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position_increment_gap

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`position_increment_gap`

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Analyzed text fields take term positions into account, in order to be able to support proximity or phrase queries. When indexing text fields with multiple values a "fake" gap is added between the values to prevent most phrase queries from matching across the values. The size of this gap is configured using position_increment_gap and defaults to 100.

For example:

response = client.index(
  index: 'my-index-000001',
  id: 1,
  body: {
    names: [
      'John Abraham',
      'Lincoln Smith'
    ]
  }
)
puts response

response = client.search(
  index: 'my-index-000001',
  body: {
    query: {
      match_phrase: {
        names: {
          query: 'Abraham Lincoln'
        }
      }
    }
  }
)
puts response

response = client.search(
  index: 'my-index-000001',
  body: {
    query: {
      match_phrase: {
        names: {
          query: 'Abraham Lincoln',
          slop: 101
        }
      }
    }
  }
)
puts response

PUT my-index-000001/_doc/1
{
  "names": [ "John Abraham", "Lincoln Smith"]
}

GET my-index-000001/_search
{
  "query": {
    "match_phrase": {
      "names": {
        "query": "Abraham Lincoln" 
      }
    }
  }
}

GET my-index-000001/_search
{
  "query": {
    "match_phrase": {
      "names": {
        "query": "Abraham Lincoln",
        "slop": 101 
      }
    }
  }
}

	This phrase query doesn’t match our document which is totally expected.
	This phrase query matches our document, even though `Abraham` and `Lincoln` are in separate strings, because `slop` > `position_increment_gap`.

The position_increment_gap can be specified in the mapping. For instance:

response = client.indices.create(
  index: 'my-index-000001',
  body: {
    mappings: {
      properties: {
        names: {
          type: 'text',
          position_increment_gap: 0
        }
      }
    }
  }
)
puts response

response = client.index(
  index: 'my-index-000001',
  id: 1,
  body: {
    names: [
      'John Abraham',
      'Lincoln Smith'
    ]
  }
)
puts response

response = client.search(
  index: 'my-index-000001',
  body: {
    query: {
      match_phrase: {
        names: 'Abraham Lincoln'
      }
    }
  }
)
puts response

PUT my-index-000001
{
  "mappings": {
    "properties": {
      "names": {
        "type": "text",
        "position_increment_gap": 0 
      }
    }
  }
}

PUT my-index-000001/_doc/1
{
  "names": [ "John Abraham", "Lincoln Smith"]
}

GET my-index-000001/_search
{
  "query": {
    "match_phrase": {
      "names": "Abraham Lincoln" 
    }
  }
}

	The first term in the next array element will be 0 terms apart from the last term in the previous array element.
	The phrase query matches our document which is weird, but its what we asked for in the mapping.

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