https://github.com/xiaozhiliaoo/elasticsearch-plugins
Elasticsearch Custom Plugins
https://github.com/xiaozhiliaoo/elasticsearch-plugins
elasticsearch elasticsearch-plugins
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Elasticsearch Custom Plugins
- Host: GitHub
- URL: https://github.com/xiaozhiliaoo/elasticsearch-plugins
- Owner: xiaozhiliaoo
- Created: 2022-11-27T10:41:59.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-11-28T02:39:17.000Z (over 2 years ago)
- Last Synced: 2025-02-16T08:27:43.004Z (3 months ago)
- Topics: elasticsearch, elasticsearch-plugins
- Language: Java
- Homepage:
- Size: 66.4 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# ElasticSearch插件(ES版本7.15.1)
[单字分词Analyzer：onecharstandard](#单字分词analyzeronecharstandard)
# 单字分词Analyzer：onecharstandard
ES的数字类型的text默认的分词器是[StandardAnalyzer](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/analysis-standard-analyzer.html)，该分词器会将"123456789"（比如手机号）分词成"123456789"，所以如果查询"123"，"345"的时候，会找不到文档，但是ES的StandardAnalyzer 支持配置**max_token_length**，将该值改为1，可以实现单字分词的效果，如下[**分析文本**](#分析文本)有示例。可以应用于如根据手机号的一部分搜索文档的功能，但是每次配置比较繁琐，所以创建了onecharstandard的插件。下面演示正常配置过程：
## 创建索引
```
PUT yourindex
{
"mappings": {
"properties": {
"mobile": {
"type": "text",
"analyzer": "custom_onecharstandard",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
},
"settings": {
"analysis": {
"analyzer": {
"custom_onecharstandard": {
"type": "standard",
"max_token_length": 1
}
}
}
}
}
```
## 分析文本
```
//分词成1，2，3，4，5，6，7，8
POST _analyze
{
"tokenizer": {
"type": "standard",
"max_token_length": 1
},
"text": "12345678"
}
//分词成12345678整体
POST _analyze
{
"analyzer": "standard",
"text": "12345678"
}
```
## 写入文档
```
//doc1
POST yourindex/_doc
{
"mobile": "1"
}
//doc2
POST yourindex/_doc
{
"mobile": "2"
}
//doc3
POST yourindex/_doc
{
"mobile": "12"
}
//doc4
POST yourindex/_doc
{
"mobile": "21"
}
//doc5
POST yourindex/_doc
{
"mobile": "123"
}
```
## 搜索文档
- 可以使用手机号中的一部分（如一般常用为后四位）搜索文档。注意必须是match_phrase(slop默认是0)短语搜索，不能是match搜索。因为match搜索(operator默认是OR)会查出不在mobile里面的内容。
| term | docId |
| ---- | ------- |
| 1 | 1,2,3,5 |
| 2 | 2,3,4,5 |
| 3 | 5 |
```
//match查询会查询全部，doc1到doc5。因为operator默认是OR的关系。
GET yourindex/_search
{
"query": {
"match": {
"mobile": "12"
}
}
}
//match_phrase查出只包含12的文档。分词效果是1，2，必须同时包括1,2的文档，且保证顺序不变。此时只有一个,查出doc3
GET yourindex/_search
{
"query": {
"match_phrase": {
"mobile": "12"
}
}
}
//该效果和match_phrase类似，operator配置成and
GET yourindex/_search
{
"query": {
"match": {
"mobile": {
"operator": "and",
"query":"12"
}
}
}
}
//查不到，因为没有这个分词文档
GET yourindex/_search
{
"query": {
"term": {
"mobile": {
"value": "12"
}
}
}
}
//查不到，因为没有这个分词文档
GET yourindex/_search
{
"query": {
"term": {
"mobile": {
"value": "12"
}
}
}
}
//只查到12文档doc3
GET yourindex/_search
{
"query": {
"term": {
"mobile.keyword": {
"value": "12"
}
}
}
}
```
- 因为配置了多字段fields:keyword，也可以用term做精确值查询。
```
GET yourindex/_search
{
"query": {
"term": {
"mobile.keyword": "123"
}
}
}
```
但是这种方式需要在创建索引的时候在mapping和settings中配置analyzer，比较不方便，因此该插件提供了一个新的Analyzer：**onecharstandard**
```
//创建索引时可以直接配置，无需在settings里再构造自定义analyzer
PUT yourindex
{
"mappings": {
"properties": {
"mobile": {
"type": "text",
"analyzer": "onecharstandard",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
```
# 插件
[https://www.elastic.co/guide/en/elasticsearch/plugins/current/intro.html](https://www.elastic.co/guide/en/elasticsearch/plugins/current/intro.html)
## 运行插件
1. 执行 zip task。
2. 把elasticsearch-plugins-0.0.1.jar包移动到ESPlugin-es7.15.1-0.0.1.zip文件中。
3. 安装：elasticsearch-plugin.bat install file:///D:/ELK/ESPlugin-es7.15.1-0.0.1.zip
4. 重启
## 插件列表
elasticsearch-plugin.bat list
## 删除插件
elasticsearch-plugin.bat remove ESPlugin
# Standard Analyzer介绍
官方文档 [Analysis Standard Analyzer](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/analysis-standard-analyzer.html)
| Character Filter | Tokenizer | Token Filter |
| ---------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
| 无 | [Standard Tokenizer](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/analysis-standard-tokenizer.html) | [Lower Case Token Filter](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/analysis-lowercase-tokenfilter.html) |
| | | [Stop Token Filter](https://www.elastic.co/guide/en/elasticsearch/reference/8.5/analysis-stop-tokenfilter.html) |
Standard Analyzer由Standard Tokenizer和两个Token Filter组成。
Standard Tokenizer基于Unicode Text Segmentation算法，lowercase token filter是把大写转小写，stop token filter是移除停用词，类似的效果如下：
```
//会分为2 quick brown foxes jumped over lazy dog bone，其中大写转小写，并且the停用词被移除。
POST _analyze
{
"tokenizer": "standard",
"filter" : ["lowercase","stop"],
"text": "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
}
```
# 参考
1. ES
官方Plugin例子：[https://github.com/elastic/elasticsearch/tree/main/plugins/examples](https://github.com/elastic/elasticsearch/tree/main/plugins/examples)
2. ES
官方Plugin文档：[https://www.elastic.co/guide/en/elasticsearch/plugins/current/intro.html](https://www.elastic.co/guide/en/elasticsearch/plugins/current/intro.html)