keyword
字段的normalizer属性类似于分析器,只是它保证分析链生成单个token。
在索引关键字之前,以及在通过诸如match
查询之类的查询解析器或者通过诸如term
查询之类的术语级查询搜索keyword
字段时的搜索,应用规范化器——normalizer。
PUT index
{
"settings": {
"analysis": {
"normalizer": {
"my_normalizer": {
"type": "custom",
"char_filter": [],
"filter": ["lowercase", "asciifolding"]
}
}
}
},
"mappings": {
"_doc": {
"properties": {
"foo": {
"type": "keyword",
"normalizer": "my_normalizer"
}
}
}
}
}
PUT index/_doc/1
{
"foo": "BÀR"
}
PUT index/_doc/2
{
"foo": "bar"
}
PUT index/_doc/3
{
"foo": "baz"
}
POST index/_refresh
GET index/_search
{
"query": {
"term": {
"foo": "BAR"
}
}
}
GET index/_search
{
"query": {
"match": {
"foo": "BAR"
}
}
}
上述查询与文档1和2匹配,因为在索引和查询时都将BÀR转换为bar
。
{
"took": $body.took,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped" : 0,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0.2876821,
"hits": [
{
"_index": "index",
"_type": "_doc",
"_id": "2",
"_score": 0.2876821,
"_source": {
"foo": "bar"
}
},
{
"_index": "index",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"foo": "BÀR"
}
}
]
}
}
此外,关键字在索引之前被转换的事实也意味着聚合返回归一化值:
GET index/_search
{
"size": 0,
"aggs": {
"foo_terms": {
"terms": {
"field": "foo"
}
}
}
}
返回:
{
"took": 43,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped" : 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.0,
"hits": []
},
"aggregations": {
"foo_terms": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "bar",
"doc_count": 2
},
{
"key": "baz",
"doc_count": 1
}
]
}
}
}