---
title: Path hierarchy tokenizer
description: The path_hierarchy tokenizer takes a hierarchical value like a filesystem path, splits on the path separator, and emits a term for each component in the...
url: https://www.elastic.co/elastic/docs-builder/docs/2322/reference/text-analysis/analysis-pathhierarchy-tokenizer
---

# Path hierarchy tokenizer
The `path_hierarchy` tokenizer takes a hierarchical value like a filesystem path, splits on the path separator, and emits a term for each component in the tree. The `path_hierarcy` tokenizer uses Lucene’s [PathHierarchyTokenizer](https://lucene.apache.org/core/10_0_0/analysis/common/org/apache/lucene/analysis/path/PathHierarchyTokenizer.md) underneath.

## Example output

```json

{
  "tokenizer": "path_hierarchy",
  "text": "/one/two/three"
}
```

The above text would produce the following terms:
```text
[ /one, /one/two, /one/two/three ]
```


## Configuration

The `path_hierarchy` tokenizer accepts the following parameters:
<definitions>
  <definition term="delimiter">
    The character to use as the path separator. Defaults to `/`.
  </definition>
  <definition term="replacement">
    An optional replacement character to use for the delimiter. Defaults to the `delimiter`.
  </definition>
  <definition term="buffer_size">
    The number of characters read into the term buffer in a single pass. Defaults to `1024`. The term buffer will grow by this size until all the text has been consumed. It is advisable not to change this setting.
  </definition>
  <definition term="reverse">
    If `true`, uses Lucene’s [ReversePathHierarchyTokenizer](http://lucene.apache.org/core/10_0_0/analysis/common/org/apache/lucene/analysis/path/ReversePathHierarchyTokenizer.md), which is suitable for domain–like hierarchies. Defaults to `false`.
  </definition>
  <definition term="skip">
    The number of initial tokens to skip. Defaults to `0`.
  </definition>
</definitions>


## Example configuration

In this example, we configure the `path_hierarchy` tokenizer to split on `-` characters, and to replace them with `/`. The first two tokens are skipped:
```json

{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_analyzer": {
          "tokenizer": "my_tokenizer"
        }
      },
      "tokenizer": {
        "my_tokenizer": {
          "type": "path_hierarchy",
          "delimiter": "-",
          "replacement": "/",
          "skip": 2
        }
      }
    }
  }
}


{
  "analyzer": "my_analyzer",
  "text": "one-two-three-four-five"
}
```

The above example produces the following terms:
```text
[ /three, /three/four, /three/four/five ]
```

If we were to set `reverse` to `true`, it would produce the following:
```text
[ one/two/three/, two/three/, three/ ]
```


## Detailed examples

A common use-case for the `path_hierarchy` tokenizer is filtering results by file paths. If indexing a file path along with the data, the use of the `path_hierarchy` tokenizer to analyze the path allows filtering the results by different parts of the file path string.
This example configures an index to have two custom analyzers and applies those analyzers to multifields of the `file_path` text field that will store filenames. One of the two analyzers uses reverse tokenization. Some sample documents are then indexed to represent some file paths for photos inside photo folders of two different users.
```json

{
  "settings": {
    "analysis": {
      "analyzer": {
        "custom_path_tree": {
          "tokenizer": "custom_hierarchy"
        },
        "custom_path_tree_reversed": {
          "tokenizer": "custom_hierarchy_reversed"
        }
      },
      "tokenizer": {
        "custom_hierarchy": {
          "type": "path_hierarchy",
          "delimiter": "/"
        },
        "custom_hierarchy_reversed": {
          "type": "path_hierarchy",
          "delimiter": "/",
          "reverse": "true"
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "file_path": {
        "type": "text",
        "fields": {
          "tree": {
            "type": "text",
            "analyzer": "custom_path_tree"
          },
          "tree_reversed": {
            "type": "text",
            "analyzer": "custom_path_tree_reversed"
          }
        }
      }
    }
  }
}


{
  "file_path": "/User/alice/photos/2017/05/16/my_photo1.jpg"
}


{
  "file_path": "/User/alice/photos/2017/05/16/my_photo2.jpg"
}


{
  "file_path": "/User/alice/photos/2017/05/16/my_photo3.jpg"
}


{
  "file_path": "/User/alice/photos/2017/05/15/my_photo1.jpg"
}


{
  "file_path": "/User/bob/photos/2017/05/16/my_photo1.jpg"
}
```

A search for a particular file path string against the text field matches all the example documents, with Bob’s documents ranking highest due to `bob` also being one of the terms created by the standard analyzer boosting relevance for Bob’s documents.
```json

{
  "query": {
    "match": {
      "file_path": "/User/bob/photos/2017/05"
    }
  }
}
```

It’s simple to match or filter documents with file paths that exist within a particular directory using the `file_path.tree` field.
```json

{
  "query": {
    "term": {
      "file_path.tree": "/User/alice/photos/2017/05/16"
    }
  }
}
```

With the reverse parameter for this tokenizer, it’s also possible to match from the other end of the file path, such as individual file names or a deep level subdirectory. The following example shows a search for all files named `my_photo1.jpg` within any directory via the `file_path.tree_reversed` field configured to use the reverse parameter in the mapping.
```json

{
  "query": {
    "term": {
      "file_path.tree_reversed": {
        "value": "my_photo1.jpg"
      }
    }
  }
}
```

Viewing the tokens generated with both forward and reverse is instructive in showing the tokens created for the same file path value.
```json

{
  "analyzer": "custom_path_tree",
  "text": "/User/alice/photos/2017/05/16/my_photo1.jpg"
}


{
  "analyzer": "custom_path_tree_reversed",
  "text": "/User/alice/photos/2017/05/16/my_photo1.jpg"
}
```

It’s also useful to be able to filter with file paths when combined with other types of searches, such as this example looking for any files paths with `16` that also must be in Alice’s photo directory.
```json

{
  "query": {
    "bool" : {
      "must" : {
        "match" : { "file_path" : "16" }
      },
      "filter": {
        "term" : { "file_path.tree" : "/User/alice" }
      }
    }
  }
}
```