python爬取前程无忧招聘用Hive做数据分析Sqoop存储到Mysql并可视化

一、导出数据

导出为zh_all2.txt文件

二、上传数据

三、使用Flume传入HDFS

（1）编写conf文件
在flume的conf目录下新建文件

a1.sources=r1
a1.channels=c1
a1.sinks=s1a1.sources.r1.type=exec
a1.sources.r1.command=tail -F /opt/module/flume-1.9.0/conf/data/zh_all2.txt
a1.sources.r1.bind=0.0.0.0
a1.sources.r1.port=44444a1.sinks.s1.type=HDFSa1.sinks.s1.type=hdfs://hadoop129:90000/user/flume/qcwy_txt
a1.sinks.s1.hdfs.rollCount=0
a1.sinks.s1.hdfs.fileType=Datastream# 配置a1的channel组件c1的属性
a1.channels.c1.type=memory
a1.channels.c1.capacity=1000
a1.channels.c1.transactionCapacity=100
# 为source和sink组件绑定channel
a1.sources.r1.channels=c1
a1.sinks.k1.channel=c1

文件传入成功

四、数据分析

1、利用hive进行分析，2、将hive分析结果利用sqoop技术存储到mysql数据库中，并最后显示分析结果

1、启动Hive导入zh_all2.txt数据

2、查看table表qcwy2

3、岗位薪资分析

分析“数据分析”、“大数据开发工程师”、“数据采集”等岗位的平均工资、最高工资、最低工资，并作条形图将结果展示出来

A. 数据分析岗位
（1）模糊匹配提取
以模糊匹配提取出数据分析岗位的记录，存入表f_x_1（只存Jobtitle和wages字段）

（2）切分薪资字段存储

create table f_x_2 as select Jobtitle, regexp_extract(wages,'([0-9]+)-',1) as a_min, regexp_extract(wages,'-([0-9]+)',1) as a_max, (regexp_extract(wages,'([0-9]+)-',1) + regexp_extract(wages,'-([0-9]+)',1))/2 as a_avg from f_x_1;

数据分析

数据采集


大数据


（3）计算最大 、最小、平均

create table f_x_3 as select "数据分析" as Jobtitle, min(int(a_min)*0.1) as s_min, max(int(a_max)*0.1) as s_max, regexp_extract(avg(a_avg),'([0-9]+.[0-9]?[0-9]?)',1)*0.1 as s_avg from f_x_2;

汇总
（4）、下面查询大数据、数据采集方法类似、然后汇总为一张总表

四、使用sqoop存到mysql

（1）在mysql创建数据库数据表
进入数据库：mysql -u root -p

创建qcwy_db数据库

使用qcwy_db数据库创建表

（1）创建表：create table tab1(t_name varchar(20), t_min int, t_max int, t_avg varchar(10)) charset utf8 collate utf8_general_ci;

（2）导入数据

bin/sqoop export --connect jdbc:mysql://hadoop129:3306/qcwy_db  --username root --password 1 --table tab1 --export-dir /user/hive/warehouse/qcwy_db.db/tab1 --input-null-string "\\\\N" --input-null-non-string "\\\\N" --input-fields-terminated-by "\001" --input-lines-terminated-by "\\n" -m 1 

查询导入的数据

查询城市岗位数

可视化分析

创建远程访问mysql数据库用户

 GRANT ALL PRIVILEGES ON *.* TO 'admin'@'%' IDENTIFIED BY '1' WITH GRANT OPTION; 

1、岗位薪资分析

import pymysql
from pyecharts.charts import Bar
from pyecharts import options as opts
class MysqlTool:def __init__(self,host,user,password,database,port = 3306,charset = 'utf8'):self.host = hostself.user = userself.password = passwordself.database = databaseself.port = portself.charset = charsetdef connect(self):#连接数据库self.conn = pymysql.connect(host = self.host,user = self.user,password = self.password,database = self.database,port = self.port,charset = self.charset)self.cursor = self.conn.cursor() #cursor获取游标#增删改#sql:要执行的sql语句#args:带参sql的值#返回受影响的行数def __cud(self,sql,args = None):#私有row_count = 0try:self.connect()row_count = self.cursor.execute(sql,args)#execute执行self.conn.commit()#commit提交self.close()except Exception as e:print(e)return row_count#插入def insert(self,sql,args):return self.__cud(sql,args)#修改def updata(self,sql,args):return self.__cud(sql,args)#删除def delete(self,sql,args):return self.__cud(sql,args)#查询一条信息def get_one(self,sql,args=None):try:self.connect()self.cursor.execute(sql,args)result=self.cursor.fetchone()self.close()return resultexcept Exception as e:print(e)#查询多条信息def get_all(self,sql,args=None):try:self.connect()self.cursor.execute(sql,args)#  连接，获取光标，执行# result=self.cursor.execute()result=self.cursor.fetchall()#返回结果self.close()return resultexcept Exception as e:print(e)#关闭连接def close(self):self.cursor.close()self.conn.close()mt = MysqlTool('192.168.10.129', 'root', '1', 'hive')
def show_text():sql = "select * from work_1"result = mt.get_all(sql)
#得到职位名称
def show_name(list):vv = []for v in list:name = ''a = re.findall('[\u4e00-\u9fa5]', str(v))for i in a:name += ivv.append(name)#print(vv)return vv
#
def show_bar_chart1(data1,cc):ll = data1# 创建3个空数组average_Pay_level = []max_Pay_level = []min_Pay_level = []#循环向数组添加数据for i in ll:data = pd.DataFrame(list(db.find(i)))bb = data['wages'].valuesmax_Pay_level.append(Pay_level_list(bb)[0])average_Pay_level.append(Pay_level_list(bb)[1])min_Pay_level.append(Pay_level_list(bb)[2])show(max_Pay_level, average_Pay_level, min_Pay_level, cc)
#data为工资列表
#统一格式后，输出最大，平均，最小
def Pay_level_list(data):ww = [".*?千/月", ".*?万/月", ".*?万/年", ".*?元/天"]Pay_level_list = []for i in data:if isinstance(i, str):for j, v in enumerate(ww):if re.search(v, i) is not None:if j == 0:num = [round(i, 2) for i in([(i * 12 / 10) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))])]elif j == 1:num = [round(i, 2) for i in([(i * 12) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))])]elif j == 2:num = [round(i, 2) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))]elif j == 3:num = [round(i, 2) for i in([(i * 365 / 10000) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))])]Pay_level_list.append(num_al(num))return max(Pay_level_list), tall_num(Pay_level_list), min(Pay_level_list)
#求平均值
def tall_num(list):num = 0for i in list:num += ireturn round(num/(len(list)+1), 2)
def num_al(list):if len(list) >= 2:num = (list[0] + list[1]) / 2else:num = list[0]return round(num, 2)
#输出条形图
def show(a, b, c, d):name=d  #d = x轴标题（abcd个数要对应）y1 = a  # a = 最高工资列表y2 = b  #b = 平均工资列表y3 = c  #c = 最低工资x = pd.np.arange(len(name))width = 0.25plt.bar(x, y1, width=width, label='最高工资', color='red')plt.bar(x + width, y2, width=width, label='平均工资', color='deepskyblue', tick_label=name)plt.bar(x + 2 * width, y3, width=width, label='最低工资', color='green')# 显示在图形上的值for a, b in zip(x, y1):plt.text(a, b + 0.1, b, ha='center', va='bottom')for a, b in zip(x, y2):plt.text(a + width, b + 0.1, b, ha='center', va='bottom')for a, b in zip(x, y3):plt.text(a + 2 * width, b + 0.1, b, ha='center', va='bottom')plt.xticks()plt.legend(loc="upper left")  # 防止label和图像重合显示不出来plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签plt.ylabel('月/K')plt.xlabel('岗位名称')plt.rcParams['savefig.dpi'] = 300  # 图片像素plt.rcParams['figure.dpi'] = 300  # 分辨率plt.rcParams['figure.figsize'] = (15.0, 8.0)  # 尺寸plt.title("工资分析")plt.savefig('D:\\result.png')plt.show()

2、岗位数量分析

import pymysql
from pyecharts.charts import Bar
from pyecharts import options as opts
class MysqlTool:def __init__(self,host,user,password,database,port = 3306,charset = 'utf8'):self.host = hostself.user = userself.password = passwordself.database = databaseself.port = portself.charset = charsetdef connect(self):#连接数据库self.conn = pymysql.connect(host = self.host,user = self.user,password = self.password,database = self.database,port = self.port,charset = self.charset)self.cursor = self.conn.cursor() #cursor获取游标#增删改#sql:要执行的sql语句#args:带参sql的值#返回受影响的行数def __cud(self,sql,args = None):#私有row_count = 0try:self.connect()row_count = self.cursor.execute(sql,args)#execute执行self.conn.commit()#commit提交self.close()except Exception as e:print(e)return row_count#插入def insert(self,sql,args):return self.__cud(sql,args)#修改def updata(self,sql,args):return self.__cud(sql,args)#删除def delete(self,sql,args):return self.__cud(sql,args)#查询一条信息def get_one(self,sql,args=None):try:self.connect()self.cursor.execute(sql,args)result=self.cursor.fetchone()self.close()return resultexcept Exception as e:print(e)#查询多条信息def get_all(self,sql,args=None):try:self.connect()self.cursor.execute(sql,args)#  连接，获取光标，执行# result=self.cursor.execute()result=self.cursor.fetchall()#返回结果self.close()return resultexcept Exception as e:print(e)#关闭连接def close(self):self.cursor.close()self.conn.close()mt = MysqlTool('192.168.10.129', 'root', '1', 'hive')
def show_text():sql = "select * from work_1"result = mt.get_all(sql)
#得到职位名称
def show_name(list):vv = []for v in list:name = ''a = re.findall('[\u4e00-\u9fa5]', str(v))for i in a:name += ivv.append(name)return vv#饼图实现
def pie_chart(list1):city = list1city1 = []city2 = []for i in city:city1.append(i["recruiters"])#拿到公司名mm = show_name(city1)for j, v in enumerate(city):bb = len(pd.DataFrame(list(db.find(v))))city2.append(bb)mm[j] += str(bb)plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签sizes = city2# explode = (0.1, 0, 0, 0, 0)plt.pie(sizes, labels=mm, autopct='%1.1f%%', shadow=False, startangle=150)  # 想要突出plt.title("饼图示例-岗位数")plt.show()

三、岗位经验分析

import pymysql
from pyecharts.charts import Bar
from pyecharts import options as opts
class MysqlTool:def __init__(self,host,user,password,database,port = 3306,charset = 'utf8'):self.host = hostself.user = userself.password = passwordself.database = databaseself.port = portself.charset = charsetdef connect(self):#连接数据库self.conn = pymysql.connect(host = self.host,user = self.user,password = self.password,database = self.database,port = self.port,charset = self.charset)self.cursor = self.conn.cursor() #cursor获取游标#增删改#sql:要执行的sql语句#args:带参sql的值#返回受影响的行数def __cud(self,sql,args = None):#私有row_count = 0try:self.connect()row_count = self.cursor.execute(sql,args)#execute执行self.conn.commit()#commit提交self.close()except Exception as e:print(e)return row_count#插入def insert(self,sql,args):return self.__cud(sql,args)#修改def updata(self,sql,args):return self.__cud(sql,args)#删除def delete(self,sql,args):return self.__cud(sql,args)#查询一条信息def get_one(self,sql,args=None):try:self.connect()self.cursor.execute(sql,args)result=self.cursor.fetchone()self.close()return resultexcept Exception as e:print(e)#查询多条信息def get_all(self,sql,args=None):try:self.connect()self.cursor.execute(sql,args)#  连接，获取光标，执行# result=self.cursor.execute()result=self.cursor.fetchall()#返回结果self.close()return resultexcept Exception as e:print(e)#关闭连接def close(self):self.cursor.close()self.conn.close()mt = MysqlTool('192.168.10.129', 'root', '1', 'hive')
def show_text():sql = "select * from work_1"result = mt.get_all(sql)
#data为工资列表
# 统一格式后，输出最大，平均，最小
def Pay_level_list(data):ww = [".*?千/月", ".*?万/月", ".*?万/年", ".*?元/天"]Pay_level_list = []for i in data:if isinstance(i, str):for j, v in enumerate(ww):if re.search(v, i) is not None:if j == 0:num = [round(i, 2) for i in([(i * 12 / 10) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))])]elif j == 1:num = [round(i, 2) for i in([(i * 12) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))])]elif j == 2:num = [round(i, 2) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))]elif j == 3:num = [round(i, 2) for i in([(i * 365 / 10000) for i in (list(map(float, re.findall(r"\d+\.?\d*", i))))])]Pay_level_list.append(num_al(num))return max(Pay_level_list), tall_num(Pay_level_list), min(Pay_level_list)
#求平均数
def tall_num(list):num = 0for i in list:num += ireturn round(num/(len(list)+1), 2)
def num_al(list):if len(list) >= 2:num = (list[0] + list[1]) / 2else:num = list[0]return round(num, 2)
#
def show_bar_chart1(xx,cc):#拿到工资数据ll = xx#创建3个空数组average_Pay_level = []max_Pay_level = []min_Pay_level = []#循环向数组添加数据for i in ll:data = pd.DataFrame(list(db.find(i)))bb = data['wages'].valuesmax_Pay_level.append(Pay_level_list(bb)[0])average_Pay_level.append(Pay_level_list(bb)[1])min_Pay_level.append(Pay_level_list(bb)[2])show(max_Pay_level, average_Pay_level, min_Pay_level, cc)def show(a, b, c, d):name=d  #d = x轴标题（abcd个数要对应）y1 = a  # a = 最高工资列表y2 = b  #b = 平均工资列表y3 = c  #c = 最低工资x = pd.np.arange(len(name))width = 0.25plt.bar(x, y1, width=width, label='最高工资', color='red')plt.bar(x + width, y2, width=width, label='平均工资', color='green', tick_label=name)plt.bar(x + 2 * width, y3, width=width, label='最低工资', color='pink')# 显示在图形上的值for a, b in zip(x, y1):plt.text(a, b + 0.1, b, ha='center', va='bottom')for a, b in zip(x, y2):plt.text(a + width, b + 0.1, b, ha='center', va='bottom')for a, b in zip(x, y3):plt.text(a + 2 * width, b + 0.1, b, ha='center', va='bottom')plt.xticks()plt.legend(loc="upper left")  # 防止label和图像重合显示不出来plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签plt.ylabel('月/K')plt.xlabel('经验年限')plt.rcParams['savefig.dpi'] = 300  # 图片像素plt.rcParams['figure.dpi'] = 300  # 分辨率plt.rcParams['figure.figsize'] = (15.0, 8.0)  # 尺寸plt.title("工作年限工资图")plt.savefig('D:\\result.png')plt.show()