Match-only text field type
A match_only_text field is a variant of a text field designed for full-text search when scoring and positional information of terms within a document are not critical.
A match_only_text field is different from a text field in the following ways:
- Omits storing positions, frequencies, and norms, reducing storage requirements.
- Disables scoring so that all matching documents receive a constant score of 1.0.
- Supports all query types except interval and span queries.
Choose the match_only_text field type to prioritize efficient full-text search over complex ranking and positional queries while optimizing storage costs. Using match_only_text creates significantly smaller indexes, which results in lower storage costs, especially for large datasets.
Use a match_only_text field when you need to quickly find documents containing specific terms without the overhead of storing frequencies and positions. The match_only_text field type is not the best choice for ranking results based on relevance or for queries that rely on term proximity or order, like interval or span queries. While this field type does support phrase queries, their performance isn’t as efficient as when using the text field type. If identifying exact phrases or their locations within documents is essential, use the text field type instead.
Example
Create a mapping with a match_only_text field:
PUT movies
{
"mappings" : {
"properties" : {
"title" : {
"type" : "match_only_text"
}
}
}
}
Parameters
While match_only_text supports most parameters available for text fields, modifying most of them can be counterproductive. This field type is intended to be simple and efficient, minimizing data stored in the index to optimize storage costs. Therefore, keeping the default settings is generally the best approach. Any modifications beyond analyzer settings can reintroduce overhead and negate the efficiency benefits of match_only_text.
The following table lists all parameters available for match_text_only fields.
| Parameter | Description |
|---|---|
analyzer | The analyzer to be used for the field. By default, it will be used at index time and at search time. To override it at search time, set the search_analyzer parameter. Default is the standard analyzer, which uses grammar-based tokenization and is based on the Unicode Text Segmentation algorithm. |
boost | All hits are assigned a score of 1 and are multiplied by boost to produce the final score for the query clause. |
eager_global_ordinals | Specifies whether global ordinals should be loaded eagerly on refresh. If the field is often used for aggregations, this parameter should be set to true. Default is false. |
fielddata | A Boolean value that specifies whether to access analyzed tokens for sorting, aggregation, and scripting. Default is false. |
fielddata_frequency_filter | A JSON object specifying that only those analyzed tokens whose document frequency is between the min and max values (provided as either an absolute number or a percentage) should be loaded into memory. Frequency is computed per segment. Parameters: min, max, min_segment_size. Default is to load all analyzed tokens. |
fields | To index the same string in several ways (for example, as a keyword and text), provide the fields parameter. You can specify one version of the field to be used for search and another to be used for sorting and aggregation. |
index | A Boolean value that specifies whether the field should be searchable. Default is true. |
index_options | You cannot modify this parameter. |
index_phrases | Not supported. |
index_prefixes | Not supported. |
meta | Accepts metadata for this field. |
norms | Norms are disabled and cannot be enabled. |
position_increment_gap | Although positions are disabled, position_increment_gap behaves similarly to the text field when used in phrase queries. Such queries may be slower but are still functional. |
similarity | Setting similarity has no impact. The match_only_text field type doesn’t support queries like more_like_this, which rely on similarity. Use a keyword or text field for queries that rely on similarity. |
term_vector | Term vectors are supported, but using them is discouraged because it contradicts the primary purpose of this field—storage optimization. |
Migrating a field from text to match_only_text
You can use the Reindex API to migrate from a text field to match_only_text by updating the correct mapping in the destination index.
In the following example, the source index contains a title field of type text.
Create a destination index with the title field mapped as text:
PUT destination
{
"mappings" : {
"properties" : {
"title" : {
"type" : "match_only_text"
}
}
}
}
Reindex the data:
POST _reindex
{
"source": {
"index":"source"
},
"dest": {
"index":"destination"
}
}