normalizer
keyword 字段的 normalizer 属性类似于 analyzer，只是它保证分析链产生单个词元。
normalizer 在索引关键字之前应用，以及在通过查询解析器（例如 match 查询）或词条级查询（例如 term 查询）搜索关键字字段时的搜索阶段应用。
Elasticsearch 自带一个名为 lowercase 的简单 normalizer，可以直接使用。自定义 normalizer 可以作为分析设置的一部分定义，如下所示：
PUT index
{
"settings": {
"analysis": {
"normalizer": {
"my_normalizer": {
"type": "custom",
"char_filter": [],
"filter": ["lowercase", "asciifolding"]
}
}
}
},
"mappings": {
"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"
}
}
}
上面的查询匹配文档 1 和 2，因为 BÀR 在索引和查询时都被转换为 bar。
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped" : 0,
"failed": 0
},
"hits": {
"total" : {
"value": 2,
"relation": "eq"
},
"max_score": 0.4700036,
"hits": [
{
"_index": "index",
"_id": "1",
"_score": 0.4700036,
"_source": {
"foo": "BÀR"
}
},
{
"_index": "index",
"_id": "2",
"_score": 0.4700036,
"_source": {
"foo": "bar"
}
}
]
}
}
此外，关键字在索引之前被转换这一事实也意味着聚合返回的是归一化后的值：
GET index/_search
{
"size": 0,
"aggs": {
"foo_terms": {
"terms": {
"field": "foo"
}
}
}
}
返回：
{
"took": 43,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped" : 0,
"failed": 0
},
"hits": {
"total" : {
"value": 3,
"relation": "eq"
},
"max_score": null,
"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
}
]
}
}
}