tvl-depot/tools/nixery/builder/layers.go
Vincent Ambo 6716bf018c chore(nixery): Housekeeping for depot compatibility
Cleans up a whole bunch of things I wanted to get out of the door
right away:

* depot internal references to //third_party/nixery have been replaced
  with //tools/nixery
* cleaned up files from Github
* fixed SPDX & Copyright headers
* code formatting and inclusion in //tools/depotfmt checks

Change-Id: Iea79f0fdf3aa04f71741d4f4032f88605ae415bb
Reviewed-on: https://cl.tvl.fyi/c/depot/+/5486
Tested-by: BuildkiteCI
Reviewed-by: tazjin <tazjin@tvl.su>
Autosubmit: tazjin <tazjin@tvl.su>
2022-04-20 15:31:16 +00:00

353 lines
9.8 KiB
Go

// Copyright 2022 The TVL Contributors
// SPDX-License-Identifier: Apache-2.0
// This package reads an export reference graph (i.e. a graph representing the
// runtime dependencies of a set of derivations) created by Nix and groups it 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
// * popularity values of each package 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 builder
import (
"crypto/sha1"
"fmt"
"regexp"
"sort"
"strings"
log "github.com/sirupsen/logrus"
"gonum.org/v1/gonum/graph/flow"
"gonum.org/v1/gonum/graph/simple"
)
// runtimeGraph represents structured information from Nix about the runtime
// dependencies of a derivation.
//
// This is generated in Nix by using the exportReferencesGraph feature.
type runtimeGraph 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
}
// Hash the contents of a layer to create a deterministic identifier that can be
// used for caching.
func (l *layer) Hash() string {
sum := sha1.Sum([]byte(strings.Join(l.Contents, ":")))
return fmt.Sprintf("%x", sum)
}
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]+-`)
// PackageFromPath returns the name of a Nix package based on its
// output store path.
func packageFromPath(path string) string {
return nixRegexp.ReplaceAllString(path, "")
}
// DOTID provides a human-readable package name. The name stems from
// the dot format used by GraphViz, into which the dependency graph
// can be rendered.
func (c *closure) DOTID() string {
return packageFromPath(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
}
// Threshold value is picked arbitrarily right now. The reason
// for this is that some packages (such as `cacert`) have very
// few direct dependencies, but are required by pretty much
// everything.
if c.Popularity >= 100 {
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 *runtimeGraph, 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,
}
// The packages `nss-cacert` and `iana-etc` are added
// by Nixery to *every single image* and should have a
// very high popularity.
//
// Other popularity values are populated from the data
// set assembled by Nixery's popcount.
id := node.DOTID()
if strings.HasPrefix(id, "nss-cacert") || strings.HasPrefix(id, "iana-etc") {
// glibc has ~300k references, these packages need *more*
node.Popularity = 500000
} else if p, ok := (*pop)[id]; 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())...)
}
// Contents are sorted to ensure that hashing is consistent
sort.Strings(contents)
return layer{
Contents: contents,
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.WithFields(log.Fields{
"layers": len(layers),
"budget": budget,
}).Info("ideal image exceeds layer budget")
}
for len(layers) > budget {
merged := layers[0].merge(layers[1])
layers[1] = merged
layers = layers[1:]
}
return layers
}
// groupLayers applies the algorithm described above the its input and returns a
// list of layers, each consisting of a list of Nix store paths that it should
// contain.
func groupLayers(refs *runtimeGraph, pop *Popularity, budget int) []layer {
graph := buildGraph(refs, pop)
return dominate(budget, graph)
}