This week-end project started by browsing the open-data repository of Paris’ public transport network, which contains various APIs to query real-time departures, current disruptions, etc.The data reuse section caught my eye, as it features external projects that use this open data.In particular, the RATP status website provides a really nice interface to visualize historical disruptions on metro, RER/train and tramway lines.
In my experience taking an inefficient format and copping out by saying “we can just compress it” is always rubbish. Compression tends to be slow, rules out sparse reads, is awkward to deal with remotely, and you generally always end up with the inefficient decompressed data in the end anyway, whether in temporarily decompressed files or in memory.
I worked in a company where they went against my recommendation not to use JSON for a memory profiler output. We ended up with 10 GB JSON files, even compressed they were super annoying.
We switched to SQLite in the end which was far superior.
In my experience taking an inefficient format and copping out by saying “we can just compress it” is always rubbish. Compression tends to be slow, rules out sparse reads, is awkward to deal with remotely, and you generally always end up with the inefficient decompressed data in the end anyway, whether in temporarily decompressed files or in memory.
I worked in a company where they went against my recommendation not to use JSON for a memory profiler output. We ended up with 10 GB JSON files, even compressed they were super annoying.
We switched to SQLite in the end which was far superior.
Of course compressing isn’t a good solution for this stuff. The point of the comment was to say how unremarkable the original claim was.
Yeah I agree.