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.
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
Very 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.
Nothing happens, in chrome console I see those errors :
XMLHttpRequest cannot load http://localhost:9200/myindex/_settings. Response to preflight request doesn't pass access control check: A wildcard '*' cannot be used in the 'Access-Control-Allow-Origin' header when the credentials flag is true. Origin 'http://opensource.appbase.io' is therefore not allowed access. The credentials mode of an XMLHttpRequest is controlled by the withCredentials attribute.
I can use elastic-head to connect local elasticsearch service. I did cors settings in elastic configuration file.
While this thread is still active, I would like to share more context around the project:
GEM is built as an auxiliary app to go along with mirage[0] and dejavu[1]. Together, the three can be used to model data, perform CRUD operations and compose queries.
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[ 4.8 ms ] story [ 32.0 ms ] threadGEM 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.
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
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.
Nothing happens, in chrome console I see those errors :
XMLHttpRequest cannot load http://localhost:9200/myindex/_settings. Response to preflight request doesn't pass access control check: A wildcard '*' cannot be used in the 'Access-Control-Allow-Origin' header when the credentials flag is true. Origin 'http://opensource.appbase.io' is therefore not allowed access. The credentials mode of an XMLHttpRequest is controlled by the withCredentials attribute.
I can use elastic-head to connect local elasticsearch service. I did cors settings in elastic configuration file.
GEM is built as an auxiliary app to go along with mirage[0] and dejavu[1]. Together, the three can be used to model data, perform CRUD operations and compose queries.
[0]: https://github.com/appbaseio/mirage
[1]: https://github.com/appbaseio/dejavu