Kibana operation es

es On

es website

kibana operation es

Elaticsearch, Referred to as es, Yes es The operation is based on REST Style operation ;
The basic operations are :PUT（ establish , modify ） POST（ establish , modify ） DELETE（ Delete ） GET（ Inquire about ） POST（ Inquire about ） ; We usually do the most additions, deletions, modifications and checks ; Query is the most important and complex .
What I posted can be copied directly to kibana Inside , Then you can create more data by yourself , You can make your own according to the query .

Simple operation

#  obtain ElasticSearch A lot of current information ！
GET _cat/
GET /_cat/plugins

##  participle 
GET _analyze
{
    
  "analyzer": "ik_smart",
  "text": " Young people don't speak martial arts "
}

GET _analyze
{
    
  "analyzer": "ik_max_word",
  "text": " Young people don't speak martial arts "
}

#  Create index , Cannot modify after creation 
PUT /test1
{
    
  
  "mappings": {
    
    "properties": {
    
      "name":{
    
        "type": "text"
      },
      "age":{
    
        "type": "long"
      },
      "birthday":{
    
        "type": "date"
      },
       "tag":{
    
        "type": "text"
      }
    }
  }

}
#  Get index information 
GET test1
##  Delete index 
DELETE test1

#  The new document    Appoint id, Follow random id
PUT /test1/_doc/1 
{
    
  "name":" Zhang Yida ",
  "age":11,
  "birthday": "1990-08-09"
}

POST /test1/_doc/
{
    
  "name":" Zhang Yida ",
  "age":11,
  "birthday": "1990-08-09"
}

#  Modify the document 
# put Cover ,_version Meeting +1  If not, it will be empty ( Don't suggest , Fields will be lost , Unless you really want to cover it all )
PUT /test1/_doc/1
{
    
  "name" : " Zhang Yida ",
  "age" : 183
}
GET /test1/_doc/1
# post _update  Suggest ,_version unchanged ( Suggest , Be careful doc Field )
POST /test1/_update/1/
{
    
  "doc": {
    
  "name" : " Zhang Yida 2"
  }
}
GET /test1/_doc/1

Query operation

Query basic operations

##  Inquire about 
##  Deprecation: [types removal] Specifying types in search requests is deprecated. Will let you delete type,_doc
GET /test1/_doc/_search?q=name: benefit 
GET /test1/_search?q=name: benefit 
GET /test1/_search?q=age:11

## Query match 
##match： matching （ Can use word segmentation to parse （ First analyze the document , And then query ））
## term:  Specify terms directly through inverted index , Accurate query , No participle , Suitable field types are number,date,keyword, Not suitable for text
##_source： Filter fields 
##sort： Sort 
##form、size  Pagination 
GET /test1/_search
{
    
  "query": {
    
    "match": {
    
      "name": " Zhang "
    }
  }
   ,
  "_source": ["name","age"],
  "sort": [
    {
    
      "age": {
    
        "order": "asc"
      }
    }
  ],
  "from": 1
  ,
  "size": 1
}

#  Multiconditional query 
#must  amount to  and
#should  amount to  or
#must_not  amount to  not (... and ...)
#filter  Filter 
GET /test1/_search
{
    
  "query": {
    
    "bool": {
    
      "must": [
        {
    
          "match": {
    
            "name": "1"
          }
        },
        {
    
           "match": {
    
            "age": "1"
          }
        }
      ],
      "filter": [
        {
    
          "range": {
    
            "age": {
    
              "gte": 1,
              "lte": 2
            }
          }
        }
      ]
    }
  }
}

#  Create an index with an array , If the index does not exist, it will be created automatically 

POST /test_arr/_doc
{
    
  "name" : " Zhang Yida 2",
  "age" : 18,
  "birthday":"1990-09-08",
  "tag":[" The lawyer "," Funny "," self-confidence "]
}

POST /test_arr/_doc
{
    
  "name" : " Zhang Yida 3",
  "age" : 18,
  "birthday":"1990-09-08",
  "tag":[" The lawyer " ," male "]
}
GET /test_arr/_doc/1

GET /test_arr/_search
{
    
  "query": {
    
    "match": {
    
      "tag": " male   t "
    }
  }
}
#  match  Can use word segmentation to parse （ First analyze the document , And then query ）
GET /test_arr/_search
{
    
  "query": {
    
    "bool": {
    
      "must": [
        {
    
          "match": {
    
            "name": " Zhang "
          }
        },
        {
    
           "match": {
    
            "tag": " Male lawyers are funny, female confident people "
          }
        }
      ]
    }
  }
}

# term Accurate query 
GET /test1/_search
{
    
  "query": {
    
    "term": {
    
      "age": 1
    }
  }
}

text and keyword

• text：
  Support participle , Full text search 、 Support ambiguity 、 Precise query , Aggregation is not supported , The sorting operation ;
  text The maximum supported character length of type is unlimited , Suitable for large field storage ;
• keyword：
  No participle , Direct index 、 Support ambiguity 、 Support exact match , Support aggregation 、 The sorting operation .
  keyword The maximum supported length of a type is ——32766 individual UTF-8 Type of characters , Can be set by ignore_above Specify self-contained character length , Data beyond a given length will not be indexed , Unable to get term Exact matching search results return .

##  test keyword and text Whether word segmentation is supported 
PUT /test
{
    
  "mappings": {
    
    "properties": {
    
      "text":{
    
        "type":"text"
      },
      "keyword":{
    
        "type":"keyword"
      }
    }
  }
}

PUT /test/_doc/1
{
    
  "text":" test keyword and text Whether word segmentation is supported ",
  "keyword":" test keyword and text Whether word segmentation is supported "
}

# text  Support participle 
# keyword  Participle... Is not supported 

#  Find out 
GET /test/_doc/_search
{
    
  "query":{
    
   "match":{
    
      "text":" test "
   }
  }
}
##  We can't find it 
GET /test/_doc/_search
{
    
  "query":{
    
   "match":{
    
      "keyword":" test "
   }
  }
}

#  Word segmentation analysis 
GET _analyze
{
    
  "analyzer": "keyword",
  "text": [" test liu"]
}

GET _analyze
{
    
  "analyzer": "standard",
  "text": [" test liu"]
}

GET _analyze
{
    
  "analyzer":"ik_max_word",
  "text": [" test liu"]
}

Highlight query

##  Highlight query , The main thing is to add prefix and suffix to the content of the query 
GET test1/_doc/_search
{
    
  "query": {
    
    "match": {
    
      "name":" Zhang "
    }
  }
  ,
  "highlight": {
    
    "pre_tags": "<p class='key' style='color:red'>",
    "post_tags": "</p>", 
    "fields": {
    
      "name": {
    }
    }
  }
}

thus kibana operation es Some common operations of , See the official documents for more details :

https://www.elastic.co/guide/cn/elasticsearch/guide/current/full-body-search.html

The next section uses java Code operation es