Move ecosystem detection tool to nodejs org

[cjihrig]

This is a continuation of the discussion in #7619. For a while now, we have pinged @ChALkeR every time we wanted to know how heavily something was used in the ecosystem. I'm proposing that we bring this into the nodejs org so that it is more accessible to other people (busFactor++;), and more likely to get additional maintainers. @ChALkeR is currently working on the project in https://github.com/ChALkeR/Gzemnid.

[ChALkeR]

Citing myself from #7619 (comment) and below:

I'm trying to host the scripts at https://github.com/ChALkeR/Gzemnid, but it's only slowly transitioning from a set of hacky bash scripts that require manual actions to something more sensible. Perhaps will push some updates soon. That also works as a server to allow searches using a web API. I had it running as web service some time ago at http://gzemnid.oserv.org/, but it's not ready yet, and atm it's down.

Perhaps I will spend a bit more time on that in the coming days.

The 2016-01-28 dataset is hosted at http://oserv.org/npm/Gzemnid/2016-01-28/ — the *.lzo files and the bash script. Anyone could download the pre-built dataset and obtain exactly the same greps.

Also that repo provides the deep dependency checker (to build lists like this), pre-built files are named deps-nested.json in other folders.

Perhaps we need a separate issue for that somewhere.

I will try to make that one working without any additional non-documented actions, document it a bit (at least list the commands), and then it'll be at least usable by anyone other than myself. I'm all for moving that into the org once it reaches a «usable» state.

[jasnell]

@ChALkeR : Can you describe the infrastructure / hosting requirements that you have to run this? I can look into whether or not some part of our existing dedicated hosting resources can be used.

[ChALkeR]

@jasnell Atm it's suboptimal, some fixes are required to make it faster and less consuming. The main requirement is storage, but I can't tell the exact numbers now. Something around 200 GiB, perhaps (could be hosted on slow storage, it affects only dataset rebuild time). With proper fixes, that could be brought down to a few GiB, but a cache of about 80 GiB for packed files would still be useful in case if the rebuilding rules change.

The built dataset itself is around 5 GiB, so it's quite small.

[ChALkeR]

@jasnell I will to move the whole process to a small vps again to check if everything works fine (another reason is that I am far from my PC atm and can't rebuild this on my notebook due to slow internet). That would also help me to outline (and lower) the requirements to run this thing autonomously.

[jasnell]

No worries.
@mhdawson ... can some of our dedicated softlayer resources be used for this? (Particularly noting the storage requirements)

[ChALkeR]

@jasnell More specific:

Tarballs for @latest are consuming 79 GiB now. It's not required to store them, but they would be needed in case if the algorithm would be changed.

Partials (uncompressed) are exprected to consume around 30-50 GiB (I need to readjust the blacklist). Those are required to obtain reasonable rebuild speed and are essentially pre-built dataset chunks for each package. Those could be stored in the compressed form (reducing their size to something around 5 GiB), but that's not supported yet.

The dataset itself should be about the same size as all the partilals together (minus a few GiB). The compressed size is expected to be about 5 GiB, and we might want to keep several versions of those.

Deep dependencies builder has some memory requirements, but I don't remember how much memory exactly does it consume. It's below 2 GiB, I think.

I will post an update with real numbers once I finish rebuilding the dataset on my VPS.

[ChALkeR]

Ok. Partials are consuming 40 GiB.

That could increase as I would probably want to add more information there, i.e. package.json (to check postinstall scripts, for example) and the disk usage (to build a list of abnormally huge packages). That would be only +2-4 GiB though, I suppose. Or it could also decrease once I update the blacklist.

---

Upd: partials are 36 GiB with package.json files and fixed and updated blacklist. This could significantly increase in the future, though — it grows with the npm size.

[ChALkeR]

Ok. The unpacked dataset size is 29 GiB, 27 GiB of which is code search data.

The actual (packed) dataset size is 4.3 GiB, latest version is uploaded to http://oserv.org/npm/Gzemnid/2016-08-04/.

[ChALkeR]

Status update: no additional manual actions are required anymore, and it could be used by itself to build the same datasets that I'm using, without some internal knowledge.

I began documenting the commands and making it easier to work with the tool, I will hopefully make it into something sensible this week.

[jbergstroem]

Perhaps the build group can host this? We have room in our infrastructure.

[ChALkeR]

Status update: initial documentation is in place, search script also got merged, atm it has no more bash parts. The usage is pretty simple now.

I believe we could start moving this into the org at this point, if we would decide on that,