大数据Hive学习案例(2)——基于汽车销售的日志数据分析

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原始数据

原始数据为csv格式，列数比较多

项目实战

数据仓库的构建

1.构建数据仓库

create database if not exists car;

2.创建原始数据表

use car;

create external table cars(
province string, --省份
month int, --月
city string, --市 
district string, --区县
year int, --年
model string,--车辆型号
manufacturer string,--制造商
brand string, --品牌
vehicletype string,--车辆类型
ownership string,--所有权
nature string, --使用性质
quantity int,--数量
enginemodel string,--发动机型号
displacement int,--排量
power double, --功率
fuel string,--燃料种类
length1 int,--车长
width1 int,--车宽
height1 int,--车高
length2 int,--厢长
width2 int,--厢宽
height2 int,--厢高
numberofaxles int,--轴数
wheelbase int,--轴距
frontwheelbase int,--前轮距
tirespecification string,--轮胎规格
tirenumber int,--轮胎数
totalquality int,--总质量
completequality int,--整备质量
approvedquality int,--核定载质量
approvedpassenger string,--核定载客
tractionquality int,--准牵引质量
chassisenterprise string,--底盘企业
chassisbrand string,--底盘品牌
chassismodel string,--底盘型号
engineenterprise string,--发动机企业
vehiclename string,--车辆名称
age int,--年龄
gender string --性别
)
row format delimited
fields terminated by ','
location '/cars'
tblproperties("skip.header.line.count"="1");  --跳过文件行首1行;

desc cars;

3.加载数据到数据仓库

[hadoop@hadoop000 hive_data]$ hadoop fs -put ./cars.csv /cars

4.验证数据结果

select * from cars limit 10;

数据分析

1.乘用车辆和商用车辆的销售数量和比例

select '非营运',sum(if(a.nature='非营运',a.cnt,0)),'营运',sum(if(a.nature!='非营运',a.cnt,0)) 
from 
(select nature,count(*) as cnt 
from cars group by nature having nature is not null and nature!='') a;

Total MapReduce CPU Time Spent: 6 seconds 810 msec
OK
非营运	66478	营运	3884
Time taken: 32.365 seconds, Fetched: 1 row(s)

2.山西省2013年每个月的汽车销售数量比例

select  month,c1.ss/c2.sum 
from 
(select month,sum(quantity) as ss 
from cars where province = '山西省' and year = '2013' group by month ) c1,
(select sum(quantity) as sum 
from cars where province = '山西省' and year = '2013') c2;

Total MapReduce CPU Time Spent: 9 seconds 150 msec
OK
1	0.14799181376311077
2	0.05831272561894204
3	0.09306159574770473
4	0.06587362496802251
5	0.0732071288479577
6	0.05547028225462608
7	0.06323015263920867
8	0.06378442909525028
9	0.06948352804070379
10	0.1044882180722549
11	0.10053722179585571
12	0.1045592791563628
Time taken: 53.486 seconds, Fetched: 12 row(s)

3.买车的男女比例和男女对车的品牌的选择

select '男性',B.man/(B.man+B.woman),'女性', B.woman/(B.man+B.woman) 
from
(select '男性',sum(if(A.gender='男性',A.cnt,0)) as man,'女性',sum(if(A.gender='女性',A.cnt,0)) as woman 
from
(select gender,count(*) as cnt
from cars where gender is not null and gender != '' group by gender) A) B;

Total MapReduce CPU Time Spent: 5 seconds 880 msec
OK
男性	0.7010659323952227	女性	0.29893406760477725
Time taken: 34.488 seconds, Fetched: 1 row(s)

select gender,brand,count(*) as cnt
from cars
where  gender is not null and gender != ''  and age is not null
group by gender,brand
having brand is not null and brand !=' '
order by cnt desc
limit 5;

Total MapReduce CPU Time Spent: 5 seconds 330 msec
OK
男性	五菱	28208
女性	五菱	12004
男性	长安	3679
男性	东风	3214
男性	五菱宏光	2331
Time taken: 33.615 seconds, Fetched: 5 row(s)

4.车的所有权，车辆型号，车辆类型

select a.cnt,count(*) 
from 
(select concat(model,ownership,vehicletype) as cnt from cars) a 
group by a.cnt;

ZK6726DX3单位大型专用校车	1
ZK6726DXA9单位大型专用校车	4
ZK6729D2单位大型普通客车	2
ZK6729DB单位大型普通客车	16
ZK6731DG1单位大型普通客车	6
ZK6731NG1单位大型普通客车	24
ZK6750D2单位大型普通客车	17
......

5.不同车型在一个月的销售量

select month,vehicletype,count(*) from cars group by vehicletype,month having month is not null and vehicletype is null and vehicletype != '';

6.不同品牌车销售情况，统计发动机和燃料种类

select brand,enginemodel,fuel,count(*) from cars group by brand,enginemodel,fuel;

7.统计五菱某一年每月的销售量

select brand,month,count(*) from cars group by brand,month having brand='五菱';

Total MapReduce CPU Time Spent: 3 seconds 940 msec
OK
五菱	1	5589
五菱	2	2226
五菱	3	3557
五菱	4	2389
五菱	5	3351
五菱	6	2302
五菱	7	2893
五菱	8	2980
五菱	9	3422
五菱	10	5278
五菱	11	4809
五菱	12	4963
Time taken: 16.416 seconds, Fetched: 12 row(s)