Elasticsearch---索引管理、基于scroll+bu

2017-04-09  本文已影响0人  缓慢移动的蜗牛

创建索引的语法

PUT /my_index
{
    "settings": { ... any settings ... },
    "mappings": {
        "type_one": { ... any mappings ... },
        "type_two": { ... any mappings ... },
        ...
    }
}

示例：

PUT /my_index
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0
  },
  "mappings": {
    "my_type":{
      "properties": {
        "my_field":{
          "type": "text"
        }
      }
    }
  }
}

添加索引（索引一旦建立，不能修改）

PUT /my_index/_settings
{
  "number_of_replicas": 1
}
PUT /my_index/_mapping/my_type
{
  "properties": {
    "my_field":{
      "type": "string"
    }
  }
}

删除索引

DELETE /my_index
DELETE /index_one,index_two
DELETE /index_*
DELETE /_all    //要想这样删除，需要修改config/elasticsearch.yml 中action.destructive_requires_name: false

分词器的修改与定制

默认分词器是standard

  • standard tokenizer：已单词边界进行切分
  • standard token filter：什么都不做
  • lowercase token filter：将所有字符转换为小写
  • stop token filter（默认禁用）：移除停用词
PUT /my_index
{
 "settings": {
   "analysis": {
     "analyzer": {
       "my_analyzer_std":{
         "type":"standard",
         "stopwords":"_english_"
       }
     }
   }
 }
}
//测试
GET /my_index/_analyze
{
 "analyzer": "my_analyzer_std",
 "text": "hello,you are the good boy"    // are the会被去掉
}

PUT /my_index
{
  "settings": {
    "analysis": {
      "char_filter":{
        "&_to_and":{
          "type":"mapping",
          "mappings":["&=> and"]
        }
      },
      "filter": {
        "my_stopwords":{
          "type":"stop",
          "stopwords":["the","are"]
        }
      },
      "analyzer": {
        "my_analyzer":{
          "type":"custom",
          "char_filter":["html_strip","&_to_and"],
          "tokenizer":"standard",
          "filter":["lowercase","my_stopwords"]
        }
      }
    }
  }
}
//测试
GET /my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text":"tom & jery,they are the good friend,<a>CLICK ME</a>"
}

type底层的数据结构

type，是一个index中用来区分类似的数据的，类似的数据
,但是可能有不同的fields，而且有不同的属性来控制索引建立、分词器
field的value，在底层的lucene中建立索引的时候，全部是opaque bytes（二进制）类型，不区分类型的。
lucene是没有type的概念的，在document中，实际上将type作为一个document的field来存储，即_type，es通过_type来进行type的过滤和筛选
一个index中的多个type，实际上是放在一起存储的，因此一个index下，不能有多个type重名，而类型或者其他设置不同的，因为那样是无法处理的

//设置_mapping
PUT /ecommerce
{
 "mappings": {
   "elactronic_goods":{
     "properties": {
       "name":{
         "type": "string"
       },
       "price":{
         "type":"double"
       },
       "service_period":{
         "type":"string"
       }
     }
   },
   "fresh_goods":{
     "properties": {
       "name":{
         "type": "string"
       },
       "price":{
         "type": "double"
       },
       "eat_period":{
         "type":"string"
       }
     }
   }
 }
}
//查询_mapping
GET /ecommerce/_mapping
//存入document
PUT /ecommerce/elactronic_goods/1
{
 "name":"geli kongtiao",
 "price":3999,
 "service_period":"one year"
}
PUT /ecommerce/fresh_goods/1
{
 "name":"da xia",
 "price":99,
 "eat_period":"one week"
}

底层数据结构是这样的

{
   "ecommerce": {
      "mappings": {
        "_type": {
          "type": "string",
          "index": "not_analyzed"
        },
        "name": {
          "type": "string"
        }
        "price": {
          "type": "double"
        }
        "service_period": {
          "type": "string"
        }
        "eat_period": {
          "type": "string"
        }
      }
   }
}
//放入的document是这样的
{
  "_type": "elactronic_goods",
  "name": "geli kongtiao",
  "price": 1999.0,
  "service_period": "one year",
  "eat_period": ""
}
{
  "_type": "fresh_goods",
  "name": "aozhou dalongxia",
  "price": 199.0,
  "service_period": "",
  "eat_period": "one week"
}

所以应该把类似结构的type放在一个index下，这些type应该有多个field是相同的，如果一个index的多个type的field完全不同，那个每条数据会有一大部分的field在底层lucene中是空值，会有严重的性能问题

_mapping root object深入剖析

PUT /my_index
{
  "mappings": {
    "my_type":{
      "properties": {}
    }
  }
}

PUT /my_index/_mapping/my_type
{
  "properties": {
    "title":{
      "type": "text"
    }
  }
}
  • 查询的时候，直接可以拿到完整的document，不需要先拿document id，再发送一次请求拿document
  • partial update基于_source实现
  • reindex时，直接基于_source实现，不需要从数据库（或者其他外部存储）查询数据再修改
  • 可以基于_source定制返回field
  • debug query更容易，因为可以直接看到_source

如果不需要上述好处，可以禁用_source

PUT /my_index/_mapping/my_type2
{
  "_source": {"enabled": false}
}

PUT /my_index/_mapping/my_type3
{
  "_all": {"enabled": false}
}

也可以在field级别设置include_in_all field，设置是否要将field的值包含在_all field中

PUT /my_index/_mapping/my_type4
{
  "properties": {
    "my_field": {
      "type": "text",
      "include_in_all": false
    }
  }
}

dynamic mapping策略

  • true：遇到陌生字段，就进行dynamic mapping
  • false：遇到陌生字段，就忽略
  • strict：遇到陌生字段，就报错
PUT /my_index
{
 "mappings": {
   "my_type":{
     "dynamic":"strict",
     "properties": {
       "title":{
         "type": "text"
       },
       "address":{
         "type": "object",
         "dynamic":"true"
       }
     }
   }
 }
}

PUT /my_index/my_type/1
{
 "content":"uuuu",
 "title":"hello world",
 "address":{
   "country":"china",
   "provice":"beiing"
 }
}
//结果
{
 "error": {
   "root_cause": [
     {
       "type": "strict_dynamic_mapping_exception",
       "reason": "mapping set to strict, dynamic introduction of [content] within [my_type] is not allowed"
     }
   ],
   "type": "strict_dynamic_mapping_exception",
   "reason": "mapping set to strict, dynamic introduction of [content] within [my_type] is not allowed"
 },
 "status": 400
}

PUT /my_index/_mapping/my_type
{
  "date_detection": false
}

PUT /my_index
{
  "mappings": {
    "my_type":{
      "dynamic_templates":[
        {
          "en":{
            "match":"*_en",
            "match_mapping_type":"string",
            "mapping":{
              "type":"string",
              "analyzer":"english"
            }
          }
        }
      ]
    }
  }
}
//插入数据
PUT /my_index/my_type/1
{
  "title":"this is my first article"
}
PUT /my_index/my_type/2
{
  "title_en":"this is my first article"
}
//查询
//-------------------------------第一个
//没有匹配到任何的dynamic模板
//默认就是standard分词器，不会过滤停用词，is会进入倒排索引，用is来搜索是可以搜索到的
GET /my_index/my_type/_search
{
  "query": {
    "match": {
      "title": "is"
    }
  }
}
//-------------------------------第二个
//匹配到了dynamic模板，就是english分词器，会过滤停用词，is这种停用词就会被过滤掉，用is来搜索就搜索不到了
GET /my_index/my_type/_search
{
  "query": {
    "match": {
      "title_en": "is"
    }
  }
}

PUT /my_index
{
  "mappings": {
    "_default_":{
      "_all":{
        "enabled":false
      }
    },
   "blog":{
      "_all":{
        "enabled":true
      }
    }
  }
}

基于scroll+bulk的索引重建

一个field的设置是不能被修改的，如果要修改一个field，那么应该重新按照新的mapping，建立一个index，然后将数据批量查询出来，重新用bulk api写入index中
批量查询的时候，建议才用scroll api，并且才用多线程并发的方式来reindex数据，每次scroll就查询指定日期的一段数据，交个一个线程即可

PUT /my_index/my_type/1
{
  "title":"2017-01-01"
}
PUT /my_index/my_type/2
{
  "title":"2017-01-02"
}
PUT /my_index/my_type/3
{
  "title":"2017-01-03"
}

PUT /my_index/my_type/4
{
  "title":"my first article"
}
{
  "error": {
    "root_cause": [
      {
        "type": "mapper_parsing_exception",
        "reason": "failed to parse [title]"
      }
    ],
    "type": "mapper_parsing_exception",
    "reason": "failed to parse [title]",
    "caused_by": {
      "type": "illegal_argument_exception",
      "reason": "Invalid format: \"my first article\""
    }
  },
  "status": 400
}
//查看其mapping
GET /my_index/_mapping/my_type
{
  "my_index": {
    "mappings": {
      "my_type": {
        "properties": {
          "title": {
            "type": "date"
          }
        }
      }
    }
  }
}

PUT /my_index/_mapping/my_type
{
  "properties": {
    "title":{
      "type": "string"
    }
  }
}
//返回结果
{
  "error": {
    "root_cause": [
      {
        "type": "illegal_argument_exception",
        "reason": "mapper [title] of different type, current_type [date], merged_type [text]"
      }
    ],
    "type": "illegal_argument_exception",
    "reason": "mapper [title] of different type, current_type [date], merged_type [text]"
  },
  "status": 400
}

PUT /my_index/_alias/goods_index

PUT /my_index_new
{
  "mappings": {
    "my_type":{
      "properties": {
        "title":{
          "type": "string"
        }
      }
    }
  }
}

GET /my_index/_search?scroll=1m
{
  "query": {
    "match_all": {}
  },
  "sort":["_doc"],
  "size":1
}

POST /_bulk
{"index":{"_index":"my_index_new","_type":"my_type","_id":"2"}}
{"title":"2017-01-02"}

GET /_search/scroll
{
  "scroll":"1m",
  "scroll_id":"DnF1ZXJ5VGhlbkZldGNoBQAAAAAAAC6bFlhIb1FOME82U3llb202bER1Zm95VkEAAAAAAAAumBZYSG9RTjBPNlN5ZW9tNmxEdWZveVZBAAAAAAAALpwWWEhvUU4wTzZTeWVvbTZsRHVmb3lWQQAAAAAAAC6ZFlhIb1FOME82U3llb202bER1Zm95VkEAAAAAAAAumhZYSG9RTjBPNlN5ZW9tNmxEdWZveVZB"
}
POST /_bulk
{"index":{"_index":"my_index_new","_type":"my_type","_id":"...."}}
{"title":"..."}

POST /_aliases
{
  "actions": [
    {
      "remove": {"index":"my_index","alias": "goods_index"}
    },
    {
      "add":{"index":"my_index_new","alias": "goods_index"}
    }
  ]
}
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