Add attributesToRetrieve for facetDistribution

[mmmcorpsvit]

import pprint

import meilisearch

client = meilisearch.Client('http://127.0.0.1:7700', 'meili_master_key')
index_name = 'cars'
documents = [
    {'id': 1, 'slug': 'damage1', 'name': 'Damage 1', 'name_ua': 'Пошкодження 1'},
    {'id': 2, 'slug': 'damage3', 'name': 'Damage 3', 'name_ua': 'Пошкодження 3'},
    {'id': 3, 'slug': 'damage3', 'name': 'Damage 3', 'name_ua': 'Пошкодження 3'},
]
client.create_index(uid=index_name, options={'primaryKey': 'id'})
client.index(index_name).add_documents(documents)
client.index(index_name).update_settings(
    {
        'filterableAttributes': ['id', 'slug', 'damage', 'name', 'name_ua'],
    }
)

results = client.index(index_name).facet_search(
    'slug',
    opt_params={
        'attributesToRetrieve': ['name', 'name_ua'],
        'facetAttributes': ['slug'],
    }
)

pprint.pprint(results, depth=10, indent=4)

how get count, and additionally: "name", "name_ua"?
https://blog.meilisearch.com/id-based-facets-guide/ - only one way - merge id and data, but this very ugly idea - because very slow)

Please add support to get count and another field, this critically important for e-shops to reduce queries to only one for get full facet information (count, names, something else...)

[macraig]

Hello @mmmcorpsvit , I'm not sure if I understand your need correctly. Facets are a way of categorizing documents and facet search will return the number (count) of documents that match those categories. What other fields could be returned in a set of facets? Do you mean you'd like to return some of the document fields from the documents that match the facets as well?

[mmmcorpsvit]

for example i have cars (id + name) and attribute color (id + name)

car_id;car_name;color_id;color_name
1;BMW x5;3;gray
2;Mazda X1;7;gray

if i need get facet with count - meilisearch only propose way: facet by color_name, but color name is not unique
so I need do facet by color_id, but in this case get only color_id (without color_name in same query)

same on elasticksearch have this important future:

POST /cars2/_search
{
  "size": 0,
  "aggs": {
    "colors": {
      "terms": {
        "field": "color.id"
      },
      "aggs": {
        "color_details": {
          "top_hits": {
            "_source": {
              "includes": ["color.id", "color.name"]
            },
            "size": 1
          }
        }
      }
    }
  }
}

{
  "took": 0,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 5,
      "relation": "eq"
    },
    "max_score": null,
    "hits": []
  },
  "aggregations": {
    "colors": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": 1,
          "doc_count": 2,
          "color_details": {
            "hits": {
              "total": {
                "value": 2,
                "relation": "eq"
              },
              "max_score": 1,
              "hits": [
                {
                  "_index": "cars2",
                  "_id": "1",
                  "_score": 1,
                  "_source": {
                    "color": {
                      "id": 1,
                      "name": "Red"
                    }
                  }
                }
              ]
            }
          }
        },
        {
          "key": 2,
          "doc_count": 2,
          "color_details": {
            "hits": {
              "total": {
                "value": 2,
                "relation": "eq"
              },
              "max_score": 1,
              "hits": [
                {
                  "_index": "cars2",
                  "_id": "2",
                  "_score": 1,
                  "_source": {
                    "color": {
                      "id": 2,
                      "name": "Blue"
                    }
                  }
                }
              ]
            }
          }
        },
        {
          "key": 3,
          "doc_count": 1,
          "color_details": {
            "hits": {
              "total": {
                "value": 1,
                "relation": "eq"
              },
              "max_score": 1,
              "hits": [
                {
                  "_index": "cars2",
                  "_id": "4",
                  "_score": 1,
                  "_source": {
                    "color": {
                      "id": 3,
                      "name": "Green"
                    }
                  }
                }
              ]
            }
          }
        }
      ]
    }
  }
}

[macraig]

Hi again @mmmcorpsvit , apologies for the late reply. I gather that you want to combine a terms aggregation with a top hits aggregation.

The result would be the facet count per color.id, while getting the top document of each bucket that also contains the color.name information as well. Is that correct?