60 lines
2.1 KiB
Markdown
60 lines
2.1 KiB
Markdown
---
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title: "Crazy Experiment: Frontend Shipping as asar"
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date: "2017-01-09"
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---
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Today's crazy experiment is using an [asar archive](https://github.com/electron/asar) for shipping around
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and mounting frontend Javascript applications. This is something I feel is worth doing because it allows
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the web frontend developer (or team) give the backend team a single "binary" that can be dropped into the
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deployment process without having to build the frontend code as part of CI.
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asar is an interesting file format because it allows for random access of the data inside the archive.
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This allows an HTTP server to be able to concurrently serve files out of it without having to lock or
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incur an additional open file descriptor.
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In order to implement this, I have created a Go package named [asarfs](https://github.com/Xe/asarfs) that
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exposes the contents of an asar archive as a standard http.Handler.
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Example Usage:
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```go
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package main
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import (
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"log"
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"net/http"
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"os"
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"github.com/Xe/asarfs"
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)
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func do404(w http.ResponseWriter, r *http.Request) {
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http.Error(w, "Not found", http.StatusNotFound)
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}
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func main() {
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fs, err := asarfs.New("./static.asar", http.HandlerFunc(do404))
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if err != nil {
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log.Fatal(err)
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}
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http.ListenAndServe(":"+os.Getenv("PORT"), fs)
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}
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```
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I made some contrived benchmarks using some sample data (lots of large json files from mongodb dumps)
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I had laying around and ran them a few times. The results were very promising:
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```console
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[~/g/s/g/X/asarfs] : go1.8beta2 test -bench=. -benchmem
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BenchmarkHTTPFileSystem-8 20000 66481 ns/op 3219 B/op 58 allocs/op
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BenchmarkASARfs-8 20000 72084 ns/op 3549 B/op 77 allocs/op
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BenchmarkPreloadedASARfs-8 20000 62894 ns/op 3218 B/op 58 allocs/op
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PASS
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ok github.com/Xe/asarfs 5.636s
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```
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Amazingly, the performance and memory usage differences between serving the files over an asar archive
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and off of the filesystem are negligible. I've implemented it in the latest release of my personal website
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and hopefully end users should be seeing no difference in page load times.
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