[ELK] Elastic Search (3)

Metric Aggregation

산술 aggregation

{
    "size" : 0,
    "aggs" : {
        "stats_score" : {
                "stats" : {
                    "field" : "points"
            }
        }
    }
}

curl -XGET -H'Content-Type: application/json' localhost:9200/_search?pretty --data-binary @avg_points_aggs.json

• AVG(평균)

• MAX (최대값)

• status : count/ min / max / avg / sum => aggregation이 다 나올 수 있는 코드

---

Bucket aggregation

SQL Group by와 같음

{
    "size" : 0,
    "aggs" : {
        "team_stats" : {
            "terms" : {
                "field" : "team"
            },
            "aggs" : {
                "stats_score" : {
                    "stats" : {
                        "field" : "points"
                    }
                }
            }
        }
    }
}

• 일단 index 생성 후 mapping

curl -XPUT 'http://localhost:9200/basket/record/_mapping?include_type_name=true' -H "Content-Type: application/json" -d @basketball_mapping.json

• document @file로 post하기

curl -XPOST 'localhost:9200/\_bulk' -H 'Content-Type: application/json' --data-binary @twoteam\_basketball.json

• bucket aggregation search

curl -XGET -H "Content-Type: application/json" localhost:9200/basket/\_search?pretty --data-binary 
@terms\_aggs.json

team별로 document를 묶은 다음 결과값에서 또 aggregation을 진행함

 

index 조회

curl -XGET 'localhost:9200/\_cat/indices?v'

index 삭제

curl --location --request DELETE 'localhost:9200/basketbal'

• 참고링크
  https://victorydntmd.tistory.com/308

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