Dynamic templates
editDynamic templates
editDynamic templates allow you to define custom mappings that can be applied to dynamically added fields based on:
-
the data type detected by Elasticsearch, with
match_mapping_type
. -
the name of the field, with
match
andunmatch
ormatch_pattern
. -
the full dotted path to the field, with
path_match
andpath_unmatch
.
The original field name {name}
and the detected data type
{dynamic_type}
template variables can be used in
the mapping specification as placeholders.
Dynamic field mappings are only added when a field contains a
concrete value — not null
or an empty array. This means that if the
null_value
option is used in a dynamic_template
, it will only be applied
after the first document with a concrete value for the field has been
indexed.
Dynamic templates are specified as an array of named objects:
"dynamic_templates": [ { "my_template_name": { ... match conditions ... "mapping": { ... } } }, ... ]
The template name can be any string value. |
|
The match conditions can include any of : |
|
The mapping that the matched field should use. |
If a provided mapping contains an invalid mapping snippet, a validation error is returned. Validation occurs when applying the dynamic template at index time, and, in most cases, when the dynamic template is updated. Providing an invalid mapping snippet may cause the update or validation of a dynamic template to fail under certain conditions:
-
If no
match_mapping_type
has been specified but the template is valid for at least one predefined mapping type, the mapping snippet is considered valid. However, a validation error is returned at index time if a field matching the template is indexed as a different type. For example, configuring a dynamic template with nomatch_mapping_type
is considered valid as string type, but if a field matching the dynamic template is indexed as a long, a validation error is returned at index time. -
If the
{name}
placeholder is used in the mapping snippet, validation is skipped when updating the dynamic template. This is because the field name is unknown at that time. Instead, validation occurs when the template is applied at index time.
Templates are processed in order — the first matching template wins. When putting new dynamic templates through the put mapping API, all existing templates are overwritten. This allows for dynamic templates to be reordered or deleted after they were initially added.
match_mapping_type
editThe match_mapping_type
is the data type detected by the JSON parser. Since
JSON doesn’t distinguish a long
from an integer
or a double
from
a float
, it will always choose the wider data type, i.e. long
for integers
and double
for floating-point numbers.
The following data types may be automatically detected:
-
boolean
whentrue
orfalse
are encountered. -
date
when date detection is enabled and a string matching any of the configured date formats is found. -
double
for numbers with a decimal part. -
long
for numbers without a decimal part. -
object
for objects, also called hashes. -
string
for character strings.
*
may also be used in order to match all data types.
For example, if we wanted to map all integer fields as integer
instead of
long
, and all string
fields as both text
and keyword
, we
could use the following template:
PUT my-index-000001 { "mappings": { "dynamic_templates": [ { "integers": { "match_mapping_type": "long", "mapping": { "type": "integer" } } }, { "strings": { "match_mapping_type": "string", "mapping": { "type": "text", "fields": { "raw": { "type": "keyword", "ignore_above": 256 } } } } } ] } } PUT my-index-000001/_doc/1 { "my_integer": 5, "my_string": "Some string" }
The |
|
The |
match
and unmatch
editThe match
parameter uses a pattern to match on the field name, while
unmatch
uses a pattern to exclude fields matched by match
.
The following example matches all string
fields whose name starts with
long_
(except for those which end with _text
) and maps them as long
fields:
match_pattern
editThe match_pattern
parameter adjusts the behavior of the match
parameter
such that it supports full Java regular expression matching on the field name
instead of simple wildcards, for instance:
"match_pattern": "regex", "match": "^profit_\d+$"
path_match
and path_unmatch
editThe path_match
and path_unmatch
parameters work in the same way as match
and unmatch
, but operate on the full dotted path to the field, not just the
final name, e.g. some_object.*.some_field
.
This example copies the values of any fields in the name
object to the
top-level full_name
field, except for the middle
field:
PUT my-index-000001 { "mappings": { "dynamic_templates": [ { "full_name": { "path_match": "name.*", "path_unmatch": "*.middle", "mapping": { "type": "text", "copy_to": "full_name" } } } ] } } PUT my-index-000001/_doc/1 { "name": { "first": "John", "middle": "Winston", "last": "Lennon" } }
Note that the path_match
and path_unmatch
parameters match on object paths
in addition to leaf fields. As an example, indexing the following document will
result in an error because the path_match
setting also matches the object
field name.title
, which can’t be mapped as text:
PUT my-index-000001/_doc/2 { "name": { "first": "Paul", "last": "McCartney", "title": { "value": "Sir", "category": "order of chivalry" } } }
{name}
and {dynamic_type}
editThe {name}
and {dynamic_type}
placeholders are replaced in the mapping
with the field name and detected dynamic type. The following example sets all
string fields to use an analyzer
with the same name as the
field, and disables doc_values
for all non-string fields:
PUT my-index-000001 { "mappings": { "dynamic_templates": [ { "named_analyzers": { "match_mapping_type": "string", "match": "*", "mapping": { "type": "text", "analyzer": "{name}" } } }, { "no_doc_values": { "match_mapping_type":"*", "mapping": { "type": "{dynamic_type}", "doc_values": false } } } ] } } PUT my-index-000001/_doc/1 { "english": "Some English text", "count": 5 }
Template examples
editHere are some examples of potentially useful dynamic templates:
Structured search
editBy default Elasticsearch will map string fields as a text
field with a sub
keyword
field. However if you are only indexing structured content and not
interested in full text search, you can make Elasticsearch map your fields
only as `keyword`s. Note that this means that in order to search those fields,
you will have to search on the exact same value that was indexed.
PUT my-index-000001 { "mappings": { "dynamic_templates": [ { "strings_as_keywords": { "match_mapping_type": "string", "mapping": { "type": "keyword" } } } ] } }
text
-only mappings for strings
editOn the contrary to the previous example, if the only thing that you care about on your string fields is full-text search, and if you don’t plan on running aggregations, sorting or exact search on your string fields, you could tell Elasticsearch to map it only as a text field (which was the default behaviour before 5.0):
PUT my-index-000001 { "mappings": { "dynamic_templates": [ { "strings_as_text": { "match_mapping_type": "string", "mapping": { "type": "text" } } } ] } }
Disabled norms
editNorms are index-time scoring factors. If you do not care about scoring, which would be the case for instance if you never sort documents by score, you could disable the storage of these scoring factors in the index and save some space.
PUT my-index-000001 { "mappings": { "dynamic_templates": [ { "strings_as_keywords": { "match_mapping_type": "string", "mapping": { "type": "text", "norms": false, "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } } } } ] } }
The sub keyword
field appears in this template to be consistent with the
default rules of dynamic mappings. Of course if you do not need them because
you don’t need to perform exact search or aggregate on this field, you could
remove it as described in the previous section.
Time-series
editWhen doing time series analysis with Elasticsearch, it is common to have many numeric fields that you will often aggregate on but never filter on. In such a case, you could disable indexing on those fields to save disk space and also maybe gain some indexing speed: