mirror of
https://github.com/gorhill/uBlock.git
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85c68116bd
In the static network filtering engine (snfe), the
compiling-related code was spread across two classes.
This commit makes it so that all the compiling-related
code is in FilterCompiler class, which clear purpose is
to compile raw filters into a form which can be persisted
and later fed to the snfe with no parsing overhead.
To compile raw static network filter, the new approach is:
snfe.createCompiler(parser);
Then for each single raw filter to compile:
compiler.compile(parser, writer);
The caller is responsible to keep a reference to the
compiler instance for as long as it is needed. This removes
the need for the clunky code used to keep an instance of
compiler alive in the snfe.
Additionally, snfe.tokenHistograms() has been moved to
benchmarks.js, as it has no dependency on the snfe, it's
just a utility function.
340 lines
12 KiB
JavaScript
340 lines
12 KiB
JavaScript
/*******************************************************************************
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uBlock Origin - a browser extension to block requests.
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Copyright (C) 2014-present Raymond Hill
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see {http://www.gnu.org/licenses/}.
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Home: https://github.com/gorhill/uBlock
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*/
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'use strict';
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/******************************************************************************/
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import cosmeticFilteringEngine from './cosmetic-filtering.js';
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import globals from './globals.js';
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import io from './assets.js';
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import scriptletFilteringEngine from './scriptlet-filtering.js';
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import staticNetFilteringEngine from './static-net-filtering.js';
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import µb from './background.js';
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import { FilteringContext } from './filtering-context.js';
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import { LineIterator } from './text-utils.js';
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import { sessionFirewall } from './filtering-engines.js';
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import {
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domainFromHostname,
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entityFromDomain,
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hostnameFromURI,
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} from './uri-utils.js';
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/******************************************************************************/
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// The requests.json.gz file can be downloaded from:
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// https://cdn.cliqz.com/adblocking/requests_top500.json.gz
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//
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// Which is linked from:
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// https://whotracks.me/blog/adblockers_performance_study.html
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//
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// Copy the file into ./tmp/requests.json.gz
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//
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// If the file is present when you build uBO using `make-[target].sh` from
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// the shell, the resulting package will have `./assets/requests.json`, which
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// will be looked-up by the method below to launch a benchmark session.
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//
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// From uBO's dev console, launch the benchmark:
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// µBlock.staticNetFilteringEngine.benchmark();
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//
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// The usual browser dev tools can be used to obtain useful profiling
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// data, i.e. start the profiler, call the benchmark method from the
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// console, then stop the profiler when it completes.
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//
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// Keep in mind that the measurements at the blog post above where obtained
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// with ONLY EasyList. The CPU reportedly used was:
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// https://www.cpubenchmark.net/cpu.php?cpu=Intel+Core+i7-6600U+%40+2.60GHz&id=2608
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//
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// Rename ./tmp/requests.json.gz to something else if you no longer want
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// ./assets/requests.json in the build.
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const loadBenchmarkDataset = (( ) => {
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let datasetPromise;
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let ttlTimer;
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return function() {
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if ( ttlTimer !== undefined ) {
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globals.clearTimeout(ttlTimer);
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ttlTimer = undefined;
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}
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globals.setTimeout(( ) => {
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ttlTimer = undefined;
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datasetPromise = undefined;
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}, 5 * 60 * 1000);
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if ( datasetPromise !== undefined ) {
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return datasetPromise;
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}
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const datasetURL = µb.hiddenSettings.benchmarkDatasetURL;
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if ( datasetURL === 'unset' ) {
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console.info(`No benchmark dataset available.`);
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return Promise.resolve();
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}
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console.info(`Loading benchmark dataset...`);
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datasetPromise = io.fetchText(datasetURL).then(details => {
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console.info(`Parsing benchmark dataset...`);
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const requests = [];
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const lineIter = new LineIterator(details.content);
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while ( lineIter.eot() === false ) {
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let request;
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try {
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request = JSON.parse(lineIter.next());
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} catch(ex) {
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}
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if ( request instanceof Object === false ) { continue; }
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if ( !request.frameUrl || !request.url ) { continue; }
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if ( request.cpt === 'document' ) {
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request.cpt = 'main_frame';
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} else if ( request.cpt === 'xhr' ) {
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request.cpt = 'xmlhttprequest';
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}
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requests.push(request);
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}
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return requests;
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}).catch(details => {
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console.info(`Not found: ${details.url}`);
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datasetPromise = undefined;
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});
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return datasetPromise;
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};
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})();
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/******************************************************************************/
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// action: 1=test
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µb.benchmarkStaticNetFiltering = async function(options = {}) {
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const { target, redirectEngine } = options;
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const requests = await loadBenchmarkDataset();
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if ( Array.isArray(requests) === false || requests.length === 0 ) {
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const text = 'No dataset found to benchmark';
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console.info(text);
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return text;
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}
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console.info(`Benchmarking staticNetFilteringEngine.matchRequest()...`);
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const fctxt = new FilteringContext();
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if ( typeof target === 'number' ) {
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const request = requests[target];
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fctxt.setURL(request.url);
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fctxt.setDocOriginFromURL(request.frameUrl);
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fctxt.setType(request.cpt);
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const r = staticNetFilteringEngine.matchRequest(fctxt);
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console.info(`Result=${r}:`);
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console.info(`\ttype=${fctxt.type}`);
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console.info(`\turl=${fctxt.url}`);
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console.info(`\tdocOrigin=${fctxt.getDocOrigin()}`);
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if ( r !== 0 ) {
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console.info(staticNetFilteringEngine.toLogData());
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}
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return;
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}
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const t0 = globals.performance.now();
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let matchCount = 0;
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let blockCount = 0;
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let allowCount = 0;
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for ( let i = 0; i < requests.length; i++ ) {
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const request = requests[i];
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fctxt.setURL(request.url);
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fctxt.setDocOriginFromURL(request.frameUrl);
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fctxt.setType(request.cpt);
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staticNetFilteringEngine.redirectURL = undefined;
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const r = staticNetFilteringEngine.matchRequest(fctxt);
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matchCount += 1;
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if ( r === 1 ) { blockCount += 1; }
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else if ( r === 2 ) { allowCount += 1; }
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if ( r !== 1 ) {
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if ( staticNetFilteringEngine.hasQuery(fctxt) ) {
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staticNetFilteringEngine.filterQuery(fctxt, 'queryprune');
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}
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if ( fctxt.type === 'main_frame' || fctxt.type === 'sub_frame' ) {
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staticNetFilteringEngine.matchAndFetchModifiers(fctxt, 'csp');
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}
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staticNetFilteringEngine.matchHeaders(fctxt, []);
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} else if ( redirectEngine !== undefined ) {
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staticNetFilteringEngine.redirectRequest(redirectEngine, fctxt);
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}
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}
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const t1 = globals.performance.now();
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const dur = t1 - t0;
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const output = [
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'Benchmarked static network filtering engine:',
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`\tEvaluated ${matchCount} match calls in ${dur.toFixed(0)} ms`,
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`\tAverage: ${(dur / matchCount).toFixed(3)} ms per request`,
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`\tNot blocked: ${matchCount - blockCount - allowCount}`,
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`\tBlocked: ${blockCount}`,
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`\tUnblocked: ${allowCount}`,
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];
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const s = output.join('\n');
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console.info(s);
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return s;
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};
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/******************************************************************************/
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µb.tokenHistograms = async function() {
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const requests = await loadBenchmarkDataset();
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if ( Array.isArray(requests) === false || requests.length === 0 ) {
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console.info('No requests found to benchmark');
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return;
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}
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console.info(`Computing token histograms...`);
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const fctxt = new FilteringContext();
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const missTokenMap = new Map();
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const hitTokenMap = new Map();
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const reTokens = /[0-9a-z%]{2,}/g;
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for ( let i = 0; i < requests.length; i++ ) {
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const request = requests[i];
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fctxt.setURL(request.url);
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fctxt.setDocOriginFromURL(request.frameUrl);
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fctxt.setType(request.cpt);
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const r = staticNetFilteringEngine.matchRequest(fctxt);
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for ( let [ keyword ] of request.url.toLowerCase().matchAll(reTokens) ) {
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const token = keyword.slice(0, 7);
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if ( r === 0 ) {
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missTokenMap.set(token, (missTokenMap.get(token) || 0) + 1);
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} else if ( r === 1 ) {
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hitTokenMap.set(token, (hitTokenMap.get(token) || 0) + 1);
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}
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}
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}
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const customSort = (a, b) => b[1] - a[1];
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const topmisses = Array.from(missTokenMap).sort(customSort).slice(0, 100);
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for ( const [ token ] of topmisses ) {
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hitTokenMap.delete(token);
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}
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const tophits = Array.from(hitTokenMap).sort(customSort).slice(0, 100);
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console.info('Misses:', JSON.stringify(topmisses));
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console.info('Hits:', JSON.stringify(tophits));
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};
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/******************************************************************************/
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µb.benchmarkDynamicNetFiltering = async function() {
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const requests = await loadBenchmarkDataset();
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if ( Array.isArray(requests) === false || requests.length === 0 ) {
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console.info('No requests found to benchmark');
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return;
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}
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console.info(`Benchmarking sessionFirewall.evaluateCellZY()...`);
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const fctxt = new FilteringContext();
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const t0 = globals.performance.now();
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for ( const request of requests ) {
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fctxt.setURL(request.url);
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fctxt.setTabOriginFromURL(request.frameUrl);
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fctxt.setType(request.cpt);
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sessionFirewall.evaluateCellZY(
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fctxt.getTabHostname(),
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fctxt.getHostname(),
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fctxt.type
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);
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}
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const t1 = globals.performance.now();
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const dur = t1 - t0;
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console.info(`Evaluated ${requests.length} requests in ${dur.toFixed(0)} ms`);
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console.info(`\tAverage: ${(dur / requests.length).toFixed(3)} ms per request`);
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};
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/******************************************************************************/
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µb.benchmarkCosmeticFiltering = async function() {
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const requests = await loadBenchmarkDataset();
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if ( Array.isArray(requests) === false || requests.length === 0 ) {
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console.info('No requests found to benchmark');
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return;
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}
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console.info('Benchmarking cosmeticFilteringEngine.retrieveSpecificSelectors()...');
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const details = {
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tabId: undefined,
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frameId: undefined,
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hostname: '',
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domain: '',
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entity: '',
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};
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const options = {
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noSpecificCosmeticFiltering: false,
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noGenericCosmeticFiltering: false,
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};
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let count = 0;
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const t0 = globals.performance.now();
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for ( let i = 0; i < requests.length; i++ ) {
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const request = requests[i];
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if ( request.cpt !== 'main_frame' ) { continue; }
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count += 1;
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details.hostname = hostnameFromURI(request.url);
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details.domain = domainFromHostname(details.hostname);
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details.entity = entityFromDomain(details.domain);
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void cosmeticFilteringEngine.retrieveSpecificSelectors(details, options);
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}
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const t1 = globals.performance.now();
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const dur = t1 - t0;
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console.info(`Evaluated ${count} requests in ${dur.toFixed(0)} ms`);
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console.info(`\tAverage: ${(dur / count).toFixed(3)} ms per request`);
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};
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/******************************************************************************/
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µb.benchmarkScriptletFiltering = async function() {
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const requests = await loadBenchmarkDataset();
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if ( Array.isArray(requests) === false || requests.length === 0 ) {
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console.info('No requests found to benchmark');
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return;
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}
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console.info('Benchmarking scriptletFilteringEngine.retrieve()...');
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const details = {
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domain: '',
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entity: '',
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hostname: '',
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tabId: 0,
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url: '',
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};
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let count = 0;
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const t0 = globals.performance.now();
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for ( let i = 0; i < requests.length; i++ ) {
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const request = requests[i];
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if ( request.cpt !== 'main_frame' ) { continue; }
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count += 1;
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details.url = request.url;
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details.hostname = hostnameFromURI(request.url);
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details.domain = domainFromHostname(details.hostname);
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details.entity = entityFromDomain(details.domain);
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void scriptletFilteringEngine.retrieve(details);
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}
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const t1 = globals.performance.now();
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const dur = t1 - t0;
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console.info(`Evaluated ${count} requests in ${dur.toFixed(0)} ms`);
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console.info(`\tAverage: ${(dur / count).toFixed(3)} ms per request`);
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};
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/******************************************************************************/
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