-->

position_increment_gap

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:

PUT my_index/_doc/1
{
    "names": [ "John Abraham", "Lincoln Smith"]
}

GET my_index/_search
{
    "query": {
        "match_phrase": {
            "names": {
                "query": "Abraham Lincoln" 
            }
        }
    }
}

GET my_index/_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:

PUT my_index
{
  "mappings": {
    "properties": {
      "names": {
        "type": "text",
        "position_increment_gap": 0 
      }
    }
  }
}

PUT my_index/_doc/1
{
    "names": [ "John Abraham", "Lincoln Smith"]
}

GET my_index/_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.