具有分层类别、子类别的 Elasticsearch 聚合；限制级别

Question

我有带有类别字段的产品。使用聚合我可以获得包含所有子类别的完整类别。我想限制方面的级别。

例如我有这样的方面：

auto, tools & travel    (115)
auto, tools & travel > luggage tags (90)
auto, tools & travel > luggage tags > luggage spotters  (40)
auto, tools & travel > luggage tags > something else    (50)
auto, tools & travel > car organizers   (25)

使用聚合之类的

"aggs": {
    "cat_groups": {
      "terms": {
        "field": "categories.keyword",
        "size": 10,
       "include": "auto, tools & travel > .*"
      }
    }
}

我得到了喜欢的桶

"buckets": [
        {
          "auto, tools & travel > luggage tags",
          "doc_count": 90
        },
        {
          "key": "auto, tools & travel > luggage tags > luggage spotters",
          "doc_count": 40
        },
        {
          "key": "auto, tools & travel > luggage tags > something else",
          "doc_count": 50
        },
        {
          "key": "auto, tools & travel > car organizers",
          "doc_count": 25
        }
]

但我想限制级别。例如我只想获得auto, tools & travel > luggage tags 的结果。如何限制级别？ 顺便说一句，"exclude": ".* > .* > .*" 不适合我。

我需要根据搜索得到不同级别的桶。有时一级，有时二级或三级。当我想要第一级时，我不希望第二级出现在存储桶上；以此类推其他级别。

Elasticsearch 6.4 版

Answer 1

我终于能够弄清楚以下技术。

我已经使用Path Hierarchy Tokenizer 实现了custom analyzer，并且我创建了名为categories 的多字段，以便您可以将categories.facets 用于聚合/构面，并使用categories 进行普通文本搜索。

自定义分析器仅适用于categories.facets

请注意属性"fielddata": "true" 我的字段categories.facet

映射

PUT myindex
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "my_tokenizer"
        }
      },
      "tokenizer": {
        "my_tokenizer": {
          "type": "path_hierarchy",
          "delimiter": ">"
        }
      }
    }
  },
  "mappings": {
    "mydocs": {
      "properties": {
        "categories": {
          "type": "text",
          "fields": {
            "facet": { 
              "type":  "text",
              "analyzer": "my_analyzer",
              "fielddata": "true"
            }
          }
        }
      }
    }
  }
}

示例文档

POST myindex/mydocs/1
{
    "categories" : "auto, tools & travel > luggage tags > luggage spotters"
}

POST myindex/mydocs/2
{
    "categories" : "auto, tools & travel > luggage tags > luggage spotters"
}

POST myindex/mydocs/3
{
    "categories" : "auto, tools & travel > luggage tags > luggage spotters"
}

POST myindex/mydocs/4
{
    "categories" : "auto, tools & travel > luggage tags > something else"
}

查询

您可以尝试以下您正在寻找的查询。我再次实现了Filter Aggregation，因为您只需要特定的单词以及Terms Aggregation。

{
  "size": 0,
  "aggs":{
    "facets": {
      "filter": { 
          "bool": {
            "must": [
              { "match": { "categories": "luggage"} }
            ]
         }
      },
      "aggs": {
        "categories": {
          "terms": {
            "field": "categories.facet"
          }
        }
      }
    }
  }
}

响应

{
    "took": 43,
    "timed_out": false,
    "_shards": {
        "total": 1,
        "successful": 1,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": 11,
        "max_score": 0,
        "hits": []
    },
    "aggregations": {
        "facets": {
            "doc_count": 4,
            "categories": {
                "doc_count_error_upper_bound": 0,
                "sum_other_doc_count": 0,
                "buckets": [
                    {
                        "key": "auto, tools & travel ",
                        "doc_count": 4
                    },
                    {
                        "key": "auto, tools & travel > luggage tags ",
                        "doc_count": 4
                    },
                    {
                        "key": "auto, tools & travel > luggage tags > luggage spotters",
                        "doc_count": 3
                    },
                    {
                        "key": "auto, tools & travel > luggage tags > something else",
                        "doc_count": 1
                    }
                ]
            }
        }
    }
}

关于聊天的最终答案发布讨论

POST myindex/_search
{
  "size": 0,
  "aggs":{
    "facets": {
      "filter": { 
          "bool": {
            "must": [
              { "match": { "categories": "luggage"} }
          ]
        }
      },
      "aggs": {
        "categories": {
          "terms": {
            "field": "categories.facet",
            "exclude": ".*>{1}.*>{1}.*"
          }
        }
      }
    }
  }
}

请注意，我添加了 exclude 和 regular expression，因此它不会考虑任何出现多次 > 的方面

如果有帮助，请告诉我。

Answer 2

只需添加一个名为 level 的整数字段，表示您的类别在层次结构中的级别。只需计算分隔符“>”的出现次数并将其保存为值。然后将 rangeQuery 添加到您的 boolQuery。

将此添加到您的架构中：

"level": {
    "type": "integer",
    "store": "true",
    "index": "true"
}

在您的代码中，您有类似这样的内容，它计算表示层次结构级别的分隔符的数量（没有分隔符意味着主类别）：

public Builder(final String path) {
    this.path = path;
    this.level = StringUtils.countMatches(path, DELIMITER);
}

然后您的查询搜索可能会是这样的：

{
    "query": {
        "bool": {
            "filter": [
                {
                    "prefix": {
                        "category": {
                            "value": "auto, tools & travel",
                            "boost": 1
                        }
                    }
                },
                {
                    "range": {
                        "level": {
                            "from": 2,
                            "to": 4,
                            "include_lower": true,
                            "include_upper": true,
                            "boost": 1
                        }
                    }
                }
            ],
            "adjust_pure_negative": true,
            "boost": 1
        }
    }
}