问题描述
让我解释一下这个问题。我有这样的代码行: u = FOREACH人将GENERATE FLATTEN($ 0#'experience')作为j;
转储u;
产生这个输出:
<$ p $ ($#c#),($#$,$#$,$#$,$# b $ b([id#1,date_begin#12 2011,description#blabla3,date_end#04 2012],[id#2,date_begin#02 2010,description#blabla4,date_end#04 2011])$ b $ b
然后,当我这样做时:
p = foreach u生成j#'id',j#'description';
转储p;
我有这样的输出:
(1,blabla)
(1,blabla3)
但那不是我想要的。我想要一个这样的输出:
$ p $ (1,blabla)
(2,blabla2)
(1,blabla3)
(2,blabla4)
我怎么能拥有这个
非常感谢。 我假设
$ b $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $' b
总体问题是 j
仅引用元组中的第一个映射。为了得到你想要的输出,你必须将每个元组转换成一个包,然后 FLATTEN
它。
如果你知道每个元组最多有两个映射,你可以这样做:
- 我的B是你的
B = FOREACH一个GENERATE(元组(map [],map []))$ 0#'experience'AS T;
B2 = FOREACH B GENERATE FLATTEN(TOBAG(T. $ 0,T. $ 1))AS j;
C = foreach B2生成j#'id',j#'description';
如果你不知道元组中有多少个字段,那么这将是很多。
注意:
对于映射数量未定的元组,我能想到的最佳答案是使用UDF来解析字节数组:
myudf.py
@outputSchema('vals:{(val:map [])}')
def foo(the_input):
#这会将不确定数量的地图转换为包。
foo = [chr(i)for the in_input]
foo =''.join(foo).strip('()')
out = []
for f in foo.split('],['):
f = f.strip('[]')
out.append(dict((k,v)for k,v in [i。 (',')]))
返回
myscript.pig
使用jython作为myudf注册'myudf.py';
B = FOREACH A GENERATE FLATTEN($ 0#'experience');
T1 = FOREACH B GENERATE FLATTEN(myudf.foo($ 0))AS M;
T2 = FOREACH T1 GENERATE M#'id',M#'description';
然而,这依赖于#
,,
或],[
不会出现在地图中的任何键或值中。 p>
注意:适用于0.11猪。
$ b $因此,似乎猪在这种情况下如何处理python UDF的输入。字节阵列不是输入到 foo
的字节阵列,而是自动转换为适当的类型。在这种情况下,它使一切变得容易:
myudf.py
<$ p $ ($ val $:{val:map [])}')
def foo(the_input):
#这会将不确定的地图数量转换为一个包。
out = []
for the_input中的地图:
out.append(map)
返回
myscript.pig
register'myudf。 py'使用jython作为myudf;
#这次你应该传入整个元组。
B = FOREACH A GENERATE $ 0#'experience';
T1 = FOREACH B GENERATE FLATTEN(myudf.foo($ 0))AS M;
T2 = FOREACH T1 GENERATE M#'id',M#'description';
Let me explain the problem. I have this line of code:
u = FOREACH persons GENERATE FLATTEN($0#'experiences') as j;
dump u;
which produces this output:
([id#1,date_begin#12 2012,description#blabla,date_end#04 2013],[id#2,date_begin#02 2011,description#blabla2,date_end#04 2013])
([id#1,date_begin#12 2011,description#blabla3,date_end#04 2012],[id#2,date_begin#02 2010,description#blabla4,date_end#04 2011])
Then, when I do this:
p = foreach u generate j#'id', j#'description';
dump p;
I have this output:
(1,blabla)
(1,blabla3)
But that's not what I wanted. I would like to have an output like this:
(1,blabla)
(2,blabla2)
(1,blabla3)
(2,blabla4)
How could I have this ?
Thank you very much.
I'm assuming that the $0 you are FLATTEN
ing in u
is a tuple.
The overall problem is that j
is only referencing the first map in the tuple. In order to get the output you want, you'll have to convert each tuple into a bag, then FLATTEN
it.
If you know that each tuple will have up to two maps, you can do:
-- My B is your u
B = FOREACH A GENERATE (tuple(map[],map[]))$0#'experiences' AS T ;
B2 = FOREACH B GENERATE FLATTEN(TOBAG(T.$0, T.$1)) AS j ;
C = foreach B2 generate j#'id', j#'description' ;
If you don't know how many fields will be in the tuple, then this is will be much harder.
NOTE: This works for pig 0.10.
For tuples with an undefined number of maps, the best answer I can think of is using a UDF to parse the bytearray:
myudf.py
@outputSchema('vals: {(val:map[])}')
def foo(the_input):
# This converts the indeterminate number of maps into a bag.
foo = [chr(i) for i in the_input]
foo = ''.join(foo).strip('()')
out = []
for f in foo.split('],['):
f = f.strip('[]')
out.append(dict((k, v) for k, v in [ i.split('#') for i in f.split(',')]))
return out
myscript.pig
register 'myudf.py' using jython as myudf ;
B = FOREACH A GENERATE FLATTEN($0#'experiences') ;
T1 = FOREACH B GENERATE FLATTEN(myudf.foo($0)) AS M ;
T2 = FOREACH T1 GENERATE M#'id', M#'description' ;
However, this relies on the fact that #
, ,
, or ],[
will not appear in any of the keys or values in the map.
NOTE: This works for pig 0.11.
So it seems that how pig handles the input to the python UDFs changed in this case. Instead of a bytearray being the input to foo
, the bytearray is automatically converted to the appropriate type. In that case it makes everything much easier:
myudf.py
@outputSchema('vals: {(val:map[])}')
def foo(the_input):
# This converts the indeterminate number of maps into a bag.
out = []
for map in the_input:
out.append(map)
return out
myscript.pig
register 'myudf.py' using jython as myudf ;
# This time you should pass in the entire tuple.
B = FOREACH A GENERATE $0#'experiences' ;
T1 = FOREACH B GENERATE FLATTEN(myudf.foo($0)) AS M ;
T2 = FOREACH T1 GENERATE M#'id', M#'description' ;
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