发布时间:2020-02-22 11:46:39编辑:admin阅读(2384)
注意: 本环境使用 elasticsearch 7.0版本开发,切勿低于此版本
有一张表,记录的数据特别的多,需要将7天前的记录,插入到Elasticsearch中,并删除原有表7天前的记录。
表结构如下:
CREATE TABLE `historic_records` ( `id` bigint(20) NOT NULL AUTO_INCREMENT, `user_id` varchar(50) NOT NULL DEFAULT '' COMMENT '用户id', `time` bigint(20) NOT NULL DEFAULT '0' COMMENT '上线/下线时间', `create_time` bigint(20) NOT NULL DEFAULT '0' COMMENT '创建时间', `update_time` bigint(20) NOT NULL DEFAULT '0' COMMENT '更新时间', `online_status` tinyint(1) NOT NULL DEFAULT '0' COMMENT '在线状态 默认1 0 离线 1 在线', `status` tinyint(1) NOT NULL DEFAULT '1' COMMENT '软删除标志:0-已删除;1-正常', PRIMARY KEY (`id`), KEY `user_id` (`user_id`), KEY `order_index` (`time`,`create_time`,`update_time`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='历史记录表';
查询sql:
select * from historic_records where create_time < unix_timestamp(date_add(cast(sysdate() as date), interval -7 day)) * 1000
删除sql:
delete from historic_records where create_time < unix_timestamp(date_add(cast(sysdate() as date), interval -7 day)) * 1000
相当于mysql中的数据库
相当于mysql中的一张表
相当于mysql中的一行(一条记录)
相当于mysql中的一列(一个字段)
一个服务器,由一个名字来标识
一个或多个节点组织在一起
将一份数据划分为多小份的能力,允许水平分割和扩展容量。多个分片可以响应请求,提高性能和吞吐量。
复制数据,一个节点出问题时,其余节点可以顶上。
可参考 https://www.elastic.co/guide/cn/elasticsearch/guide/current/inverted-index.html
设定映射,规定好各个字段及其数据类型,便于es更好地进行管理。根据mysql表结构,映射如下:
# 创建映射 _index_mappings = { "settings": { "index": { "number_of_shards": 3, "number_of_replicas": 1 } }, "mappings": { # self.index_type : { "properties": { "id": {"type": "long"}, "loid": {"type": "keyword"}, "mac": {"type": "keyword"}, "time": { "type": "date", "format": "epoch_millis" }, "create_time": { "type": "date", "format": "epoch_millis" }, "update_time": { "type": "date", "format": "epoch_millis" }, "online_status": {"type": "short"}, "status": {"type": "short"} } # } } }
解释:
索引设置,都在 settings{...} 中
number_of_shards
每个索引的主分片数,默认值是 5 。这个配置在索引创建后不能修改。
number_of_replicas
每个主分片的副本数,默认值是 1 。对于活动的索引库,这个配置可以随时修改。
映射配置,都在mappings{...} 中
属性设置,都在 properties{...} 中
Elasticsearch 支持 如下简单域类型:
字符串: string
整数 : byte
, short
, integer
, long
浮点数: float
, double
布尔型: boolean
日期: date
仔细看上面的mysql 表结构
由于 id 的类型是 bigint(20),那么在es中就是 long,表示长整形。
user_id 的类型是 varchar(50) ,在es中,有2中,分别是 text和 keyword。
这2种,是有区别的。text 会创建全文索引,支持模糊搜索。而keyword则不会,必须精确搜索才行。
由于 user_id不需要模糊搜索,因此 设置 keyword才是合理的。
create_time 虽然类型是 bigint(20),但是它存储在mysql里面,表示时间戳。
因此es中就是data,时间格式为:epoch_millis,表示微秒时间戳。
online_status 的类型是tinyint(1),在es中是 short,表示短的数字
新建目录elasticsearch
mkdir /opt/elasticsearch-7.1.1
目录结构如下:
./ ├── dockerfile ├── elasticsearch-7.1.1-amd64.deb ├── run.sh └── sources.list
dockerfile
FROM ubuntu:16.04 # 修改更新源为阿里云 ADD sources.list /etc/apt/sources.list ADD elasticsearch-7.1.1-amd64.deb ./ # 安装jdk和elasticsearch RUN apt-get update && apt-get install -y openjdk-8-jdk --allow-unauthenticated && apt-get clean all && dpkg -i elasticsearch-7.1.1-amd64.deb && rm -rf elasticsearch-7.1.1-amd64.deb EXPOSE 9200 # 添加启动脚本 ADD run.sh . RUN chmod 755 run.sh ENTRYPOINT [ "/run.sh"]
run.sh
#!/bin/bash set -e # 添加时区 TZ=Asia/Shanghai ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone # 覆盖配置文件 cp /etc/elasticsearch/elasticsearch.yml /etc/elasticsearch/elasticsearch.yml.bak echo "transport.host: localhost transport.tcp.port: 9300 http.port: 9200 network.host: 0.0.0.0" >> /etc/elasticsearch/elasticsearch.yml # 修改启动文件,去掉-d参数,避免后台运行 sed -i 72's@-d -p $PID_FILE@-p $PID_FILE@g' /etc/init.d/elasticsearch # 启动elasticsearch,要hold住,否则容器启动就退出了! /etc/init.d/elasticsearch start
sources.list
deb http://mirrors.aliyun.com/ubuntu/ xenial main restricted deb http://mirrors.aliyun.com/ubuntu/ xenial-updates main restricted deb http://mirrors.aliyun.com/ubuntu/ xenial universe deb http://mirrors.aliyun.com/ubuntu/ xenial-updates universe deb http://mirrors.aliyun.com/ubuntu/ xenial multiverse deb http://mirrors.aliyun.com/ubuntu/ xenial-updates multiverse deb http://mirrors.aliyun.com/ubuntu/ xenial-backports main restricted universe multiverse deb http://mirrors.aliyun.com/ubuntu xenial-security main restricted deb http://mirrors.aliyun.com/ubuntu xenial-security universe deb http://mirrors.aliyun.com/ubuntu xenial-security multiverse
生成镜像
docker build -t elasticsearch-7.1.1 .
启动容器
docker run -d -it --restart=always -p 9200:9200 elasticsearch-7.1.1
访问页面
新建目录kibana
mkdir /opt/kibana-7.1.1
目录结构如下:
./ ├── dockerfile ├── kibana-7.1.1-amd64.deb └── run.sh
dockerfile
FROM ubuntu:16.04 ADD kibana-7.1.1-amd64.deb ./ # 安装jdk和elasticsearch RUN dpkg -i kibana-7.1.1-amd64.deb && rm -rf kibana-7.1.1-amd64.deb EXPOSE 5601 # 添加启动脚本 ADD run.sh . RUN chmod 755 run.sh ENTRYPOINT [ "/run.sh"]
run.sh
#!/bin/bash # 添加时区 TZ=Asia/Shanghai ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone #elasticsearch="192.168.91.128" if [ -z $elasticsearch ];then echo "elasticsearch参数为空!比如: 192.168.91.128" exit fi # 修改配置文件 # 修改监听地址 sed -i '7s@#server.host: "localhost"@server.host: "0.0.0.0"@g' /etc/kibana/kibana.yml # 删除行,并添加一行内容 sed -i '28d' /etc/kibana/kibana.yml sed -i "N;28 i elasticsearch.hosts: ["http://$elasticsearch:9200"]" /etc/kibana/kibana.yml # 启动 /usr/share/kibana/bin/kibana "-c /etc/kibana/kibana.yml"
生成镜像
docker build -t kibana-7.1.1 .
启动镜像
docker run -d -it --restart=always -p 5601:5601 -e elasticsearch=192.168.10.104 kibana-7.1.1
访问页面
为了方便操作 mysql,封装了一个mysql工具类,用来查询和更新数据。
mysql.py
#!/usr/bin/env python3 # coding: utf-8 import pymysql class Mysql(object): # mysql 端口号,注意:必须是int类型 def __init__(self,host,user,passwd,db_name,port=3306): self.host = host self.user = user self.passwd = passwd self.db_name = db_name self.port = port def select(self,sql): """ 执行sql命令 :param sql: 命令 :return: 元祖 """ try: conn = pymysql.connect( host=self.host, user=self.user, passwd=self.passwd, port=self.port, database=self.db_name, charset='utf8', cursorclass=pymysql.cursors.DictCursor ) cur = conn.cursor() # 创建游标 cur.execute(sql) # 执行sql命令 res = cur.fetchall() # 获取执行的返回结果 cur.close() conn.close() # 关闭mysql 连接 return res except Exception as e: print(e) return False def update(self,sql): """ 更新操作,比如insert, delete,update :param sql: sql命令 :return: bool """ try: conn = pymysql.connect( host=self.host, user=self.user, passwd=self.passwd, port=self.port, database=self.db_name, ) cur = conn.cursor(cursor=pymysql.cursors.DictCursor) # 创建游标 # conn.cursor() # print("ip: {} insert 执行命令: {}".format(self.host,sql)) sta = cur.execute(sql) # 执行sql命令,返回影响的行数 # print("sta",sta,type(sta)) #res = cur.fetchall() # 获取执行的返回结果 if isinstance(sta,int): # 判断返回结果, 是数字就是正常的 #print('插入记录 Done') pass # write_log('正常,远程执行sql: %s 成功'%sql, "green") else: write_log('错误,远程执行sql: %s 失败'%sql, "red") return False conn.commit() # 主动提交,否则执行sql不生效 cur.close() conn.close() # 关闭mysql 连接 return sta except Exception as e: print(e) # write_log('错误,远程mysql执行命令: {} 异常'.format(sql), "red") return False
使用时,就简单了。导入这个类,调用相关方法。
mysql_test.py
from mysql import Mysql host = "192.168.0.179" user = "sdn_db" passwd = "Sdn@ujmyhn" db_name = "terminalservice" port = 3306 sql = "select * from terminals_record_0 where create_time < unix_timestamp(date_add(cast(sysdate() as date), interval -7 day)) * 1000" res = Mysql(host,user,passwd,db_name,port).select(sql) print(res)
由于时间关系,代码不一一解释了。附上完整代码:
./ ├── conf.py ├── es_bulk.py ├── README.md ├── requirements.txt └── utils ├── common.py └── mysql.py
conf.py
#!/usr/bin/env python3 # coding: utf-8 """ 配置文件,用于mysql和elasticsearch """ import os BASE_DIR = os.path.dirname(os.path.abspath(__file__)) # 项目根目录 # mysql HOST = "192.168.0.136" USER = "root" PASSWD = "123456" DB_NAME = "terminal" PORT = 3306 # elasticsearch INDEX_NAME = "historic_records" INDEX_TYPE = "_doc" ES_IP = "192.169.3.133" MAXIMUM = 100 # 一次性插入多少条
es_bulk.py
#!/usr/bin/env python3 # coding: utf-8 import time from elasticsearch import Elasticsearch from elasticsearch import helpers import conf from utils.mysql import Mysql from utils.common import write_log,valid_ip,check_tcp class ElasticObj: def __init__(self,timeout=3600): ''' :param timeout: 超时时间 ''' self.index_name = conf.INDEX_NAME # 索引名称 self.index_type = conf.INDEX_TYPE # 索引类型 self.es_ip = conf.ES_IP # es ip # 无用户名密码状态 self.es = Elasticsearch([self.es_ip], port=9200, timeout=timeout) # 用户名密码状态 # self.es = Elasticsearch([self.es_ip], http_auth=('esadm', 'mdase123'), port=9200, timeout=timeout) def create_index(self): ''' 创建索引 :return: bool ''' # 创建映射 _index_mappings = { # 索引配置 "settings": { "index": { "number_of_shards": 3, # 分片数 "number_of_replicas": 1 # 副本数 } }, # 设置字段 "mappings": { "properties": { "id": {"type": "long"}, "loid": {"type": "keyword"}, "mac": {"type": "keyword"}, "time": { "type": "date", "format": "epoch_millis" }, "create_time": { "type": "date", "format": "epoch_millis" }, "update_time": { "type": "date", "format": "epoch_millis" }, "online_status": {"type": "short"}, "status": {"type": "short"} } } } # 判断索引不存在时 if self.es.indices.exists(index=self.index_name) is not True: # 创建索引 res = self.es.indices.create(index=self.index_name, body=_index_mappings) # print(res) if not res: write_log("错误,创建索引{}失败".format(self.index_name),"red") return False write_log("正常,创建索引{}成功".format(self.index_name), "green") return True else: write_log("正常,索引{}已存在".format(self.index_name), "green") return True def bulk_insert(self,table,data_list): """ 批量写入数据 :param table: 表名 :param data_list: 数据列表 [ { 'online_status': 1, 'update_time': 1556073035327, 'create_time': 1556073035327, 'id': 1, 'status': 1, 'time': 1556073035327, 'loid': '100010000123', 'mac': '60:45:cb:87:c9:93' }, ... ] :return: bool """ # 批量插入 start_time = time.time() # 开始时间 actions = [] # 临时数据列表 i = 0 # 计数值 try: # 循环数据列表 for data in data_list: action = { "_index": self.index_name, "_type": self.index_type, #"_id": i, #_id 也可以默认生成,不赋值 "_source": { 'id': data['id'], 'user_id': data['user_id'], 'time': data['time'], 'create_time': data['create_time'], 'online_status': data['online_status'], 'status': data['status'], } } i += 1 actions.append(action) # 添加到列表 if len(action) == conf.MAXIMUM: # 列表数量达到100时 helpers.bulk(self.es, actions) # 批量插入数据 del actions[0:len(action)] # 删除列表元素 if i > 0: # 不足100时,插入剩余数据 helpers.bulk(self.es, actions) end_time = time.time() # 结束时间 t = round((end_time - start_time),2) # 计算耗时 # print('本次共写入{}条数据,用时{}s'.format(i, t)) write_log("正常,{} 表写入ES {}条数据,用时{}s".format(table,i, t), "green") return True except Exception as e: print(e) return False def has_table(self,db_name,target_table): """ 远程表是否存在 :return: bool """ mysql_obj = Mysql(conf.HOST, conf.USER, conf.PASSWD, conf.DB_NAME, conf.PORT) sql = "select count(1) from {}.{}".format(db_name, target_table) res = mysql_obj.select(sql) # print("表是否存在",res,type(res)) if res is False: write_log("错误,远程表 {}.{} 不存在".format(db_name,target_table),"red") return False else: return True def has_conf(self): """ 判断配置文件中的mysql和es 端口是否正常 :return: """ if not valid_ip(conf.HOST): write_log("错误,MySQL IP配置不正确","red") return False if not valid_ip(conf.ES_IP): write_log("错误,ES IP配置不正确","red") return False if not check_tcp(conf.HOST,conf.PORT): write_log("错误,MySQL {} 端口不可达".format(conf.PORT),"red") return False if not check_tcp(conf.ES_IP,9200): write_log("错误,ES 9200 端口不可达","red") return False return True def read_mysql_es(self): """ 读取7天的记录,并写入es :return: bool """ # 判断配置文件中的mysql和es 端口是否正常 if not self.has_conf(): # print(1) return False # 创建索引 if self.create_index() is False: # print(2) return False max = conf.MAXIMUM # 一次性查询多少条 flag_list = [] # 标志位列表 mysql_obj = Mysql(conf.HOST, conf.USER, conf.PASSWD, conf.DB_NAME, conf.PORT) for i in range(64): # 写入64张表 # 判断表是否存在 res = self.has_table(conf.DB_NAME,'historic_record_%s'%i) if not res: flag_list.append(False) return False id = 0 # 每一次查询后的最大id while True: # 查询数据 sql = "select * from historic_record_%s where create_time < unix_timestamp(date_add(cast(sysdate() as date), interval -7 day)) * 1000 and id > %s order by id limit %s" % ( i, id, max) # print(sql) data_list = mysql_obj.select(sql) # print(data_list) if not data_list: # 当结果为空时,结束循环 write_log("警告,执行sql: %s 记录为空,无需写入es" %(sql), "yellow") break # 跳出循环 last_row = data_list[-1] # 最后一行记录 # print(last_row) id = last_row['id'] # 修改最大id res = self.bulk_insert('historic_record_%s' % i, data_list) if not res: write_log("错误,historic_record_%s 写入ES 失败"%i,"red") flag_list.append(False) return False if False in flag_list: write_log("错误,historic_record 部分表写入ES错误,请查看上文","red") return False write_log("正常,historic_record 64张表全部写入ES成功", "green") return True def delete_record(self): """ 删除7天的表数据 :return: bool """ max = conf.MAXIMUM # 一次性查询多少条 flag_list = [] mysql_obj = Mysql(conf.HOST, conf.USER, conf.PASSWD, conf.DB_NAME, conf.PORT) for i in range(64): # 64张表 # 判断表是否存在 res = self.has_table(conf.DB_NAME, 'historic_record_%s' % i) if not res: flag_list.append(False) return False ### 先查询数据 id = 0 # 每一次查询后的最大id while True: # 查询数据 sql = "select * from historic_record_%s where create_time < unix_timestamp(date_add(cast(sysdate() as date), interval -7 day)) * 1000 and id > %s order by id limit %s" % ( i, id, max) # print(sql) data_list = mysql_obj.select(sql) # print(data_list) if not data_list: # 当结果为空时,结束循环 write_log("警告,执行sql: %s 记录为空,无需删除" % sql, "yellow") break # 跳出循环 ### 再删除数据 sql = "delete from historic_record_%s where create_time < unix_timestamp(date_add(cast(sysdate() as date), interval -7 day)) * 1000 and id > %s order by id limit %s" % ( i, id, max) # print(sql) res = mysql_obj.update(sql) if res is False: write_log("错误,删除 historic_record_%s 记录失败" % i, "red") flag_list.append(False) break else: write_log("正常,删除 historic_record_%s 记录成功" % i, "green") last_row = data_list[-1] # 最后一行记录 # print(last_row) id = last_row['id'] # 修改最大id if False in flag_list: write_log("错误,删除 historic_record 部分表失败,请查看上文", "red") return False write_log("正常,删除 historic_record 64张表记录全部成功", "green") def main(self): self.read_mysql_es() self.delete_record() ElasticObj().main() # 执行主程序
common.py
#!/usr/bin/env python3 # coding: utf-8 """ 共有的方法 """ import sys import io def setup_io(): # 设置默认屏幕输出为utf-8编码 sys.stdout = sys.__stdout__ = io.TextIOWrapper(sys.stdout.detach(), encoding='utf-8', line_buffering=True) sys.stderr = sys.__stderr__ = io.TextIOWrapper(sys.stderr.detach(), encoding='utf-8', line_buffering=True) setup_io() import os import time import conf import socket import subprocess import ipaddress from multiprocessing import cpu_count def write_log(content,colour='white',skip=False): """ 写入日志文件 :param content: 写入内容 :param colour: 颜色 :param skip: 是否跳过打印时间 :return: """ # 颜色代码 colour_dict = { 'red': 31, # 红色 'green': 32, # 绿色 'yellow': 33, # 黄色 'blue': 34, # 蓝色 'purple_red': 35, # 紫红色 'bluish_blue': 36, # 浅蓝色 'white': 37, # 白色 } choice = colour_dict.get(colour) # 选择颜色 path = os.path.join(conf.BASE_DIR,"output.log") # 日志文件 with open(path, mode='a+', encoding='utf-8') as f: if skip is False: # 不跳过打印时间时 content = time.strftime('%Y-%m-%d %H:%M:%S') + ' ' + content info = "\033[1;{};1m{}\033[0m".format(choice, content) print(info) f.write(content+"\n") def execute_linux2(cmd, timeout=10, skip=False): """ 执行linux命令,返回list :param cmd: linux命令 :param timeout: 超时时间,生产环境, 特别卡, 因此要3秒 :param skip: 是否跳过超时 :return: list """ p = subprocess.Popen(cmd, stderr=subprocess.STDOUT, stdout=subprocess.PIPE, shell=True) # print(p) # timeout = 1 # 超时时间 t_beginning = time.time() # 开始时间 # seconds_passed = 0 # 执行时间 while True: if p.poll() is not None: break seconds_passed = time.time() - t_beginning if timeout and seconds_passed > timeout: p.terminate() # raise TimeoutError(cmd, timeout) if not skip: # self.res.code = 500 # print('命令: {},执行超时!'.format(cmd)) write_log('错误, 命令: {},本地执行超时!'.format(cmd),"red") # return self.res.__dict__ return False # return '命令: {},执行超时!'.format(cmd) # result = p.stdout.read().decode('utf-8').strip() # 命令运行结果 # print("result",result) # self.res.data = result # return self.res.__dict__ result = p.stdout.readlines() return result def valid_ip(ip): """ 验证ip是否有效,比如192.168.1.256是一个不存在的ip :return: bool """ try: # 判断 python 版本 if sys.version_info[0] == 2: ipaddress.ip_address(ip.strip().decode("utf-8")) elif sys.version_info[0] == 3: # ipaddress.ip_address(bytes(ip.strip().encode("utf-8"))) ipaddress.ip_address(ip) return True except Exception as e: print(e) return False def check_tcp(ip, port, timeout=1): """ 检测tcp端口 :param ip: ip地址 :param port: 端口号 :param timeout: 超时时间 :return: bool """ flag = False try: socket.setdefaulttimeout(timeout) # 整个socket层设置超时时间 cs = socket.socket(socket.AF_INET, socket.SOCK_STREAM) address = (str(ip), int(port)) status = cs.connect_ex((address)) # 开始连接 cs.settimeout(timeout) if not status: flag = True return flag except Exception as e: print(e) return flag COROUTINE_NUMBER = cpu_count() # 协程池数量,根据cpu核心数来开,避免cpu飙高
mysql.py
#!/usr/bin/env python3 # coding: utf-8 import pymysql from utils.common import write_log class Mysql(object): # mysql 端口号,注意:必须是int类型 def __init__(self,host,user,passwd,db_name,port=3306): self.host = host self.user = user self.passwd = passwd self.db_name = db_name self.port = port def select(self,sql): """ 执行sql命令 :param sql: 命令 :return: 元祖 """ try: # print(host,self.user,self.passwd,self.port,self.db_name) conn = pymysql.connect( host=self.host, user=self.user, passwd=self.passwd, port=self.port, database=self.db_name, charset='utf8', cursorclass=pymysql.cursors.DictCursor ) cur = conn.cursor() # 创建游标 # conn.cursor() cur.execute(sql) # 执行sql命令 res = cur.fetchall() # 获取执行的返回结果 cur.close() conn.close() # 关闭mysql 连接 return res except Exception as e: print(e) return False def update(self,sql): """ 更新操作,比如insert, delete,update :param sql: sql命令 :return: bool """ try: conn = pymysql.connect( host=self.host, user=self.user, passwd=self.passwd, port=self.port, database=self.db_name, ) cur = conn.cursor(cursor=pymysql.cursors.DictCursor) # 创建游标 # conn.cursor() # print("ip: {} insert 执行命令: {}".format(self.host,sql)) sta = cur.execute(sql) # 执行sql命令,返回影响的行数 # print("sta",sta,type(sta)) #res = cur.fetchall() # 获取执行的返回结果 if isinstance(sta,int): # 判断返回结果, 是数字就是正常的 #print('插入记录 Done') pass # write_log('正常,远程执行sql: %s 成功'%sql, "green") else: write_log('错误,远程执行sql: %s 失败'%sql, "red") return False conn.commit() # 主动提交,否则执行sql不生效 cur.close() conn.close() # 关闭mysql 连接 #Migration.flag_list.append(True) return sta except Exception as e: print(e) # write_log('错误,远程mysql执行命令: {} 异常'.format(sql), "red") # Migration.flag_list.append(False) return False
requirements.txt
PyMySQL==0.9.2 elasticsearch==6.3.1
README.md
## 说明 终端历史记录表,写入到elasticsearch中。 主要将(terminal.historic_record_0~63) 这64张表的7天前数据写入到elasticsearch中 并删除 64张表的7天前记录 `注意: 本环境使用 elasticsearch 7.0版本开发,切勿低于此版本` ## 配置说明 `conf.py` 是环境配置 主要修改 以下信息 ```python # mysql HOST = "192.168.0.136" USER = "root" PASSWD = "123456" DB_NAME = "terminal" PORT = 3306 # elasticsearch INDEX_NAME = "historic_record" INDEX_TYPE = "_doc" ES_IP = "192.169.3.133" ``` 请根据实际情况修改以上变量 ## 运行说明 ## 一键执行,迁移相关所有表 `python es_bulk.py` ## 查看结果 结果会输出到`output.log`文件,直接查看即可! 登录到`kibana`,查看数据是否存在 <br/> <br/> Copyright (c) 2019-present, xiao You
注意:如果是es 6.x的版本,创建索引,需要增加 index_type,否则会报错。
比如:
# 创建映射 _index_mappings = { # 索引配置 "settings": { "index": { "number_of_shards": 3, # 分片数 "number_of_replicas": 1 # 副本数 } }, # 设置字段 "mappings": { self.index_type: { "properties": { "id": {"type": "long"}, "loid": {"type": "keyword"}, "mac": {"type": "keyword"}, "time": { "type": "date", "format": "epoch_millis" }, "create_time": { "type": "date", "format": "epoch_millis" }, "update_time": { "type": "date", "format": "epoch_millis" }, "online_status": {"type": "short"}, "status": {"type": "short"} } } } }
本文参考链接:
https://www.cnblogs.com/aaanthony/p/7380662.html
https://blog.csdn.net/m0_37673307/article/details/81153700
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