如何在弹性搜索中使用must with或condition中的多个匹配短语？

Question

GET questiondetails/question/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "match_phrase": {
            "tags.keyword": "azure-data"
          }
        },
        {
          "match_phrase": {
            "body": "azure-data"
          }
        },
        {
          "match_phrase": {
            "title": "azure-data"
          }
        },
        {
          "match_phrase": {
            "answers.body": "azure-data"
          }
        }
      ],
      "minimum_should_match": 1,
      "filter": {
        "range": {
          "creation_date": {
            "gte": 1584748800,
            "lte": 1585612800
          }
        }
      }
    }
  },
  "size": "10000"
}

添加注释

获取questiondetails_new/question/_search{“query”：{“bool”：{“should”：[{“match_prace”：{“tags.keyword”：“azure-data-factory”}},{“match_prach”：{“title”：“azure-data-factory”}}],“minimum_should_match”：1,“filter”：{“range”：{“creation_date”：{“gte”：1585170170,“lte”：1585170180}}}

在这个查询中，我需要所有与azure-data-factory完全匹配的文档，或者在titile（String）中有azure-data-factory的文档。应该是一个或搜索。但它与值为azure-data-factory-2的标记的匹配也是

Answer 1

添加一个char过滤器，在索引时将“-”替换为“_”。您不需要更改输入文本（它将与“-”一起工作）

PUT index38
{
  "settings": {
    "analysis": {
      "char_filter": {
        "my_char_filter": {
          "type": "mapping",
          "mappings": [
            "- => _"
          ]
        }
      },
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "standard",
          "char_filter": [
            "my_char_filter"
          ],
          "filter": [
            "lowercase"
          ]
        }
      }
    }
  },
  "mappings": {
      "properties": {
        "tags": {
          "type": "text",
          "analyzer": "my_analyzer",
          "fields": {
            "keyword":{
              "type":"keyword"
            }
          }
        },
        "title": {
          "type": "text",
          "analyzer": "my_analyzer",
          "fields": {
            "keyword":{
              "type":"keyword"
            }
          }
        }
      }
    }
}

查询：

{
  "query": {
    "bool": {
      "should": [
        {
          "match_phrase": {
            "tags": "azure-data-factory"
          }
        },
        {
          "bool": {
            "must_not": [
              {
                "match_phrase": {
                  "tags": "azure-data-factory"
                }
              }
            ],
            "should": [
              {
                "match_phrase": {
                  "body": "azure-data-factory"
                }
              },
              {
                "match_phrase": {
                  "title": "azure-data-factory"
                }
              },
              {
                "match_phrase": {
                  "answers.body": "azure-data-factory"
                }
              }
            ]
          }
        }
      ],
      "minimum_should_match": 1
    }
  },
  "size": "100"
}

如果使用默认分析器分析文本“azure-data-factory”，它将生成3个标记[“azure”,“data”,“factory”]

GET index38/_analyze
{
  "text": "azure-data-factory"
}

Result:

"tokens" : [
    {
      "token" : "azure",
      "start_offset" : 0,
      "end_offset" : 5,
      "type" : "<ALPHANUM>",
      "position" : 0
    },
    {
      "token" : "data",
      "start_offset" : 6,
      "end_offset" : 10,
      "type" : "<ALPHANUM>",
      "position" : 1
    },
    {
      "token" : "factory",
      "start_offset" : 11,
      "end_offset" : 18,
      "type" : "<ALPHANUM>",
      "position" : 2
    }
  ]

GET index38/_analyze
{
  "text": "azure-data-factory",
  "analyzer": "my_analyzer"
}

Result:

"tokens" : [
    {
      "token" : "azure_data_factory",
      "start_offset" : 0,
      "end_offset" : 18,
      "type" : "<ALPHANUM>",
      "position" : 0
    }
]