The Best Tool for the Join: Scaling Node.js with Unix | Hacker News Reader

The Best Tool for the Join: Scaling Node.js with Unix

engineering.clever.com

13 pointsjonahkagan10 comments

To quote an older hackernews comment:

"I love when people rediscover basic unix utilities and have this light bulb moment and realize that people have been working on the same problems as them for much longer and basically solved it 20 years ago."

If you think improving education with tools backed by years of unix wisdom is interesting, we're hiring! https://clever.com/about/jobs#engineer-full-stack

It's great to remind everyone how Node follows various rules of the Unix Philosophy, and how it is designed to make process spawning/streaming as natural as on the OS.

I would prefer it though if the implication wasn't that a failure in Node's design is responsible for the failure of this in-process-memory technique of sorting massive data sets. From the article:

"However, as more and more districts began relying on Clever, it quickly became apparent that in-memory joins were a huge bottleneck."

Indeed...

"Plus, Node.js processes tend to conk out when they reach their 1.7 GB memory limit, a threshold we were starting to get uncomfortably close to."

Maybe simply "processes" rather than "Node processes"? -- I don't think this is a Node-only problem.

"Once some of the country’s largest districts started using Clever, we realized that loading all of a district’s data into memory at once simply wouldn’t scale."

I think this was predictable. Earlier in the article I noticed this line:

"We implemented the join logic we needed using a simple in-memory hash join, avoiding premature optimization."

The "premature optimization" line is becoming something of a trope. It is not bad engineering to think at least as far as your business model. It sounds like reaching 1/6 of your market led to a system failure. This could (should?) have been anticipated.

To some extent we knew that in-memory joins would eventually cause problems, but we were certainly surprised at how quickly Node memory usage became the bottleneck. Here's a little gist I used to test it a while ago https://gist.github.com/rgarcia/6170213.

As for your point about premature optimization, in my opinion a startup's first priority is getting something in front of users in order to start improving and iterating. The first version of the data pipeline discussed in the blog post was built when Clever was in 0 schools, so designing it to scale to some of the largest school districts in the country would have been fairly presumptuous.

Cool solution. Reminds me of the Flow-Based programming movement happening in the node community. http://noflojs.org

It's also interesting to consider why we don't actually build more tools this way (generalizing the Unix philosophy). Some Real Talk about that here: http://memerocket.com/2006/12/01/the-unix-tools-philosophy-t...

Glad they found a solution, but wonder how the initial planning went when they started up.

Was there a conscious decision at the beginning to avoid a database? If so, why not? It kinds of sounds like they'd like to go in that direction now, but it'd require a re-write.

I thought the 1.7GB memory limit for v8 was lifted? This bug[0] seems to indicate that was fixed.

[0] https://code.google.com/p/v8/issues/detail?id=847

Good find! I can't seem to find a comment that indicates what the new limit is though. Experimentally, we were seeing processes dying at around the 1.7GB to 2GB range.

Did you find anything indicating what the expected new limit is?

Hi Clever gang, this hack is rather clever ;) I do a similar thing dealing with complicated relational structures but I child out to bash scripts vs your stream solution.

Is your stack coffescript? Doesn't look like generic javascript to me...

Yep, we use CoffeeScript.

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