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A Hugo site to test the Stork library for full-text search

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Hugo + Stork

This site is built with Hugo and includes the Stork library for full-text search. The site contains 500 articles with an average of 520 words per article.

Live test sites

Test locally on Ubuntu

./build.sh
hugo server --renderToDisk

Notes

Stork generates a binary index file. With this test site, the index file is 6 MB. To force hosts such as GitHub Pages or Netlify to compress the file, we give it a json extension. We could use html or css instead, but json seemed like a better fit.

GitHub pages uses gzip compression, producing a 2.3 MB index file.

Netlify uses Brotli compression, though not aggressively, producing a 2.1 MB index file.

If you have a host that can serve pre-compressed assets, aggressive Brotli compression produces a 1.5 MB file.

Bag of bytes

When examining the page load, you can see that the browser downloads some of the assets in parallel. I ran some experiments, using a large image, to see if there would be any benefit to splitting the Stork index into pieces.

Spoiler alert: splitting the image into chunks does not improve performance.

https://hugo-stork.netlify.app/tests/

Large image:

  • A single image
  • 5,736,890 bytes
  • 4032x2268

Large image (2 chunks):

  • The same image, split into 2 chunks
  • 6,002,033 bytes total
  • Each chunk (tile) is 4032x1134

Large image (9 chunks):

  • The same image, split into 9 chunks
  • 6,045,716 bytes total
  • Each chunk (tile) is 1344x756

This is an imperfect test because I am not splitting a binary file. I am creating multiple independent images, so the total size increases due to compression inefficiency. Even though splitting increases total size by only 5 percent, I am seeing a 10 to 20 percent drop in performance.

From these rudimentary tests it appears that splitting the index would not improve performance.

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