# Custom Analyzer（自定义分析器）
当内置分析器不能满足您的需求时，您可以创建一个custom分析器，它使用以下相应的组合：
* 零个或多个[字符过滤器](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-custom-analyzer.html)
* 一个[分析器](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-tokenizers.html)
* 零个或多个[token过滤器](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-custom-analyzer.html)
### 配置
custom（自定义）分析器接受以下的参数：
| `tokenizer` | 内置或定制的标记器。 （需要） |
| ------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `char_filter` | 内置或自定义[字符过滤器](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-charfilters.html)的可选阵列。 |
| `filter` | 可选的内置或定制token过滤器阵列。 |
| `position_increment_gap` | 在索引文本值数组时，Elasticsearch会在一个值的最后一个值和下一个值的第一个项之间插入假的“间隙”，以确保短语查询与不同数组元素的两个术语不匹配。 默认为100.有关更多信息，请参阅[position\_increment\_gap](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/position-increment-gap.html)。 |
## 配置示例
以下是一个结合以下内容的示例：
字符过滤器
* [HTML Strip Character Filter](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-htmlstrip-charfilter.html)
分词器
* [Standard Tokenizer](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-standard-tokenizer.html)
Token 分析器
* [Lowercase Token Filter](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-lowercase-tokenfilter.html)
* [ASCII-Folding Token Filter](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-asciifolding-tokenfilter.html)
```
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_custom_analyzer": {
"type": "custom",
"tokenizer": "standard",
"char_filter": [
"html_strip"
],
"filter": [
"lowercase",
"asciifolding"
]
}
}
}
}
}
POST my_index/_analyze
{
"analyzer": "my_custom_analyzer",
"text": "Is this déjà vu?"
}
```
上述句子将产生以下词语：
```
[ is, this, deja, vu ]
```
前面的例子使用了默认配置的tokenizer，令牌过滤器和字符过滤器，但是可以创建每个配置的版本并在自定义分析器中使用它们。
以下是一个比较复杂的例子：
字符过滤器
* [Mapping Character Filter](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-mapping-charfilter.html), 分词器
* [Pattern Tokenizer](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-pattern-tokenizer.html), 配置为分割标点符号
Token 分析器
* [Lowercase Token Filter](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-lowercase-tokenfilter.html)(小写分析器)
* [Stop Token Filter](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-stop-tokenfilter.html)(停止分析器), 配置为使用预定义的英文停止词列表
### 示例
```
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_custom_analyzer": {
"type": "custom",
"char_filter": [
"emoticons" # 1
],
"tokenizer": "punctuation", # 2
"filter": [
"lowercase",
"english_stop"
]
}
},
"tokenizer": {
"punctuation": {
"type": "pattern",
"pattern": "[ .,!?]"
}
},
"char_filter": {
"emoticons": {
"type": "mapping",
"mappings": [
":) => _happy_",
":( => _sad_"
]
}
},
"filter": {
"english_stop": {
"type": "stop",
"stopwords": "_english_"
}
}
}
}
}
POST my_index/_analyze
{
"analyzer": "my_custom_analyzer",
"text": "I'm a :) person, and you?"
}
```
| [](https://www.elastic.co/guide/en/elasticsearch/reference/5.3/analysis-custom-analyzer.html#CO283-1) | 表情符号字符过滤器，标点符号化器和english\_stop令牌过滤器是在相同索引设置中定义的自定义实现。 |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- |
以上示例产生以下词语：
```
[ i'm, _happy_, person, you ]
```