Elasticsearch: Top k results per keyword

Question

We have the following document in elasticsearch.

class Query(DocType):
    text = Text(analyzer='snowball', fields={'raw': Keyword()})
    src = Keyword()

Now we want top k results for each src. How can we achieve this?

Example:- Lets assume we index the following:

# src: place_order
Query(text="I want to order food", src="place_order")
Query(text="Take my order", src="place_order")
...

# src: payment
Query(text="How to pay ?", src="payment")
Query(text="Do you accept credit card ?", src="payment")
...

Now if the user writes a query take my order please along with the credit card details, and k=1, then we should return the following two results

[{"text": "Take my order", "src": "place_order", }, 
 {"text": "Do you accept credit card ?", "src": "payment"}
]

Here since k=1, we are returning the just one result for each src.

Answer 1

You may try top hits aggregation which will return top N matching documents per each bucket in aggregation.

For the example in your post the query might look like this:

POST queries/query/_search
{
  "query": {
    "match": {
      "text": "take my order please along with the credit card details"
    }
  },
  "aggs": {
    "src types": {
      "terms": {
        "field": "src"
      },
      "aggs": {
        "best hit": {
          "top_hits": {
            "size": 1
          }
        }
      }
    }
  }
}

The search on the text query restricts the set of documents for the aggregation. "src types" aggregation groups all src values found in the matched documents, and "best hit" selects one most relevant document per bucket (size parameter can be changed according to your needs).

The result of the query would be like the following:

{
  "hits": {
    "total": 3,
    "max_score": 1.3862944,
    "hits": [
      {
        "_index": "queries",
        "_type": "query",
        "_id": "VD7QVmABl04oXt2HGbGB",
        "_score": 1.3862944,
        "_source": {
          "text": "Do you accept credit card ?",
          "src": "payment"
        }
      },
      {
        "_index": "queries",
        "_type": "query",
        "_id": "Uj7PVmABl04oXt2HlLFI",
        "_score": 0.8630463,
        "_source": {
          "text": "Take my order",
          "src": "place_order"
        }
      },
      {
        "_index": "queries",
        "_type": "query",
        "_id": "UT7PVmABl04oXt2HKLFy",
        "_score": 0.6931472,
        "_source": {
          "text": "I want to order food",
          "src": "place_order"
        }
      }
    ]
  },
  "aggregations": {
    "src types": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "place_order",
          "doc_count": 2,
          "best hit": {
            "hits": {
              "total": 2,
              "max_score": 0.8630463,
              "hits": [
                {
                  "_index": "queries",
                  "_type": "query",
                  "_id": "Uj7PVmABl04oXt2HlLFI",
                  "_score": 0.8630463,
                  "_source": {
                    "text": "Take my order",
                    "src": "place_order"
                  }
                }
              ]
            }
          }
        },
        {
          "key": "payment",
          "doc_count": 1,
          "best hit": {
            "hits": {
              "total": 1,
              "max_score": 1.3862944,
              "hits": [
                {
                  "_index": "queries",
                  "_type": "query",
                  "_id": "VD7QVmABl04oXt2HGbGB",
                  "_score": 1.3862944,
                  "_source": {
                    "text": "Do you accept credit card ?",
                    "src": "payment"
                  }
                }
              ]
            }
          }
        }
      ]
    }
  }
}

Hope that helps!