("Failed to deserialise input: %s\n", err)
+	}
+
+	graph := buildGraph(&refs, &pop)
+	layers := dominate(*layerBudget, graph)
+
+	j, _ := json.Marshal(layers)
+	ioutil.WriteFile(*outFile, j, 0644)
+}