ES 基本使用

部署服务

使用 安装包 或者 容器 下载 启动 elasticserch

https://www.elastic.co/cn/start

docker 命令如下

docker run -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:7.10.1

默认会在 9200端口运行

GET localhost:9200

如果有相应代表运行成功

{
    "name": "1a22b65b032e",
    "cluster_name": "docker-cluster",
    "cluster_uuid": "T08GpTq8QWWkglHr04oiZA",
    "version": {
        "number": "7.10.1",
        "build_flavor": "default",
        "build_type": "docker",
        "build_hash": "1c34507e66d7db1211f66f3513706fdf548736aa",
        "build_date": "2020-12-05T01:00:33.671820Z",
        "build_snapshot": false,
        "lucene_version": "8.7.0",
        "minimum_wire_compatibility_version": "6.8.0",
        "minimum_index_compatibility_version": "6.0.0-beta1"
    },
    "tagline": "You Know, for Search"
}

索引

我们通过HTTP请求与ES服务进行交互

创建索引

PUT {{LOCAL_ES}}/user

创建了一个名为user的索引

查看索引列表

GET {{LOCAL_ES}}/_all

简单版本：

GET {{LOCAL_ES}}/_cat/indices?v

health status index uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open   user  AG5bAWgpRyWFTwegKhaE_w   1   1          0            0       208b           208b

查看索引

GET {{LOCAL_ES}}/user

删除索引

DELETE {{LOCAL_ES}}/user

索引状态变更

开启： POST{{LOCAL_ES}}/user/_open

关闭： POST{{LOCAL_ES}}/user/_close

Mapping

字段类型

https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-types.html

字符串：

• text: 需要被全文搜索的内容。设置text类型后，字段内容会被分析，升到倒排索引以前，字符串会被分析器拆分成一个个词项。text字段不用于排序，很少用于聚合
• keyword : 全字匹配，用于过滤和排序

日期类型:

• date

     "date": {
        "type":   "date",
        "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
      }

数值类型:

• long
• integer
• short
• byte
• double
• float
• half_float
• scaled_float
• unsigned_long

范围类型:

• integer_range

    "properties": {
      "expected_attendees": {
        "type": "integer_range"
      },
      "time_frame": {
        "type": "date_range", 
        "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
      }
    }

• float_range
• long_range
• double_range
• date_range
• ip_range

映射创建

ES 只能新增映射,不能修改或删除，只能数据重建。

新增映射

POST {{LOCAL_ES}}/ts300/_mapping

{
    "properties": {
        "contents": {
            "type": "text"
        },
        "type": {
            "type": "keyword"
        },
        "author": {
            "type": "keyword"
        },
        "title": {
            "type": "keyword"
        }
    }
}

原有映射修改

1. 创建一个新的权限索引，包含调整后的字段或类型 #job job2
2. 将原有索引(reindex)到新索引 #job reindex->#job2
3. 删除原有索引 #DELETE job
4. 将新索引别名设置为原有索引名 # job2 alias->job

文档

添加文档

POST {{LOCAL_ES}}/ts300/_create/1

请求体：

  {
    "id": 1,
    "contents": "孤鸿海上来，池潢不敢顾。\n侧见双翠鸟，巢在三珠树。\n矫矫珍木巅，得无金丸惧。\n美服患人指，高明逼神恶。\n今我游冥冥，弋者何所慕。",
    "type": "五言古诗",
    "author": "张九龄",
    "title": "感遇四首之一"
  }

返回值：

{
    "_index": "ts300",
    "_type": "_doc",
    "_id": "1",
    "_version": 1,
    "result": "created",
    "_shards": {
        "total": 2,
        "successful": 1,
        "failed": 0
    },
    "_seq_no": 0,
    "_primary_term": 1
}

更新文档（全部替换）

POST {{LOCAL_ES}}/ts300/_doc/1

如果id原来没有则创建

获取文档

GET{{LOCAL_ES}}/ts300/_doc/1

获取多个文档

POST {{LOCAL_ES}}/ts300/_mget

{
    "ids": [
        1
    ]
}

更新文档字段

不推荐使用

POST {{LOCAL_ES}}/ts300/_update/1

  {
   "script": "ctx._source.title=\"感遇四首之1一\""   
  }

删除字段

  {
   "script": "ctx._source.remove(\"title\")"
  }

删除文档

DELETE {{LOCAL_ES}}/ts300/_doc/1

ingest

文档预处理

创建

PUT {{LOCAL_ES}}/_ingest/pipeline/indexed_at

{
  "description": "Adds timestamp  to documents",
  "processors": [
    {
      "set": {
        "field": "_source.timestamp",
        "value": "{{_ingest.timestamp}}"
      }
    },
    {
      "script": {
        "source": "ctx.cont_length = ctx.contents.length();"
      }
    }
  ]
}

模板

PUT _template/my_template

{
  "index_patterns": [
    "some_index*"
  ],
  "aliases": {
    "some_index": {}
  },
  "settings": {
    "index.default_pipeline": "indexed_at",
    "number_of_replicas": 1,
    "refresh_interval": "30s"
  },
  "mappings": {
    "properties": {
      "cont_length":{
        "type":"long"
      },
      "author": {
        "type": "text",
        "fields": {
          "field": {
            "type": "keyword"
          }
        },
        "analyzer": "ik_max_word"
      },
      "contents": {
        "type": "text",
        "fields": {
          "field": {
            "type": "keyword"
          }
        },
        "analyzer": "ik_max_word",
        "fielddata": true
      },
      "timestamp": {
        "type": "date"
      },
      "title": {
        "type": "text",
        "fields": {
          "field": {
            "type": "keyword"
          }
        },
        "analyzer": "ik_max_word"
      },
      "type": {
        "type": "text",
        "fields": {
          "field": {
            "type": "keyword"
          }
        },
        "analyzer": "ik_max_word"
      }
    }
  }
}

IK 分词器安装

./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.10.1/elasticsearch-analysis-ik-7.10.1.zip

配置 kibnana 数据可视化 展示

点击visulizaiton

选择图标

点击 Split Slices

然后点击Run生成图表