nixery/group-layers/group-layers.go
Vincent Ambo d174d9c9b5 feat(group-layers): Implement first half of new layering strategy
The strategy is described in-depth in the comment at the top of the
implementation file, as well as in the design document:

https://storage.googleapis.com/nixdoc/nixery-layers.html
2019-08-14 00:02:04 +01:00

268 lines
6.9 KiB
Go

// 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 layers are merged together in this order:
//
// * layers whose root meets neither condition above
// * layers whose root is popular
// * layers whose root is big
// * layers whose root meets both conditions
//
// # 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 main
import (
"encoding/json"
"flag"
"io/ioutil"
"log"
"fmt"
"regexp"
"os"
"gonum.org/v1/gonum/graph/simple"
"gonum.org/v1/gonum/graph/flow"
"gonum.org/v1/gonum/graph/encoding/dot"
)
// 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"`
}
// closure as pointed to by the graph nodes.
type closure struct {
GraphID int64
Path string
Size uint64
Refs []string
// TODO(tazjin): popularity and other funny business
}
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, "")
}
func insertEdges(graph *simple.DirectedGraph, cmap *map[string]*closure, node *closure) {
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) *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,
}
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)
}
gv, err := dot.Marshal(graph, "deps", "", "")
if err != nil {
log.Fatalf("Could not encode graph: %s\n", err)
}
fmt.Print(string(gv))
os.Exit(0)
return graph
}
// Calculate the dominator tree of the entire package set and group
// each top-level subtree into a layer.
func dominate(graph *simple.DirectedGraph) {
dt := flow.Dominators(graph.Node(0), graph)
// convert dominator tree back into encodable graph
dg := simple.NewDirectedGraph()
for nodes := graph.Nodes(); nodes.Next(); {
dg.AddNode(nodes.Node())
}
for nodes := dg.Nodes(); nodes.Next(); {
node := nodes.Node()
for _, child := range dt.DominatedBy(node.ID()) {
edge := dg.NewEdge(node, child)
dg.SetEdge(edge)
}
}
gv, err := dot.Marshal(dg, "deps", "", "")
if err != nil {
log.Fatalf("Could not encode graph: %s\n", err)
}
fmt.Print(string(gv))
// fmt.Printf("%v edges in the graph\n", graph.Edges().Len())
// top := 0
// for _, n := range dt.DominatedBy(0) {
// fmt.Printf("%q is top-level\n", n.(*closure).Path)
// top++
// }
// fmt.Printf("%v total top-level nodes\n", top)
// root := dt.Root().(*closure)
// fmt.Printf("dominator tree root is %q\n", root.Path)
// fmt.Printf("%v nodes can reach to 1\n", nodes.Len())
}
func main() {
inputFile := flag.String("input", ".attrs.json", "Input file containing graph")
flag.Parse()
file, err := ioutil.ReadFile(*inputFile)
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)
}
graph := buildGraph(&refs)
dominate(graph)
}