elasticsearch - 在 Elasticsearch 查询中检索匹配的数组元素

Question

在电影数据库中，我存储了用户对每部电影的评分(0 到 5 星)。我在 Elastic Search(版本 1.2.2)中索引了以下文档结构

"_index": "my_index"
"_type": "film",
"_id": "6629",
"_source": {
  "id": "6629",
  "title": "Fight Club",
  "ratings" : [
    { "user_id" : 1234, "rating_value" : 3 },
    { "user_id" : 4567, "rating_value" : 2 },
    { "user_id" : 7890, "rating_value" : 1 }
    .....
  ]
}

"_index": "my_index"
"_type": "film",
"_id": "6630",
"_source": {
  "id": "6630",
  "title": "Pulp Fiction",
  "ratings" : [
    { "user_id" : 1234, "rating_value" : 1 },
    { "user_id" : 7654, "rating_value" : 2 },
    { "user_id" : 4321, "rating_value" : 5 }
    .....
  ]
}

等...

我的目标是在一次搜索中获得用户(假设用户 1234)评分的所有电影，以及 rating_value

如果我进行以下搜索

GET my_index/film/_search
{
  "query": {
    "match": {
      "ratings.user_id": "1234"
    }
  }
}

对于所有匹配的电影，我得到了整个文档，然后，我必须解析整个评级数组以找出数组中的哪个元素与我的查询匹配，以及与 user_id 1234 关联的 rating_value 是多少。

理想情况下，我希望这个查询的结果是

"hits": [ {
  "_index": "my_index"
  "_type": "film",
  "_id": "6629",
  "_source": {
    "id": "6629",
    "title": "Fight Club",
    "ratings" : [
      { "user_id" : 1234, "rating_value" : 3 }, // <= only the row that matches the query
    ]
  },
  "_index": "my_index"
  "_type": "film",
  "_id": "6630",
  "_source": {
    "id": "6630",
    "title": "Pulp Fiction",
    "ratings" : [
      { "user_id" : 1234, "rating_value" : 1 },  // <= only the row that matches the query
    ]
  }
} ]

提前致谢

Answer 1

如我之前的评论所述，我设法使用聚合 检索值。

下面是我是如何做到的。

首先，我使用的映射:

PUT test/movie/_mapping
{
  "properties": {
    "title":{
      "type": "string",
      "index": "not_analyzed"
    },
    "ratings": {
      "type": "nested"
    }
  }
}

我选择不为标题编制索引，但您可以使用 fields 属性并将其保留为“原始”字段。

然后，电影索引:

PUT test/movie/6629
{
  "title": "Fight Club",
  "ratings" : [
    { "user_id" : 1234, "rating_value" : 3 },
    { "user_id" : 4567, "rating_value" : 2 },
    { "user_id" : 7890, "rating_value" : 1 }
  ]
}


PUT test/movie/4456
{
  "title": "Jumanji",
  "ratings" : [
    { "user_id" : 1234, "rating_value" : 4 },
    { "user_id" : 4567, "rating_value" : 3 },
    { "user_id" : 4630, "rating_value" : 5 }
  ]
}

PUT test/movie/6547
{
  "title": "Hook",
  "ratings" : [
    { "user_id" : 1234, "rating_value" : 4 },
    { "user_id" : 7890, "rating_value" : 1 }
  ]
}

聚合查询是:

GET test/movie/_search
{
  "aggs": {
    "by_movie": {
      "terms": {
        "field": "title"
      },
      "aggs": {
        "ratings_by_user": {
          "nested": {
            "path": "ratings"
          },"aggs": {
            "for_user_1234": {
              "filter": {
                "term": {
                  "ratings.user_id": "1234"
                }
              },
              "aggs": {
                "rating_value": {
                  "terms": {
                    "field": "ratings.rating_value"
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

最后，这是对以前的文档执行此查询时产生的输出:

"aggregations": {
  "by_movie": {
     "buckets": [
        {
           "key": "Fight Club",
           "doc_count": 1,
           "ratings_by_user": {
              "doc_count": 3,
              "for_user_1234": {
                 "doc_count": 1,
                 "rating_value": {
                    "buckets": [
                       {
                          "key": 3,
                          "key_as_string": "3",
                          "doc_count": 1
                       }
                    ]
                 }
              }
           }
        },
        {
           "key": "Hook",
           "doc_count": 1,
           "ratings_by_user": {
              "doc_count": 2,
              "for_user_1234": {
                 "doc_count": 1,
                 "rating_value": {
                    "buckets": [
                       {
                          "key": 4,
                          "key_as_string": "4",
                          "doc_count": 1
                       }
                    ]
                 }
              }
           }
        },
        {
           "key": "Jumanji",
           "doc_count": 1,
           "ratings_by_user": {
              "doc_count": 3,
              "for_user_1234": {
                 "doc_count": 1,
                 "rating_value": {
                    "buckets": [
                       {
                          "key": 4,
                          "key_as_string": "4",
                          "doc_count": 1
                       }
                    ]
                 }
              }
           }
        }
     ]
  }

由于嵌套语法，这有点乏味，但您将能够为每部电影检索提供的用户(此处为 1234)的评分。

希望这对您有所帮助!