Lateral View用法 与 Hive UDTF explode

Lateral View是Hive中提供给UDTF的conjunction，它能够解决UDTF不能添加额外的select列的问题。

1. Why we need Lateral View？
当咱们想对hive表中某一列进行split以后，想对其转换成1 to N的模式，即一行转多列。
hive不容许咱们在UDTF函数以外，再添加其它select语句。
以下，咱们想将登陆某个游戏的用户id放在一个字段user_ids里，对每一行数据用UDTF后输出多行。

select game_id, explode(split(user_ids,'\\[\\[\\[')) as user_id   
from login_game_log  
where dt='2014-05-15' 

FAILED: Error in semantic analysis:
UDTF's are not supported outside the SELECT clause, nor nested in expressions。

提示语法分析错误，UDTF不支持函数以外的select 语句，真无语。。。
若是咱们想支持怎么办呢？接下来就是Lateral View 登场的时候了。

2. Lateral View explain
2.1 单个Lateral View
Lateral view is used in conjunction with user-defined table generatingfunctions such as explode(). As mentioned in Built-in Table-Generating Functions, a UDTF generates zero or more output rows foreach input row. A lateral view first applies the UDTF to each row of base tableand then joins resulting output rows to the input rows to form a virtual tablehaving the supplied table alias.

解释一下：
Lateral view 其实就是用来和像相似explode这种UDTF函数联用的。lateral view 会将UDTF生成的结果放到一个虚拟表中，而后这个虚拟表会和输入行即每一个game_id进行join 来达到链接UDTF外的select字段的目的。

Lateral View Syntax

lateralView: LATERAL VIEW udtf(expression) tableAlias AS columnAlias (',' columnAlias)*
fromClause: FROM baseTable (lateralView)*

1. 在udtf前面用能够看出，能够在2个地方用Lateral view：
2. 在from baseTable后面用

举个例子：
1. 先建立一个文件，里面2列用\t分割，game_id和user_ids;

hive> create table test_lateral_view_shengli(game_id string,userl_ids string) 
      row format delimited 
      fields terminated by '\t' 
      stored as textfile;  
OK  
Time taken: 2.451 seconds  
hive> load data local inpath '/home/hadoop/test_lateral' into table test_lateral_view_shengli;  
Copying data from file:/home/hadoop/test_lateral  
Copying file: file:/home/hadoop/test_lateral  
Loading data to table dw.test_lateral_view_shengli  
OK  
Time taken: 6.716 seconds;
  
hive> select * from test_lateral_view_shengli;                                                                                                             
OK  
game101       15358083654[[[ab33787873[[[zjy18052480603[[[shlg1881826[[[lxqab110  
game66        winning1ren[[[13810537508  
game101       hu330602003[[[hu330602004[[[hu330602005[[[15967506560

下面使用lateral_view

hive> select game_id, user_id    
    > from test_lateral_view_shengli 
    > lateral view explode(split(userl_ids,'\\[\\[\\[')) snTable as user_id   
    > ;  
Total MapReduce jobs = 1  
Launching Job 1 out of 1  
Number of reduce tasks is set to 0 since there's no reduce operator  
Starting Job = job_201403301416_445839, Tracking URL = http://10.1.9.10:50030/jobdetails.jsp?jobid=job_201403301416_445839  
Kill Command = /app/home/hadoop/src/hadoop-0.20.2-cdh3u5/bin/../bin/hadoop job  -Dmapred.job.tracker=10.1.9.10:9001 -kill job_201403301416_445839  
2014-05-16 17:39:19,108 Stage-1 map = 0%,  reduce = 0%  
2014-05-16 17:39:28,157 Stage-1 map = 100%,  reduce = 0%  
2014-05-16 17:39:38,830 Stage-1 map = 100%,  reduce = 100%  
Ended Job = job_201403301416_445839  
OK  

game101       hu330602003  
game101       hu330602004  
game101       hu330602005  
game101       15967506560  
game101       15358083654  
game101       ab33787873  
game101       zjy18052480603  
game101       shlg1881826  
game101       lxqab110  
game66        winning1ren  
game66        13810537508

2.2 多个Lateral View
From语句后能够跟多个Lateral View。
A FROM clause can have multiple LATERAL VIEW clauses. Subsequent LATERAL VIEWS can reference columns from any of the tables appearing to the left of the LATERAL VIEW.
给定数据：

Array<int> col1	Array<string> col2
[1, 2]	[a", "b", "c"]
[3, 4]	[d", "e", "f"]

转换目标：
想同时把第一列和第二列拆开，相似作笛卡尔乘积。

int myCol1	string myCol2
1	"a"
1	"b"
1	"c"
2	"a"
2	"b"
2	"c"
3	"d"
3	"e"
3	"f"
4	"d"
4	"e"
4	"f"

 

 

 

 

 

 

 

 

 

 

 

咱们能够这样写：

SELECT myCol1, myCol2 FROM baseTable  
LATERAL VIEW explode(col1) myTable1 AS myCol1  
LATERAL VIEW explode(col2) myTable2 AS myCol2;

3. Outer Lateral View

还有一种状况，若是UDTF转换的Array是空的怎么办呢？
在Hive0.12里面会支持outer关键字，若是UDTF的结果是空，默认会被忽略输出。
若是加上outer关键字，则会像left outer join 同样，仍是会输出select出的列，而UDTF的输出结果是NULL。

hive> select * FROM test_lateral_view_shengli LATERAL VIEW explode(array()) C AS a ;

结果是什么都不输出。
若是加上outer关键字：

SELECT * FROM src LATERAL VIEW OUTER explode(array()) C AS a limit 10;

238 val_238 NULL
86  val_86  NULL
311 val_311 NULL
27  val_27  NULL
165 val_165 NULL
409 val_409 NULL
255 val_255 NULL
278 val_278 NULL
98  val_98  NULL
...

4.总结：

Lateral View一般和UDTF一块儿出现，为了解决UDTF不容许在select字段的问题。 Multiple Lateral View能够实现相似笛卡尔乘积。 Outer关键字能够把不输出的UDTF的空结果，输出成NULL，防止丢失数据。 原创文章，转载请注明出自：http://blog.csdn.net/oopsoom/article/details/26001307