windows下載zip
linux下載tar
下載地址:https://www.elastic.co/downloads/elasticsearch
解壓后運行:bin/elasticsearch (or bin\elasticsearch.bat on Windows)
檢查是否成功:訪問 http://localhost:9200
linux下不能以root用戶運行,
普通用戶運行報錯:
java.nio.file.AccessDeniedException
原因:當前用戶沒有執行權限
解決方法: chown linux用戶名 elasticsearch安裝目錄 -R
例如:chown ealsticsearch /data/wwwroot/elasticsearch-6.2.4 -R
PS:其他Java軟件報.AccessDeniedException錯誤也可以同樣方式解決,給 執行用戶相應的目錄權限即可
2|0代碼實例
如下的代碼實現類似鏈家網小區搜索功能。
從文件讀取小區及地址信息寫入es,然后通過小區所在城市code及搜索關鍵字 匹配到對應小區。
代碼主要包含三部分內容:
1.創建索引
2.用bulk將批量數據存儲到es
3.數據搜索
注意:
代碼的es版本交低2.xx版本,高版本在創建的索引數據類型有所不同
#coding:utf8 from __future__ import unicode_literals import os import time import config from datetime import datetime from elasticsearch import Elasticsearch from elasticsearch.helpers import bulk class ElasticSearch(): def __init__(self, index_name,index_type,ip ="127.0.0.1"): ''' :param index_name: 索引名稱 :param index_type: 索引類型 ''' self.index_name =index_name self.index_type = index_type # 無用戶名密碼狀態 #self.es = Elasticsearch([ip]) #用戶名密碼狀態 self.es = Elasticsearch([ip],http_auth=('elastic', 'password'),port=9200) def create_index(self,index_name="ftech360",index_type="community"): ''' 創建索引,創建索引名稱為ott,類型為ott_type的索引 :param ex: Elasticsearch對象 :return: ''' #創建映射 _index_mappings = { "mappings": { self.index_type: { "properties": { "city_code": { "type": "string", # "index": "not_analyzed" }, "name": { "type": "string", # "index": "not_analyzed" }, "address": { "type": "string", # "index": "not_analyzed" } } } } } if self.es.indices.exists(index=self.index_name) is True: self.es.indices.delete(index=self.index_name) res = self.es.indices.create(index=self.index_name, body=_index_mappings) print res def build_data_dict(self): name_dict = {} with open(os.path.join(config.datamining_dir,'data_output','house_community.dat')) as f: for line in f: line_list = line.decode('utf-8').split('\t') community_code = line_list[6] name = line_list[7] city_code = line_list[0] name_dict[community_code] = (name,city_code) address_dict = {} with open(os.path.join(config.datamining_dir,'data_output','house_community_detail.dat')) as f: for line in f: line_list = line.decode('utf-8').split('\t') community_code = line_list[6] address = line_list[10] address_dict[community_code] = address return name_dict,address_dict def bulk_index_data(self,name_dict,address_dict): ''' 用bulk將批量數據存儲到es :return: ''' list_data = [] for community_code, data in name_dict.items(): tmp = {} tmp['code'] = community_code tmp['name'] = data[0] tmp['city_code'] = data[1] if community_code in address_dict: tmp['address'] = address_dict[community_code] else: tmp['address'] = '' list_data.append(tmp) ACTIONS = [] for line in list_data: action = { "_index": self.index_name, "_type": self.index_type, "_id": line['code'], #_id 小區code "_source": { "city_code": line['city_code'], "name": line['name'], "address": line['address'] } } ACTIONS.append(action) # 批量處理 success, _ = bulk(self.es, ACTIONS, index=self.index_name, raise_on_error=True) #單條寫入 單條寫入速度很慢 #self.es.index(index=self.index_name,doc_type="doc_type_test",body = action) print('Performed %d actions' % success) def delete_index_data(self,id): ''' 刪除索引中的一條 :param id: :return: ''' res = self.es.delete(index=self.index_name, doc_type=self.index_type, id=id) print res def get_data_id(self,id): res = self.es.get(index=self.index_name, doc_type=self.index_type,id=id) # # 輸出查詢到的結果 print res['_source']['city_code'], res['_id'], res['_source']['name'], res['_source']['address'] def get_data_by_body(self, name, city_code): # doc = {'query': {'match_all': {}}} doc = { "query": { "bool":{ "filter":{ "term":{ "city_code": city_code } }, "must":{ "multi_match": { "query": name, "type":"phrase_prefix", "fields": ['name^3', 'address'], "slop":1, } } } } } _searched = self.es.search(index=self.index_name, doc_type=self.index_type, body=doc) data = _searched['hits']['hits'] return data if __name__=='__main__': #數據插入es obj = ElasticSearch("ftech360","community") obj.create_index() name_dict, address_dict = obj.build_data_dict() obj.bulk_index_data(name_dict,address_dict) #從es讀取數據 obj2 = ElasticSearch("ftech360","community") obj2.get_data_by_body(u'保利','510100')
以上就是全部知識點內容,感謝大家的閱讀和對腳本之家的支持。
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