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For some big cases the component_segmentation can produce a json files output folder of huge sizes 10-100-... GB. The idea is to gzip compress each file and serve the Javascript with .json.gz files. They can be unpacked on the client side either automagically by a browser itself or explicitly by a script e.g. https://www.npmjs.com/package/decompress-response
The text was updated successfully, but these errors were encountered:
I've been told you see another scalability challenge every time you increase your input by 2-4x. Chunking JSON files is intended to keep each individual JSON down to <4MB. However, in very large genomes, the number of files will be large and thus the index of those files bin2file.json will also be massive. Chunking the index or having an index of indices seems slightly wrong.
For internet traffic, compressing the JSON is a great idea. The internals are very repetitive and I've seen 10x compression. However, a more direct route might be simply making the files sparse graph-genome/component_segmentation#29
One can do both: sparse info storage and gzip compression of .json
For the very big setup I'd suggest moving bin2file.json content to the backend and store the index info in an sqlite DB. One can have indices for several "pyramid" zoom levels
For some big cases the component_segmentation can produce a json files output folder of huge sizes 10-100-... GB. The idea is to gzip compress each file and serve the Javascript with .json.gz files. They can be unpacked on the client side either automagically by a browser itself or explicitly by a script e.g. https://www.npmjs.com/package/decompress-response
The text was updated successfully, but these errors were encountered: