在使用pyspark和nltk时，我想得到所有“np”单词的长度，并按降序排序。我现在被困在导航的子树。
子树输出示例。

# >>>[(Tree('NP', [Tree('NBAR', [('WASHINGTON', 'NN')])]), 1)

尝试获取所有np单词的长度。然后把这些长度按降序排列。
第一个元素是长度为1的单词和单词数，依此类推。

example: 

# [(1, 6157),6157 words length of one

# (2, 1833),1833 words length of 2

# (3, 654),

# (4, 204),

# (5, 65)]

import nltk
import re

textstring = """This is just a bunch of words to use for this example.  
John gave them to me last night but Kim took them to work.  
Hi Stacy. URL:http://example.com. Jessica, Mark, Tiger, Book, Crow, Airplane, SpaceShip"""

TOKEN_RE = re.compile(r"\b[\w']+\b")

grammar = r"""
    NBAR:
        {<NN.*|JJS>*<NN.*>}

    NP:
        {<NBAR>}
        {<NBAR><IN><NBAR>}
"""
chunker = nltk.RegexpParser(grammar)
text = sc.parallelize(textstring.split(' ')

dropURL=text.filter(lambda x: "URL" not in x)

words = dropURL.flatMap(lambda dropURL: dropURL.split(" "))
tree = words.flatMap(lambda words: chunker.parse(nltk.tag.pos_tag(nltk.regexp_tokenize(words, TOKEN_RE))))

# data=tree.map(lambda word: (word,len(word))).filter(lambda t : t.label() =='NBAR') -- error

# data=tree.map(lambda x: (x,len(x)))##.filter(lambda t : t[0] =='NBAR')

# >>>[(Tree('NP', [Tree('NBAR', [('WASHINGTON', 'NN')])]), 1)  Trying to get the length of all NP's and in descending order.

# data=tree.map(lambda x: (x,len(x))).reduceByKey(lambda x: x=='NBAR') ##this is an error but I am getting close I think

data=tree.map(lambda x: (x[0][0],len(x[0][0][0])))#.reduceByKey(lambda x : x[1] =='NP') ##Long run time.

things = data.collect()
things