elastic search记录

安装与启动

插件安装
中文分词器 https://github.com/medcl/elasticsearch-analysis-ik

elastic api

GET _search
{
  "query": {
    "match_all": {}
  }
}

GET /_cat/indices


## 查询所有索引中的字段映射
GET _mapping

## 查询index中的type, 所有文档
GET logstash-2019.11.10-000001/_search


## 根据id查询单个详情,  上面结果中返回的type=_doc
GET logstash-2019.11.10-000001/_doc/VL1cU24BpEn5ymJfSBRH?pretty


## 根据message字段全匹配查询, 提供type (已过期)
GET logstash-2019.11.10-000001/_doc/_search?q=message:ffffff

## 根据message字段模糊查询, 提供type (已过期)
GET logstash-2019.11.10-000001/_doc/_search?q=message:*f

## 根据message字段全匹配查询, 不提供type
POST logstash-2019.11.10-000001/_search 
{"query":{"match":{"message":"ffffff"}}}

## 根据message字段模糊查询, 使用的是wildcard
POST logstash-2019.11.10-000001/_search 
{"query":{"wildcard":{"message":"ff*"}}}


## 排序

GET logstash-2019.11.10-000001/_search
{
    "query" : {
        "bool" : {
            "must":   { "match": { "tweet": "manage text search" }},
            "filter" : { "term" : { "user_id" : 2 }}
        }
    },
    "sort": [
        { "date":   { "order": "desc" }},
        { "_score": { "order": "desc" }}
    ]
}

_score是ES默认的匹配度计算


## 查询之后计算权重， 在查询表达式中定义函数function_score
# https://www.elastic.co/guide/cn/elasticsearch/guide/current/function-score-query.html
## todo

使用kibana查询

bin/kibana
http://localhost:5601
页面和阿里云的日志中心非常相似

search KQL语法：

https://www.elastic.co/guide/en/kibana/current/kuery-query.html#_range_queries
https://catalog.us-east-1.prod.workshops.aws/workshops/60a6ee4e-e32d-42f5-bd9b-4a2f7c135a72/en-US/03-log-analysis-basics/03-02-log-analysis/03-02-2-search-method

message: "xx xxxx" and message: "xxxxxxxx"    value有空格的时候加上双引号
message.http.code: >500 and message: error

中文页面配置

kibana-7.4.2-linux-x86_64\config\kibana.yml最后一行

# Specifies locale to be used for all localizable strings, dates and number formats.
# Supported languages are the following: English - en , by default , Chinese - zh-CN .
i18n.locale: "zh-CN"

关于是否进行分词分析

【场景：】 id是多个数字用中划线组成的，如果默认设置type=text/string, 这时不能进行精确匹配的搜索，也不能搜索负号

这里oracle的contains()全文索引的时候 (为了解决like，instr的性能问题)，也是同样的问题，查询负号的时候总是不正确，要么性能太低（查询中间的一段数字）

ES的解决方法时设置字段类型为‘keyword’, 而不是text或string, 这样就不会自动分词了 https://www.elastic.co/guide/cn/elasticsearch/guide/current/mapping-intro.html#custom-field-mappings


DELETE /my-index-000001

## 创建index
PUT /my-index-000001

## 设置mapping
PUT /my-index-000001/_mapping
{
  "properties": {
    "id":  {
      "type": "keyword"
    }
  }
}


PUT /my-index-000001/_mapping
{
  "properties" : {
    "tag" : {
      "type" :    "text",
      "index":    "false"
    }
  }
}


GET /my-index-000001

## 插入document 
POST /my-index-000001/_doc/
{
  "id": "-999-123123",
  "message": "GET /search HTTP/1.1 200 1070000",
  "@timestamp": "2099-11-15T13:12:00"
}


POST /my-index-000001/_doc/
{
  "id": "999-123123",
  "message": "INFO /abccccc HTTP/1.1 200 1070000",
  "@timestamp": "2099-11-15T13:12:00"
}

POST /my-index-000001/_doc/
{
  "id": "10300222-123123992",
  "message": "POST FTP 400",
  "@timestamp": "2099-11-15T13:12:00"
}


GET /my-index-000001/_search/

GET /my-index-000001/_search/
{
  "query": {
    "match": {
      "id": "-999"
    }
  }
}

GET /my-index-000001/_search/
{
  "query": {
    "match": {
      "id": "123123"
    }
  }
}

## 精确匹配， 要求字段mapping的时候就是"type": "keyword"  (ES2的文档是说'not_analyzed')，不是"type": "text"
## https://www.elastic.co/guide/cn/elasticsearch/guide/current/mapping-intro.html#custom-field-mappings
GET /my-index-000001/_search/
{
  "query": {
    "term": {
      "id": "-999-123123"
    }
  }
}


## 只返回 -999的数据
GET /my-index-000001/_search
{
  "query": {
    "wildcard": {
      "id": "*-999*"
    }
  }
}

## 返回999和-999的数据
GET /my-index-000001/_search
{
  "query": {
    "wildcard": {
      "id": "*999*"
    }
  }
}


## NOT WORK!!!
GET /my-index-000001/_search
{
  "query": {
    "fuzzy": {
      "id": "*-999*"
    }
  }
}

运维

集群中节点数设置成奇数，防止脑裂

开启数据压缩

spring data elasticsearch

https://spring.io/projects/spring-data-elasticsearch#learn

https://docs.spring.io/spring-data/elasticsearch/docs/3.2.1.RELEASE/reference/html/#elasticsearch.query-methods.criterions

根据BookRepository 方法名直接生成es查询api

<dependency>
			<groupId>org.springframework.boot</groupId>
			<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
		</dependency>

		<dependency>
			<groupId>org.springframework</groupId>
			<artifactId>spring-web</artifactId>
		</dependency>

spring-web默认没加上，启动报错
jpa接口比较重，spring cloud中可能有很多冲突问题，使用原生的接口开发也许更快，