ElasticSearch 按嵌套字段中的匹配数排序

Question

这里完全是新手，很可能正在尝试做不可能的事情。我想将以下结构存储在 Elasticsearch 中:

{
    "id" : 1,
    "code" : "03f3301c-4089-11e7-a919-92ebcb67fe33",
    "countries" : [
        {
            "id" : 1,
            "name" : "Netherlands"
        },
        {
            "id" : 2,
            "name" : "United Kingdom"
        }
    ],
    "tags" : [
        {
            "id" : 1,
            "name" : "Scanned"
        },
        {
            "id" : 2,
            "name" : "Secured"
        },
        {
            "id" : 3,
            "name" : "Cleared"
        }
    ]
}

我可以完全控制它的存储方式，因此结构可以改变，但它应该以某种形式包含所有这些字段。我希望能够通过 countries 和 tags 查询此数据，以便返回所有具有至少一个匹配项的项目，并按匹配项数排序。如果可能的话，我宁愿不进行全文搜索。

例如:

id, code, country ids, tag ids
1,  ...,  [1, 2, 3],   [1]
2,  ...,  [1],         [1, 2, 3]

对于问题:“其中哪些在国家/地区 1 或具有标签 1 或具有标签 2”，应返回:

2, ..., [1], [1, 2, 3]
1, ..., [1, 2, 3], [1]

按这个顺序，因为第二行在上面的disjunction中匹配了更多的子查询。

本质上，我想复制这个 SQL 查询:

SELECT p.id, p.code, COUNT(p.id) FROM packages p
LEFT JOIN tags t ON t.package_id = p.id
LEFT JOIN countries c ON c.package_id = p.id
WHERE t.id IN (1, 2, 3) OR c.id IN (1, 2, 3)
GROUP BY p.id
ORDER BY COUNT(p.id);

如果重要的话，我正在使用 ElasticSearch 2.4.5。

希望我已经足够清楚了。感谢您的帮助!

Answer 1

您需要 countries 和 tags 为 nested 类型。此外，您需要使用 function_score 控制评分，为 function_score 内的查询提供 1 的 weight 并使用 boost_mode 和 score_mode。最后你可以使用这个查询:

GET /nested/test/_search
{
  "query": {
    "function_score": {
      "query": {
        "match_all": {}
      }, 
      "functions": [
        {
          "filter": {
            "nested": {
              "path": "tags",
              "query": {
                "term": {
                  "tags.id": 1
                }
              }
            }
          },
          "weight": 1
        },
        {
          "filter": {
            "nested": {
              "path": "tags",
              "query": {
                "term": {
                  "tags.id": 2
                }
              }
            }
          },
          "weight": 1
        },
        {
          "filter": {
            "nested": {
              "path": "countries",
              "query": {
                "term": {
                  "countries.id": 1
                }
              }
            }
          },
          "weight": 1
        }
      ],
      "boost_mode": "replace", 
      "score_mode": "sum"
    }
  }
}

为了更完整的测试用例，我还提供了映射和测试数据:

PUT nested
{
  "mappings": {
    "test": {
      "properties": {
        "tags": {
          "type": "nested",
          "properties": {
            "name": {
              "type": "string",
              "index": "not_analyzed"
            }
          }
        },
        "countries": {
          "type": "nested",
          "properties": {
            "name": {
              "type": "string",
              "index": "not_analyzed"
            }
          }
        }
      }
    }
  }
}

POST nested/test/_bulk
{"index":{"_id":1}}
{"name":"Foo Bar","tags":[{"id":2,"name":"My Tag 5"},{"id":3,"name":"My Tag 7"}],"countries":[{"id":1,"name":"USA"}]}
{"index":{"_id":2}}
{"name":"Foo Bar","tags":[{"id":3,"name":"My Tag 6"}],"countries":[{"id":1,"name":"USA"},{"id":2,"name":"UK"},{"id":3,"name":"UAE"}]}
{"index":{"_id":3}}
{"name":"Foo Bar","tags":[{"id":1,"name":"My Tag 4"},{"id":3,"name":"My Tag 1"}],"countries":[{"id":3,"name":"UAE"}]}
{"index":{"_id":4}}
{"name":"Foo Bar","tags":[{"id":1,"name":"My Tag 1"},{"id":2,"name":"My Tag 4"},{"id":3,"name":"My Tag 2"}],"countries":[{"id":2,"name":"UK"},{"id":3,"name":"UAE"}]}