胖子哥的大数据之路（十）- 基于Hive构建数据仓库实例

一、引言

　　基于Hive+Hadoop模式构建数据仓库，是大数据时代的一个不错的选择，本文以郑商所每日交易行情数据为案例，探讨数据Hive数据导入的操作实例。

二、源数据-每日行情数据

三、建表脚本

CREATE TABLE IF NOT EXISTS t_day_detail(

id STRING,

lastday FLOAT,

today FLOAT,

highest FLOAT,

lowest FLOAT,

today_end FLOAT,

today_jisuan FLOAT,

updown1 FLOAT,

updown2 FLOAT,

sum int,

empity int,

rise int,

turnover FLOAT,

delivery FLOAT

)

PARTITIONED BY (dt STRING,product STRING);

四、数据导入1

1 load data local inpath '/home/hadoop/source/in'

2 overwrite into table t_day_detail

3 partition(dt='2014-04-22',product='1');

五、数据导入2

1 load data local inpath '/home/hadoop/source/in'

2 overwrite into table t_day_detail

3 partition(dt='2014-04-23',product='1');

六、执行结果

hive> select * from t_day_detail

    > ;

OK

CF405,17365.0,17390.0,17390.0,17360.0,17380.0,17380.0,15,15,72.0,1090.0,-36,625.66,0.0  NULL    NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-22      1

CF407,17275.0,17370.0,17415.0,17320.0,17320.0,17365.0,45,90,22.0,52.0,2,191.01,0.0      NULL    NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-22      1

CF409,17450.0,17380.0,17395.0,17310.0,17320.0,17330.0,-130,-120,7860.0,34584.0,-940,68099.08,0.0        NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-22      1

CF411,16370.0,16315.0,16350.0,16220.0,16255.0,16240.0,-115,-130,984.0,17436.0,-380,7990.01,0.0  NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-22      1

CF501,16130.0,16030.0,16085.0,15920.0,15995.0,15970.0,-135,-160,26210.0,115120.0,-1906,209311.56,0.0    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-22      1

CF503,16195.0,16030.0,16065.0,16000.0,16065.0,16045.0,-130,-150,60.0,526.0,12,481.42,0.0        NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-22      1

CF405,17365.0,17390.0,17390.0,17360.0,17380.0,17380.0,15,15,72.0,1090.0,-36,625.66,0.0  NULL    NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-23      1

CF407,17275.0,17370.0,17415.0,17320.0,17320.0,17365.0,45,90,22.0,52.0,2,191.01,0.0      NULL    NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-23      1

CF409,17450.0,17380.0,17395.0,17310.0,17320.0,17330.0,-130,-120,7860.0,34584.0,-940,68099.08,0.0        NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-23      1

CF411,16370.0,16315.0,16350.0,16220.0,16255.0,16240.0,-115,-130,984.0,17436.0,-380,7990.01,0.0  NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-23      1

CF501,16130.0,16030.0,16085.0,15920.0,15995.0,15970.0,-135,-160,26210.0,115120.0,-1906,209311.56,0.0    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-23      1

CF503,16195.0,16030.0,16065.0,16000.0,16065.0,16045.0,-130,-150,60.0,526.0,12,481.42,0.0        NULL    NULL    NULL    NULLNULL     NULL    NULL    NULL    NULL    NULL    NULL    NULL    NULL    2014-04-23      1

Time taken: 0.391 seconds

hive> 

七、问题聚焦

（1）Hive分区设置的原则和技巧？

（2）Hive分区内行记录完全一致问题如何解决？

（3）Hive中文乱码问题如何解决？