[es] scripted similarity

 

 

from elasticsearch import Elasticsearch
import pprint as ppr
import json

index_name = "script-similarity-index"

query = {
    "query_string": {
        "query": "foo^1.7",
        "default_field": "field"
    }
}


class EsAPI:
    es = Elasticsearch(hosts="localhost", port=9200, http_auth=('elastic', 'elastic1!'))  # 객체 생성

    @classmethod
    def srvHealthCheck(cls):
        health = cls.es.cluster.health()
        print (health)

    @classmethod
    def allIndex(cls):  # Elasticsearch에 있는 모든 Index 조회
        print (cls.es.cat.indices())

    @classmethod
    def dataInsert(cls):
        # ===============
        # 데이터 삽입
        # ===============
        with open("/Users/doo/doo_py/homeplus/data/similarity/products.json", "r", encoding="utf-8") as fjson:
            data = json.loads(fjson.read())

            for n, i in enumerate(data):
                doc = {
                    "name": i['name']
                }
                res_n = cls.es.index(index=index_name, doc_type="_doc", id=n + 1, body=doc)
                print (res_n)
                
        cls.es.indices.refresh(index = index_name)


    @classmethod
    def searchAll(cls, indx=None):  # ===============        # 데이터 조회 [전체]        # ===============
        res_n = cls.es.search(
            index=index_name,
            doc_type="_doc",
            body={"query": {"match_all": {}}})
        print (json.dumps(res_n, ensure_ascii=False, indent=4))

    @classmethod
    def searchFilter(cls):
        # ===============        # 데이터 조회 []        # ===============
        res_n = cls.es.search(
            index=index_name,
            doc_type="_doc",
            body=query
        )
        ppr.pprint(res_n)

    @classmethod
    def createIndex(cls):
        # ===============        # 인덱스 생성        # ===============
        cls.es.indices.create(
            index=index_name,
            body={
                "settings": {
                    "number_of_replicas": 0,
                    "number_of_shards": 1,
                    "similarity": {
                        "scripted_tfidf": {
                            "type": "scripted",
                            "script": {
                                "source": "double tf = Math.sqrt(doc.freq); double idf = Math.log((field.docCount+1.0)/(term.docFreq+1.0)) + 1.0; double norm = 1/Math.sqrt(doc.length); return query.boost * tf * idf * norm;"
                            }
                        }
                    }
                },
                "mappings": {
                    "properties": {
                        "name": {
                            "type": "text",
                            "similarity": "scripted_tfidf"
                        }
                    }
                }

            }
        )


# EsAPI.allIndex()
# EsAPI.srvHealthCheck()
# EsAPI.createIndex()
# EsAPI.dataInsert()
# EsAPI.searchAll()
EsAPI.searchFilter()

 

 

 

PUT /scripted-similarity-index
{
  "settings": {
    "number_of_shards": 1,
    "similarity": {
      "scripted_tfidf": {
        "type": "scripted",
        "script": {
          "source": "double tf = Math.sqrt(doc.freq); double idf = Math.log((field.docCount+1.0)/(term.docFreq+1.0)) + 1.0; double norm = 1/Math.sqrt(doc.length); return query.boost * tf * idf * norm;"
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "field": {
        "type": "text",
        "similarity": "scripted_tfidf"
      }
    }
  }
}

PUT /scripted-similarity-index/_doc/1
{
  "field": "foo bar foo"
}

PUT /scripted-similarity-index/_doc/2
{
  "field": "bar baz"
}

POST /scripted-similarity-index/_refresh

GET /scripted-similarity-index/_search?explain=true
{
  "query": {
    "query_string": {
      "query": "foo^1.7",
      "default_field": "field"
    }
  }
}