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One of the contributers here: GEM is at the first step towards true data modeling where it makes the mappings process very accessible. For someone coming from
by sidi 10y ago
One of the contributers here:
GEM is at the first step towards true data modeling where it makes the mappings process very accessible. For someone coming from a SQL background, mappings in Elasticsearch are interesting because of it's nature of being both a search engine and a data store suited for aggregations.
Would love it to eventually have some intelligence and heuristics built in, like recommending what data types to choose, data normalization patterns.
- NikolaeVarius 10y agoDAMNIT. Been working on my own spin on this sort of GUI internally for my company. Are you guys actively taking pull requests? I would much rather contribute to a more finished application
- sidi 10y agoIt's in active development. We would love PRs that are aligned, what areas are you looking to contribute in?
- NikolaeVarius 10y agoGoing through the code right now and seeing what you guys have/need.
- deleted 10y ago[deleted]
- deleted 10y ago[deleted]
- zuxfer 10y agohow do you guys handles nested objects? And recursively nested objects? And recursively nested objects :P
- IndianAstronaut 10y agoVery interesting. Have you tested it fully on a wide array of geolocation data? Such as what are the mappings for a variety of cities and towns, where some may fit a string definition or geolocation, such as "Pleasant". I have used Solr quite a bit, not much Elasticsearch, but I am assuming the text tokenizers/analyzers aren't as complex in the schemas as Solr is, where you have a wide array of different text parsers.