OpenSearch/docs/reference/analysis/testing.asciidoc

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[[test-analyzer]]
=== Test an analyzer
The <<indices-analyze,`analyze` API>> is an invaluable tool for viewing the
terms produced by an analyzer. A built-in analyzer can be specified inline in
the request:
[source,console]
-------------------------------------
POST _analyze
{
"analyzer": "whitespace",
"text": "The quick brown fox."
}
-------------------------------------
The API returns the following response:
[source,console-result]
-------------------------------------
{
"tokens": [
{
"token": "The",
"start_offset": 0,
"end_offset": 3,
"type": "word",
"position": 0
},
{
"token": "quick",
"start_offset": 4,
"end_offset": 9,
"type": "word",
"position": 1
},
{
"token": "brown",
"start_offset": 10,
"end_offset": 15,
"type": "word",
"position": 2
},
{
"token": "fox.",
"start_offset": 16,
"end_offset": 20,
"type": "word",
"position": 3
}
]
}
-------------------------------------
You can also test combinations of:
* A tokenizer
* Zero or token filters
* Zero or more character filters
[source,console]
-------------------------------------
POST _analyze
{
"tokenizer": "standard",
"filter": [ "lowercase", "asciifolding" ],
"text": "Is this déja vu?"
}
-------------------------------------
The API returns the following response:
[source,console-result]
-------------------------------------
{
"tokens": [
{
"token": "is",
"start_offset": 0,
"end_offset": 2,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "this",
"start_offset": 3,
"end_offset": 7,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "deja",
"start_offset": 8,
"end_offset": 12,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "vu",
"start_offset": 13,
"end_offset": 15,
"type": "<ALPHANUM>",
"position": 3
}
]
}
-------------------------------------
.Positions and character offsets
*********************************************************
As can be seen from the output of the `analyze` API, analyzers not only
convert words into terms, they also record the order or relative _positions_
of each term (used for phrase queries or word proximity queries), and the
start and end _character offsets_ of each term in the original text (used for
highlighting search snippets).
*********************************************************
Alternatively, a <<analysis-custom-analyzer,`custom` analyzer>> can be
referred to when running the `analyze` API on a specific index:
[source,console]
-------------------------------------
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"std_folded": { <1>
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"asciifolding"
]
}
}
}
},
"mappings": {
"properties": {
"my_text": {
"type": "text",
"analyzer": "std_folded" <2>
}
}
}
}
GET my_index/_analyze <3>
{
"analyzer": "std_folded", <4>
"text": "Is this déjà vu?"
}
GET my_index/_analyze <3>
{
"field": "my_text", <5>
"text": "Is this déjà vu?"
}
-------------------------------------
The API returns the following response:
[source,console-result]
-------------------------------------
{
"tokens": [
{
"token": "is",
"start_offset": 0,
"end_offset": 2,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "this",
"start_offset": 3,
"end_offset": 7,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "deja",
"start_offset": 8,
"end_offset": 12,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "vu",
"start_offset": 13,
"end_offset": 15,
"type": "<ALPHANUM>",
"position": 3
}
]
}
-------------------------------------
<1> Define a `custom` analyzer called `std_folded`.
<2> The field `my_text` uses the `std_folded` analyzer.
<3> To refer to this analyzer, the `analyze` API must specify the index name.
<4> Refer to the analyzer by name.
<5> Refer to the analyzer used by field `my_text`.