1/2) There are several ways, but one way to create an index + mapping in one shot is:
PUT http://localhost:9200/infopoint { "mappings" : { "DIVER" : { "properties" : { "location" : { "type" : "geo_point", "lat_lon": true, "geohash": true }, "image" : {"index" : "no", "type": "string"} } } } } 3) There is an _all field that is automatically introduced by ES. It contains a concatenation of all the field values in your JSON document. When you do this search: { "query": { "filtered": { "query": { "query_string": { "query": "blah.jpg" } } } } } You don't specify a field, so by default it looks for "blah.jpg" in the _all field, which contains the value from your image field (plus all other fields) which is why it matches. If you do something like this: { "query": { "filtered": { "query": { "query_string": { "query": "image:blah.jpg" } } } } } Then you won't get a match if the image field is not indexed. 4) You can embed translations/tags in your document as additional fields but you will need to reindex the document every time you change it or any of its contents (such as translations/tags). -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/8cd43f57-7c5f-4d27-a472-ecdf573fe891%40googlegroups.com. For more options, visit https://groups.google.com/groups/opt_out.
