hive原生和复合型数据的示例分析

这篇文章主要介绍hive原生和复合型数据的示例分析，文中介绍的非常详细，具有一定的参考价值，感兴趣的小伙伴们一定要看完！

原生类型

原生类型包括TINYINT,SMALLINT,INT,BIGINT,BOOLEAN,FLOAT,DOUBLE,STRING,BINARY (Hive 0.8.0以上才可用),TIMESTAMP (Hive 0.8.0以上才可用)，这些数据加载很容易，只要设置好列分隔符，按照列分隔符输出到文件就可以了。

假设有这么一张用户登陆表

CREATE TABLE login (    uid  BIGINT,    ip  STRING  )  ROW FORMAT DELIMITED  FIELDS TERMINATED BY ','  STORED AS TEXTFILE;

这表示登陆表ip字段和uid字段以分隔符','隔开。

输出hive表对应的数据

# printf "%s,%s\n" 3105007001 192.168.1.1 >> login.txt  # printf "%s,%s\n" 3105007002 192.168.1.2 >> login.txt

login.txt的内容:

#cat login.txt                                                                                                                        3105007001,192.168.1.13105007002,192.168.1.2

加载数据到hive表

LOAD DATA LOCAL INPATH '/home/hadoop/login.txt' OVERWRITE INTO TABLE login PARTITION (dt='20130101');

查看数据

select uid,ip from login where dt='20130101';3105007001    192.168.1.13105007002    192.168.1.2

array

假设登陆表是

CREATE TABLE login_array (  ip  STRING,  uid  array)PARTITIONED BY (dt STRING)ROW FORMAT DELIMITEDFIELDS TERMINATED BY ','COLLECTION ITEMS TERMINATED BY '|'STORED AS TEXTFILE;

这表示登陆表每个ip有多个用户登陆，ip和uid字段之间使用','隔开，而uid数组之间的元素以'|'隔开。

输出hive表对应的数据

# printf "%s,%s|%s|%s\n" 192.168.1.1 3105007010 3105007011 3105007012 >> login_array.txt# printf "%s,%s|%s|%s\n" 192.168.1.2  3105007020 3105007021 3105007022 >> login_array.txt

login_array.txt的内容:

cat login_array.txt                                                                                                                   192.168.1.1,3105007010|3105007011|3105007012192.168.1.2,3105007020|3105007021|3105007022

加载数据到hive表

LOAD DATA LOCAL INPATH '/home/hadoop/login_array.txt' OVERWRITE INTO TABLE login_array PARTITION (dt='20130101');

查看数据

select ip,uid from login_array where dt='20130101';192.168.1.1    [3105007010,3105007011,3105007012]192.168.1.2    [3105007020,3105007021,3105007022]

使用数组

select ip,uid[0] from login_array where dt='20130101'; --使用下标访问数组select ip,size(uid) from login_array where dt='20130101'; #查看数组长度select ip from login_array where dt='20130101'  where array_contains(uid,'3105007011');#数组查找

更多操作参考 https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-CollectionFunctions

map

假设登陆表是

CREATE TABLE login_map (  ip  STRING,  uid  STRING,  gameinfo map)PARTITIONED BY (dt STRING)ROW FORMAT DELIMITEDFIELDS TERMINATED BY ','COLLECTION ITEMS TERMINATED BY '|'MAP KEYS TERMINATED BY ':'STORED AS TEXTFILE;

这表示登陆表每个用户都会有游戏信息，而用户的游戏信息有多个，key是游戏名，value是游戏的积分。map中的key和value以'':"分隔，map的元素以'|'分隔。

输出hive表对应的数据

# printf "%s,%s,%s:%s|%s:%s|%s:%s\n" 192.168.1.1  3105007010 wow 10 cf 1 qqgame 2  >> login_map.txt# printf "%s,%s,%s:%s|%s:%s|%s:%s\n" 192.168.1.2  3105007012 wow 20 cf 21 qqgame 22  >> login_map.txt

login_map.txt的内容:

# cat login_map.txt192.168.1.1,3105007010,wow:10|cf:1|qqgame:2192.168.1.2,3105007012,wow:20|cf:21|qqgame:22

加载数据到hive表

LOAD DATA LOCAL INPATH '/home/hadoop/login_map.txt' OVERWRITE INTO TABLE login_map PARTITION (dt='20130101');

查看数据

select ip,uid,gameinfo from login_map where dt='20130101';192.168.1.1    3105007010    {"wow":10,"cf":1,"qqgame":2}192.168.1.2    3105007012    {"wow":20,"cf":21,"qqgame":22}

使用map

select ip,uid,gameinfo['wow'] from login_map where dt='20130101'; --使用下标访问mapselect ip,uid,size(gameinfo) from login_map where dt='20130101'; #查看map长度select ip,uid from login_map where dt='20130101'  where array_contains(map_keys(gameinfo),'wow');#查看map的key，找出有玩wow游戏的记录

更多操作参考 https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-CollectionFunctions

struct

假设登陆表是

CREATE TABLE login_struct (  ip  STRING,  user  struct)PARTITIONED BY (dt STRING)ROW FORMAT DELIMITEDFIELDS TERMINATED BY ','COLLECTION ITEMS TERMINATED BY '|'MAP KEYS TERMINATED BY ':'STORED AS TEXTFILE;

user是一个struct,分别包含用户uid和用户名。

输出hive表对应的数据

printf "%s,%s|%s|\n" 192.168.1.1  3105007010 blue  >> login_struct.txtprintf "%s,%s|%s|\n" 192.168.1.2  3105007012 ggjucheng  >> login_struct.txt

login_struct.txt的内容:

# cat login_struct.txt192.168.1.1,3105007010|blue192.168.1.2,3105007012|ggjucheng

加载数据到hive表

LOAD DATA LOCAL INPATH '/home/hadoop/login_struct.txt' OVERWRITE INTO TABLE login_struct PARTITION (dt='20130101');

查看数据

select ip,user from login_struct where dt='20130101';192.168.1.1    {"uid":3105007010,"name":"blue"}192.168.1.2    {"uid":3105007012,"name":"ggjucheng"}

使用struct

select ip,user.uid,user.name from login_map where dt='20130101';

union

用的比较少，暂时不讲

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