Rails elasticsearch _geo_distance and custom scoring/sorting

In fact, there are many ways to "control" the scoring. Before indexing, if you already some document is meant to get high score/boost. You can give high score for the special document before indexing, please reference here.

If you cannot determine the boost before the indexing, you can boost it in the query command. About the boosting query, there are also many options and it's dependent on what kind query you used.

For query string query:

You can boost some fields, such as fields" : ["content", "name.*^5"], or boost some query command such as, quick^2 fox(this might work for you, just extra boost the name).

For others:

You can give boost for term query, such as boosting the "ivan" case:

"term" : {"name" : {"value" : "ivan","boost" : 10.0}}

you can wrap it into bool query and boost the desired case. ex. find all 'ivan', boost 'ji' on name field.

{ "query" : { "bool" : { "must": [{"match":{"name":"ivan"}}],
"should" : [ { "term" : { "name": { "value" : "ji", "boost" : 10 }}}]}}}

Except for term query, there are a lot of queries that support boost, such as prefix query, match query. You can use it under situations. Here are some official examples: http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/_boosting_query_clauses.html

Boosting might not easy for controlling score, because it needs normalization. You can specify the score using the function_score query to specify the direct score: It's really a useful query if you need more directly control.

In short, you can wrap your query in bool and add some boost for the name matching, as follow:

{ "query" : {    "bool" : {    "must": [            {"filtered" : {            "filter" : {                "geo_distance" : {                    "distance" : "2000km",                    "loc" : {                        "lat" : 10,                        "lon" : 10                    }                }            }        }}],    "should" : [ { "term" : { "name": { "value" : "ivan", "boost" : 10 }}}]}},"sort" : [            "_score",    {        "_geo_distance" : {            "loc" : [10, 10],            "order" : "asc",            "unit" : "km",            "mode" : "min",            "distance_type" : "sloppy_arc"        }    }]}

For more detailed, you can check my gist https://gist.github.com/hxuanji/e5acd9a5174ea10c08b8. I boost the "ivan" name. In the result, the "ivan" document becomes first rather than the (10,10) document.