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/* -*- js-indent-level: 2; indent-tabs-mode: nil -*- */
/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
"use strict";
/**
* This module records detailed timing information about selected
* GCs. The data is sent back in the telemetry session ping. To avoid
* bloating the ping, only a few GCs are included. There are two
* selection strategies. We always save the five GCs with the worst
* max_pause time. Additionally, five collections are selected at
* random. If a GC runs for C milliseconds and the total time for all
* GCs since the session began is T milliseconds, then the GC has a
* 5*C/T probablility of being selected (the factor of 5 is because we
* save 5 of them).
*
* GCs from both the main process and all content processes are
* recorded. The data is cleared for each new subsession.
*/
const Cu = Components.utils;
Cu.import("resource://gre/modules/Services.jsm", this);
this.EXPORTED_SYMBOLS = ["GCTelemetry"];
// Names of processes where we record GCs.
const PROCESS_NAMES = ["main", "content"];
// Should be the time we started up in milliseconds since the epoch.
const BASE_TIME = Date.now() - Services.telemetry.msSinceProcessStart();
// Records selected GCs. There is one instance per process type.
class GCData {
constructor(kind) {
let numRandom = {main: 0, content: 2};
let numWorst = {main: 2, content: 2};
this.totalGCTime = 0;
this.randomlySelected = Array(numRandom[kind]).fill(null);
this.worst = Array(numWorst[kind]).fill(null);
}
// Turn absolute timestamps (in microseconds since the epoch) into
// milliseconds since startup.
rebaseTimes(data) {
function fixup(t) {
return t / 1000.0 - BASE_TIME;
}
data.timestamp = fixup(data.timestamp);
for (let i = 0; i < data.slices.length; i++) {
let slice = data.slices[i];
slice.start_timestamp = fixup(slice.start_timestamp);
slice.end_timestamp = fixup(slice.end_timestamp);
}
}
// Records a GC (represented by |data|) in the randomlySelected or
// worst batches depending on the criteria above.
record(data) {
this.rebaseTimes(data);
let time = data.total_time;
this.totalGCTime += time;
// Probability that we will replace any one of our
// current randomlySelected GCs with |data|.
let prob = time / this.totalGCTime;
// Note that we may replace multiple GCs in
// randomlySelected. It's easier to reason about the
// probabilities this way, and it's unlikely to have any effect in
// practice.
for (let i = 0; i < this.randomlySelected.length; i++) {
let r = Math.random();
if (r <= prob) {
this.randomlySelected[i] = data;
}
}
// Save the 5 worst GCs based on max_pause. A GC may appear in
// both worst and randomlySelected.
for (let i = 0; i < this.worst.length; i++) {
if (!this.worst[i]) {
this.worst[i] = data;
break;
}
if (this.worst[i].max_pause < data.max_pause) {
this.worst.splice(i, 0, data);
this.worst.length--;
break;
}
}
}
entries() {
return {
random: this.randomlySelected.filter(e => e !== null),
worst: this.worst.filter(e => e !== null),
};
}
}
// If you adjust any of the constants here (slice limit, number of keys, etc.)
// make sure to update the JSON schema at:
// https://github.com/mozilla-services/mozilla-pipeline-schemas/blob/master/telemetry/main.schema.json
// You should also adjust browser_TelemetryGC.js.
const MAX_GC_KEYS = 25;
const MAX_SLICES = 4;
const MAX_SLICE_KEYS = 15;
const MAX_PHASES = 65;
function limitProperties(obj, count) {
// If there are too many properties, just delete them all. We don't
// expect this ever to happen.
if (Object.keys(obj).length > count) {
for (let key of Object.keys(obj)) {
delete obj[key];
}
}
}
function limitSize(data) {
// Store the number of slices so we know if we lost any at the end.
data.num_slices = data.slices.length;
data.slices.sort((a, b) => b.pause - a.pause);
if (data.slices.length > MAX_SLICES) {
// Make sure we always keep the first slice since it has the
// reason the GC was started.
let firstSliceIndex = data.slices.findIndex(s => s.slice == 0);
if (firstSliceIndex >= MAX_SLICES) {
data.slices[MAX_SLICES - 1] = data.slices[firstSliceIndex];
}
data.slices.length = MAX_SLICES;
}
data.slices.sort((a, b) => a.slice - b.slice);
limitProperties(data, MAX_GC_KEYS);
for (let slice of data.slices) {
limitProperties(slice, MAX_SLICE_KEYS);
limitProperties(slice.times, MAX_PHASES);
}
limitProperties(data.totals, MAX_PHASES);
}
let processData = new Map();
for (let name of PROCESS_NAMES) {
processData.set(name, new GCData(name));
}
var GCTelemetry = {
initialized: false,
init() {
if (this.initialized) {
return false;
}
this.initialized = true;
Services.obs.addObserver(this, "garbage-collection-statistics", false);
if (Services.appinfo.processType == Services.appinfo.PROCESS_TYPE_DEFAULT) {
Services.ppmm.addMessageListener("Telemetry:GCStatistics", this);
}
return true;
},
shutdown() {
if (!this.initialized) {
return;
}
Services.obs.removeObserver(this, "garbage-collection-statistics");
if (Services.appinfo.processType == Services.appinfo.PROCESS_TYPE_DEFAULT) {
Services.ppmm.removeMessageListener("Telemetry:GCStatistics", this);
}
this.initialized = false;
},
observe(subject, topic, arg) {
let data = JSON.parse(arg);
limitSize(data);
if (Services.appinfo.processType == Services.appinfo.PROCESS_TYPE_DEFAULT) {
processData.get("main").record(data);
} else {
Services.cpmm.sendAsyncMessage("Telemetry:GCStatistics", data);
}
},
receiveMessage(msg) {
processData.get("content").record(msg.data);
},
entries(kind, clear) {
let result = processData.get(kind).entries();
if (clear) {
processData.set(kind, new GCData(kind));
}
return result;
},
};
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