I currently have parents indexed in elastic search (documents) and child (comments) related to these documents. My first objective was to search for a document with more than N comments, based on a child query. Here is how I did it:
documents/document/_search
{
"min_score": 0,
"query": {
"has_child" : {
"type" : "comment",
"score_type" : "sum",
"boost": 1,
"query" : {
"range": {
"date": {
"lte": 20130204,
"gte": 20130201,
"boost": 1
}
}
}
}
}
}
I used score to calculate the amount of comments a document has and then I filtered the documents by this amount, using "min_score". Now, my objective is to search not just comments, but several other child documents related to the document, always based on frequency. Something like the query bellow:
documents/document/_search
{
"query": {
"match_all": {
}
},
"filter" : {
"and" : [{
"query": {
"has_child" : {
"type" : "comment",
"query" : {
"range": {
"date": {
"lte": 20130204,
"gte": 20130201
}
}
}
}
}
},
{
"or" : [
{"query": {
"has_child" : {
"type" : "comment",
"query" : {
"match": {
"text": "Finally"
}
}
}
}
},
{ "query": {
"has_child" : {
"type" : "comment",
"query" : {
"match": {
"text": "several"
}
}
}
}
}
]
}
]
}
}
The query above works fine, but it doesn't filter based on frequency as the first one does. As filters are computed before scores are calculated, I cannot use min_score to filter each child query.
Any solutions to this problem?
There is no score at all associated with filters. I'd suggest to move the whole logic to the query part and use a bool query to combine the different queries together.