下载地址：https://www.elastic.co/downloads/elasticsearch
解压后运行：bin/elasticsearch (or bin\elasticsearch.bat on Windows)
检查是否成功：访问 :9200
linux下不能以root用户运行皇姑区网站优化
下载地址：https://www.elastic.co/downloads/elasticsearch
解压后运行：bin/elasticsearch (or bin\elasticsearch.bat on Windows)
检查是否成功：访问 :9200
linux下不能以root用户运行
普通用户运行报错：
java.nio.file.AccessDeniedException
原因：当前用户没有执行权限
解决方法： chown linux用户名 elasticsearch安装目录 -R
例如：chown ealsticsearch /data/wwwroot/elasticsearch-6.2.4 -R
PS：其他Java软件报.AccessDeniedException错误也可以同样方式解决给 执行用户相应的目录权限即可
2|0代码实例
如下的代码实现类似链家网小区搜索功能。
从文件读取小区及地址信息写入es,然后通过小区所在城市code及搜索关键字 匹配到对应小区。
代码主要包含三部分内容：
1.创建索引
2.用bulk将批量数据存储到es
3.数据搜索
注意：
代码的es版本交低2.xx版本金秀瑶族自治县SEO给 执行用户相应的目录权限即可
2|0代码实例
如下的代码实现类似链家网小区搜索功能。
从文件读取小区及地址信息写入es,然后通过小区所在城市code及搜索关键字 匹配到对应小区。
代码主要包含三部分内容：
1.创建索引
2.用bulk将批量数据存储到es
3.数据搜索
注意：
代码的es版本交低2.xx版本高版本在创建的索引数据类型有所不同
#coding:utf8from __future__ import unicode_literalsimport osimport timeimport configfrom datetime import datetimefrom elasticsearch import Elasticsearchfrom elasticsearch.helpers import bulkclass ElasticSearch(): def __init__(self, index_name,index_type,ip ="127.0.0.1"): ''' :param index_name: 索引名称 :param index_type: 索引类型 ''' self.index_name =index_name self.index_type = index_type # 无用户名密码状态 #self.es = Elasticsearch([ip]) #用户名密码状态 self.es = Elasticsearch([ip],http_auth=('elastic', 'password'),port=9200) def create_index(self,index_name="ftech360",index_type="community"): ''' 创建索引,创建索引名称为ott皇姑区网站优化高版本在创建的索引数据类型有所不同 #coding:utf8from __future__ import unicode_literalsimport osimport timeimport configfrom datetime import datetimefrom elasticsearch import Elasticsearchfrom elasticsearch.helpers import bulkclass ElasticSearch(): def __init__(self, index_name,index_type,ip ="127.0.0.1"): ''' :param index_name: 索引名称 :param index_type: 索引类型 ''' self.index_name =index_name self.index_type = index_type # 无用户名密码状态 #self.es = Elasticsearch([ip]) #用户名密码状态 self.es = Elasticsearch([ip],http_auth=('elastic', 'password'),port=9200) def create_index(self,index_name="ftech360",index_type="community"): ''' 创建索引,创建索引名称为ott类型为ott_type的索引 :param ex: Elasticsearch对象 :return: ''' #创建映射 _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将批量数据存储到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 小区code "_source": { "city_code": line['city_code'], "name": line['name'], "address": line['address'] } } ACTIONS.append(action) # 批量处理 success, _ = bulk(self.es, ACTIONS, index=self.index_name, raise_on_error=True) #单条写入 单条写入速度很慢 #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): ''' 删除索引中的一条 :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) # # 输出查询到的结果 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__': #数据插入es obj = ElasticSearch("ftech360","community") obj.create_index() name_dict, address_dict = obj.build_data_dict() obj.bulk_index_data(name_dict,address_dict) #从es读取数据 obj2 = ElasticSearch("ftech360","community") obj2.get_data_by_body(u'保利','510100')以上就是全部知识点内容感谢大家的阅读和对本站的支持。