how to use multiple match phrases in must with or condition in elastic search?

Question

how to use multiple match phrases in must with or condition in elastic search?

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"
}

tried this query .... I need results in where the word exactly matches in tags or partial match on body or title or answer.body

But its not working .

Adding comment

GET questiondetails_new/question/_search? { "query": { "bool": { "should": [{ "match_phrase": { "tags.keyword": "azure-data-factory" } }, { "match_phrase": { "title": "azure-data-factory" } } ], "minimum_should_match": 1, "filter": { "range": { "creation_date": { "gte": 1585170170, "lte": 1585170180 } } }

In this query i need all the docs which has exact match as azure-data-factory or which has azure-data-factory in its titile (String ). It should be an or search . But its matching with the tags which has the value as azure-data-factory-2 also

Answer 1

Add a char filter which will replace "-" with "_" while indexing. You won't need to change input text(it will work with "-")

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"
            }
          }
        }
      }
    }
}

Query:

{
  "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"
}

If you will analyze text "azure-data-factory" with default analyzer, it will generate 3 tokens ["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
    }
  ]

If you will analyze same text with "my_analyzer" a single token is generated

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
    }
]