We want a telemetry for optimizing content process creation for typical sites.
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(Core :: Performance, enhancement, P3)
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Tracking | Status | |
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firefox78 | --- | fixed |
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(Reporter: sefeng, Assigned: beth)
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chutten
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Details | Review |
The proposed implementation is to collect number of unique origins per loaded tab. By using this number, we can get the average/distribution of the number of site origins of a typical tabs. We can use this number to optimize the content process creation for typical sites.
Reporter | ||
Comment 1•5 years ago
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Olli, would you agree the proposed implementation?
Comment 2•5 years ago
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How would we use the number for optimizing anything?
(We know that we must optimize process creation, but that we need to do anyhow)
Reporter | ||
Comment 3•5 years ago
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Say we know typical pages would use 2 processes, then we can try to make sure to always have 2 free processes ready before a pageload? Just my 2 cents guessing
Comment 5•5 years ago
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ah, that. Yeah, makes sense.
And this is about collecting number of unique sites per tab - sites which aren't being used in other tabs, right?
Reporter | ||
Comment 6•5 years ago
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Initially I think we do want to include the sites that are currently being used in other tabs.
However, by thinking it a bit more, I agree to only counts the sites that aren't being used in other tabs, and this gives us a how many new processes are going to be created for typical sites.
Do you agree Randell?
Comment 7•5 years ago
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The number of origins per-page is useful for determining the number of processes to prestart at startup and how many to have when there are "few" tabs open. The number that aren't already open will be lower, which will be too low for low-tab/startup cases, and too high for add-one-more-tab-to--bunch cases. I want information about the state of the web as we hit it, which can be used to inform various decisions and tradeoffs. The delta-new-processes number may be useful in looking at tuning an algorithm for how many to keep in reserve, though it wasn't what I was looking for here.
The alternate would be to key it so we collect the distribution of number of new origins needed vs. number of tabs loaded (not number of tabs, note) or versus number of content processes running.
Reporter | ||
Comment 8•5 years ago
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I am not convinced to use the number of site origins per-page....
I mean, I get the point that the if we only count the delta-new-process, it may vary depend on the current state of the browser. My argument is, isn't it more realistic and accurate? I think it's more representative.
The number that aren't already open will be lower, which will be too low for low-tab/startup cases
Well, I think this is true if the majority of user would open a bunch of other tabs, and then open certain high number of origins sites, and the data won't capture the minority of users who would open these high number of origins at startup. If this is the case, then do we really care? and if this is not the case, which means the majority of users would open these high number of origins sites at the startup, then the delta-new-process is able to capture this as well.
too high for add-one-more-tab-to--bunch cases
Yeah, same as the previous one, I just feel if this is an edge case, then we probably don't care. And if it's not an edge case, then the delta-new-process can capture this as well .
Hope I am clear, let me know what you think Randell.
Comment 9•5 years ago
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My goal was to get data that will help a) guide our work on process startup and caching including the model/algorithm; b) help us understand the web our users are seeing (like for example if over the next year the average origins/site goes from 1.5 to 2).
For example, we may want to prestart more origins when someone has 1 tab open than if they have 20; knowing typical origins used (and their distribution) helps set the startup/1-tab end, and the total origins (which we have) and delta-origins-per-new-load would help design how much we tail that off as number of active tabs (or origins) increases. If there's too big a tail of high-origins pages (like CNN) in the data, we may not be able to tail off the prestart #'s.
Perhaps we could get data to help with a) by getting a distribution of unique origins vs #of tabs, but I don't think we can do that sort of 2d distribution in Telemetry.
Reporter | ||
Updated•5 years ago
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Updated•5 years ago
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Comment hidden (typo) |
Comment 11•5 years ago
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Reopening because I closed this bug by mistake. We do want this telemetry to know how to tune Fission's iframe process management.
We should try to collect this information even if users don't have Fission enabled (because we don't have many Fission users yet).
Assignee | ||
Comment 12•5 years ago
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Assignee | ||
Updated•5 years ago
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Comment 13•5 years ago
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Assignee | ||
Comment 14•5 years ago
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Comment 15•5 years ago
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Comment 16•5 years ago
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bugherder |
Description
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