mirror of
https://github.com/NixOS/nixpkgs.git
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09362bc3e8
On very large graphs (14k+ paths), we'd end up with a massive in memory tree of mostly duplication. We can safely cache trees and point back to them later, saving memory.
568 lines
16 KiB
Python
568 lines
16 KiB
Python
# IMPORTANT: Making changes?
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#
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# Validate your changes with python3 ./closure-graph.py --test
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# Using a simple algorithm, convert the references to a path in to a
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# sorted list of dependent paths based on how often they're referenced
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# and how deep in the tree they live. Equally-"popular" paths are then
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# sorted by name.
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#
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# The existing writeReferencesToFile prints the paths in a simple
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# ascii-based sorting of the paths.
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#
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# Sorting the paths by graph improves the chances that the difference
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# between two builds appear near the end of the list, instead of near
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# the beginning. This makes a difference for Nix builds which export a
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# closure for another program to consume, if that program implements its
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# own level of binary diffing.
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#
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# For an example, Docker Images. If each store path is a separate layer
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# then Docker Images can be very efficiently transfered between systems,
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# and we get very good cache reuse between images built with the same
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# version of Nixpkgs. However, since Docker only reliably supports a
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# small number of layers (42) it is important to pick the individual
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# layers carefully. By storing very popular store paths in the first 40
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# layers, we improve the chances that the next Docker image will share
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# many of those layers.*
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#
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# Given the dependency tree:
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#
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# A - B - C - D -\
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# \ \ \ \
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# \ \ \ \
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# \ \ - E ---- F
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# \- G
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#
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# Nodes which have multiple references are duplicated:
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#
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# A - B - C - D - F
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# \ \ \
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# \ \ \- E - F
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# \ \
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# \ \- E - F
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# \
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# \- G
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#
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# Each leaf node is now replaced by a counter defaulted to 1:
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#
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# A - B - C - D - (F:1)
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# \ \ \
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# \ \ \- E - (F:1)
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# \ \
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# \ \- E - (F:1)
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# \
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# \- (G:1)
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#
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# Then each leaf counter is merged with its parent node, replacing the
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# parent node with a counter of 1, and each existing counter being
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# incremented by 1. That is to say `- D - (F:1)` becomes `- (D:1, F:2)`:
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#
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# A - B - C - (D:1, F:2)
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# \ \ \
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# \ \ \- (E:1, F:2)
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# \ \
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# \ \- (E:1, F:2)
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# \
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# \- (G:1)
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#
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# Then each leaf counter is merged with its parent node again, merging
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# any counters, then incrementing each:
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#
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# A - B - (C:1, D:2, E:2, F:5)
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# \ \
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# \ \- (E:1, F:2)
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# \
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# \- (G:1)
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#
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# And again:
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#
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# A - (B:1, C:2, D:3, E:4, F:8)
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# \
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# \- (G:1)
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#
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# And again:
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#
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# (A:1, B:2, C:3, D:4, E:5, F:9, G:2)
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#
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# and then paths have the following "popularity":
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#
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# A 1
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# B 2
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# C 3
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# D 4
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# E 5
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# F 9
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# G 2
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#
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# and the popularity contest would result in the paths being printed as:
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#
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# F
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# E
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# D
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# C
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# B
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# G
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# A
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#
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# * Note: People who have used a Dockerfile before assume Docker's
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# Layers are inherently ordered. However, this is not true -- Docker
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# layers are content-addressable and are not explicitly layered until
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# they are composed in to an Image.
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import sys
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import json
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import unittest
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from pprint import pprint
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from collections import defaultdict
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def debug(msg, *args, **kwargs):
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if False:
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print(
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"DEBUG: {}".format(
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msg.format(*args, **kwargs)
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),
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file=sys.stderr
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)
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# Find paths in the original dataset which are never referenced by
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# any other paths
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def find_roots(closures):
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roots = [];
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for closure in closures:
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path = closure['path']
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if not any_refer_to(path, closures):
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roots.append(path)
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return roots
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class TestFindRoots(unittest.TestCase):
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def test_find_roots(self):
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self.assertCountEqual(
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find_roots([
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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{
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"path": "/nix/store/bar",
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"references": [
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"/nix/store/bar",
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"/nix/store/tux"
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]
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},
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{
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"path": "/nix/store/hello",
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"references": [
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]
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}
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]),
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["/nix/store/foo", "/nix/store/hello"]
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)
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def any_refer_to(path, closures):
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for closure in closures:
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if path != closure['path']:
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if path in closure['references']:
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return True
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return False
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class TestAnyReferTo(unittest.TestCase):
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def test_has_references(self):
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self.assertTrue(
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any_refer_to(
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"/nix/store/bar",
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[
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/bar"
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]
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},
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]
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),
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)
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def test_no_references(self):
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self.assertFalse(
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any_refer_to(
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"/nix/store/foo",
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[
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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]
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),
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)
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def all_paths(closures):
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paths = []
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for closure in closures:
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paths.append(closure['path'])
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paths.extend(closure['references'])
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paths.sort()
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return list(set(paths))
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class TestAllPaths(unittest.TestCase):
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def test_returns_all_paths(self):
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self.assertCountEqual(
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all_paths([
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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{
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"path": "/nix/store/bar",
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"references": [
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"/nix/store/bar",
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"/nix/store/tux"
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]
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},
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{
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"path": "/nix/store/hello",
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"references": [
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]
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}
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]),
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["/nix/store/foo", "/nix/store/bar", "/nix/store/hello", "/nix/store/tux",]
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)
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def test_no_references(self):
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self.assertFalse(
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any_refer_to(
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"/nix/store/foo",
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[
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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]
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),
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)
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# Convert:
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#
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# [
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# { path: /nix/store/foo, references: [ /nix/store/foo, /nix/store/bar, /nix/store/baz ] },
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# { path: /nix/store/bar, references: [ /nix/store/bar, /nix/store/baz ] },
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# { path: /nix/store/baz, references: [ /nix/store/baz, /nix/store/tux ] },
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# { path: /nix/store/tux, references: [ /nix/store/tux ] }
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# ]
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#
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# To:
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# {
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# /nix/store/foo: [ /nix/store/bar, /nix/store/baz ],
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# /nix/store/bar: [ /nix/store/baz ],
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# /nix/store/baz: [ /nix/store/tux ] },
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# /nix/store/tux: [ ]
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# }
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#
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# Note that it drops self-references to avoid loops.
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def make_lookup(closures):
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lookup = {}
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for closure in closures:
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# paths often self-refer
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nonreferential_paths = [ref for ref in closure['references'] if ref != closure['path']]
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lookup[closure['path']] = nonreferential_paths
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return lookup
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class TestMakeLookup(unittest.TestCase):
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def test_returns_lookp(self):
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self.assertDictEqual(
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make_lookup([
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{
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"path": "/nix/store/foo",
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"references": [
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"/nix/store/foo",
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"/nix/store/bar"
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]
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},
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{
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"path": "/nix/store/bar",
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"references": [
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"/nix/store/bar",
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"/nix/store/tux"
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]
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},
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{
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"path": "/nix/store/hello",
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"references": [
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]
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}
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]),
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{
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"/nix/store/foo": [ "/nix/store/bar" ],
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"/nix/store/bar": [ "/nix/store/tux" ],
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"/nix/store/hello": [ ],
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}
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)
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# Convert:
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#
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# /nix/store/foo with
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# {
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# /nix/store/foo: [ /nix/store/bar, /nix/store/baz ],
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# /nix/store/bar: [ /nix/store/baz ],
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# /nix/store/baz: [ /nix/store/tux ] },
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# /nix/store/tux: [ ]
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# }
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#
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# To:
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#
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# {
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# /nix/store/bar: {
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# },
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# }
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subgraphs_cache = {}
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def make_graph_segment_from_root(root, lookup):
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global subgraphs_cache
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children = {}
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for ref in lookup[root]:
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# make_graph_segment_from_root is a pure function, and will
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# always return the same result based on a given input. Thus,
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# cache computation.
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#
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# Python's assignment will use a pointer, preventing memory
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# bloat for large graphs.
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if ref not in subgraphs_cache:
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debug("Subgraph Cache miss on {}".format(ref))
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subgraphs_cache[ref] = make_graph_segment_from_root(ref, lookup)
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else:
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debug("Subgraph Cache hit on {}".format(ref))
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children[ref] = subgraphs_cache[ref]
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return children
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class TestMakeGraphSegmentFromRoot(unittest.TestCase):
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def test_returns_graph(self):
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self.assertDictEqual(
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make_graph_segment_from_root("/nix/store/foo", {
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"/nix/store/foo": [ "/nix/store/bar" ],
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"/nix/store/bar": [ "/nix/store/tux" ],
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"/nix/store/tux": [ ],
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"/nix/store/hello": [ ],
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}),
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{
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"/nix/store/bar": {
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"/nix/store/tux": {}
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}
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}
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)
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def test_returns_graph_tiny(self):
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self.assertDictEqual(
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make_graph_segment_from_root("/nix/store/tux", {
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"/nix/store/foo": [ "/nix/store/bar" ],
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"/nix/store/bar": [ "/nix/store/tux" ],
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"/nix/store/tux": [ ],
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}),
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{}
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)
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# Convert a graph segment in to a popularity-counted dictionary:
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#
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# From:
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# {
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# /nix/store/foo: {
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# /nix/store/bar: {
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# }
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# /nix/store/baz: {
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# /nix/store/tux: {}
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# }
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# }
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# }
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#
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# to:
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# [
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# /nix/store/foo: 1
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# /nix/store/bar: 2
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# /nix/store/baz: 4
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# /nix/store/tux: 6
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# ]
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popularity_cache = {}
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def graph_popularity_contest(full_graph):
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global popularity_cache
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popularity = defaultdict(int)
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for path, subgraph in full_graph.items():
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popularity[path] += 1
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# graph_popularity_contest is a pure function, and will
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# always return the same result based on a given input. Thus,
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# cache computation.
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#
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# Python's assignment will use a pointer, preventing memory
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# bloat for large graphs.
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if path not in popularity_cache:
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debug("Popularity Cache miss on {}", path)
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popularity_cache[path] = graph_popularity_contest(subgraph)
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else:
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debug("Popularity Cache hit on {}", path)
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subcontest = popularity_cache[path]
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for subpath, subpopularity in subcontest.items():
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debug("Calculating popularity for {}", subpath)
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popularity[subpath] += subpopularity + 1
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return popularity
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class TestGraphPopularityContest(unittest.TestCase):
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def test_counts_popularity(self):
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self.assertDictEqual(
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graph_popularity_contest({
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"/nix/store/foo": {
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"/nix/store/bar": {
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"/nix/store/baz": {
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"/nix/store/tux": {}
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}
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},
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"/nix/store/baz": {
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"/nix/store/tux": {}
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}
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}
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}),
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{
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"/nix/store/foo": 1,
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"/nix/store/bar": 2,
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"/nix/store/baz": 4,
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"/nix/store/tux": 6,
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}
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)
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# Emit a list of packages by popularity, most first:
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#
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# From:
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# [
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# /nix/store/foo: 1
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# /nix/store/bar: 1
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# /nix/store/baz: 2
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# /nix/store/tux: 2
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# ]
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#
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# To:
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# [ /nix/store/baz /nix/store/tux /nix/store/bar /nix/store/foo ]
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def order_by_popularity(paths):
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paths_by_popularity = defaultdict(list)
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popularities = []
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for path, popularity in paths.items():
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popularities.append(popularity)
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paths_by_popularity[popularity].append(path)
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popularities = list(set(popularities))
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popularities.sort()
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flat_ordered = []
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for popularity in popularities:
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paths = paths_by_popularity[popularity]
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paths.sort(key=package_name)
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flat_ordered.extend(reversed(paths))
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return list(reversed(flat_ordered))
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class TestOrderByPopularity(unittest.TestCase):
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def test_returns_in_order(self):
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self.assertEqual(
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order_by_popularity({
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"/nix/store/foo": 1,
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"/nix/store/bar": 1,
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"/nix/store/baz": 2,
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"/nix/store/tux": 2,
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}),
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[
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"/nix/store/baz",
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"/nix/store/tux",
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"/nix/store/bar",
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"/nix/store/foo"
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]
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)
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def package_name(path):
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parts = path.split('-')
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start = parts.pop(0)
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# don't throw away any data, so the order is always the same.
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# even in cases where only the hash at the start has changed.
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parts.append(start)
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return '-'.join(parts)
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def main():
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filename = sys.argv[1]
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key = sys.argv[2]
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debug("Loading from {}", filename)
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with open(filename) as f:
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data = json.load(f)
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# Data comes in as:
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# [
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# { path: /nix/store/foo, references: [ /nix/store/foo, /nix/store/bar, /nix/store/baz ] },
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# { path: /nix/store/bar, references: [ /nix/store/bar, /nix/store/baz ] },
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# { path: /nix/store/baz, references: [ /nix/store/baz, /nix/store/tux ] },
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# { path: /nix/store/tux, references: [ /nix/store/tux ] }
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# ]
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#
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# and we want to get out a list of paths ordered by how universally,
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# important they are, ie: tux is referenced by every path, transitively
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# so it should be #1
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#
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# [
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# /nix/store/tux,
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# /nix/store/baz,
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# /nix/store/bar,
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# /nix/store/foo,
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# ]
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graph = data[key]
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debug("Finding roots from {}", key)
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roots = find_roots(graph);
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debug("Making lookup for {}", key)
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lookup = make_lookup(graph)
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full_graph = {}
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for root in roots:
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debug("Making full graph for {}", root)
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full_graph[root] = make_graph_segment_from_root(root, lookup)
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debug("Running contest")
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contest = graph_popularity_contest(full_graph)
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debug("Ordering by popularity")
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ordered = order_by_popularity(contest)
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debug("Checking for missing paths")
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missing = []
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for path in all_paths(graph):
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if path not in ordered:
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missing.append(path)
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|
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ordered.extend(missing)
|
|
print("\n".join(ordered))
|
|
|
|
if "--test" in sys.argv:
|
|
# Don't pass --test otherwise unittest gets mad
|
|
unittest.main(argv = [f for f in sys.argv if f != "--test" ])
|
|
else:
|
|
main()
|