Elasticsearch5.5.1 study notes

Add ik participle under linux

1. Download the tokenizer installation package

wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v5.5.1/elasticsearch-analysis-ik-5.5.1.zip

2. Unzip and install

1. Move elasticsearch-analysis-ik-5.5.1.zip to the plugins directory of the installation directory

mv elasticsearch-analysis-ik-5.5.1.zip /root/elasticsearch/elasticsearch-5.5.1/plugins/

2. Enter the plugins directory of the installation directory

cd /root/elasticsearch/elasticsearch-5.5.1/plugins/

3. Unzip

unzip elasticsearch-analysis-ik-5.5.1.zip 

4. Delete the compressed package

rm -rf elasticsearch-analysis-ik-5.5.1.zip

According to the official instructions, it has been successfully installed at this time, just restart ElasticSearch.

3. Test

Using the postman tool

Expand your own participle:

my.dic

Xiaomi phone
Huawei cell phone

 

Other query statements:

cluster health

curl -X GET 'http://localhost:9200/_cluster/health?pretty=true'

Elasticsearch has a feature called aggregations that allow you to generate complex analytics statistics on your data. It is much like GROUP BY in SQL but more powerful.

Format of megacorp/employee:

 {
    "first_name" : "John",
    "last_name" : "Smith",
    "age" : 25,
    "about" : "I love to go rock climbing",
    "interests" : [
      "sports",
      "music"
    ]
  }

 

Find out what all the staff have in common (hobbies):

 

{
    "aggs": {
        "all_interests": {
            "terms": {
                "field": "interests.keyword"
            }
        }
    }
}

 

Statistics on the average age of staff under each interest:

 

curl -X GET 'http://localhost:9200/megacorp/employee/_search?pretty=true' -d '
{
    "aggs" : {
        "all_interests" : {
            "terms" : { "field" : "interests.keyword" },
            "aggs" : {
                "avg_age" : {
                    "avg" : { "field" : "age" }
                }
            }
        }
    }
}’

 

Combine multiple clauses

{
    "query": {
        "bool": {
            "must": {
                "match": {
                    "first_name": "doublas"
                }
            },
            "must_not": {
                "match": {
                    "last_name": "roger"
                }
            }
        }
    }
}

Add filter conditions to the query statement:

 

{
    "query": {
        "bool": {
            "filter": {
                "term": {
                    "first_name": "john"
                }
            },
            "must": {
                "match": {
                    "last_name": "smith"
                }
            }
        }
    }
}

 

The query is highlighted:

{
    "query":{
        "match":{
            "about":"rock climbing"
        }
    },
    "highlight":{
        "pre_tags":["<font color='red'>"],
        "post_tags":["</font>"],
        "fields":{
            "about":{}
        }
    }
}