Let’s break down what’s causing your error and get your word count output in the exact format you want.

The Root Cause of the Error #

The problem hits this line of code:

sortedwords = wordcount.map(lambda x,y: (y,x)).sortByKey()

When you use map() on wordcount, each element passed to the lambda is a single tuple (like ('self', 111)), not two separate arguments. But your lambda is defined to expect two parameters (x and y), which is why you get the TypeError: <lambda>() missing 1 required positional argument: 'y' — Spark is sending one value (the tuple) but your lambda is asking for two.

The syntax error with lambda x,y : y,x happens because you forgot to wrap the return value in parentheses. Python interprets that as two separate expressions instead of a single tuple.

The Correct Lambda Syntax #

You have two reliable ways to fix this:

1. Index into the tuple (universally compatible across Python versions):
   Access the first and second elements of the tuple directly using square brackets. This is straightforward and easy to read:

   sortedwords = wordcount.map(lambda item: (item[1], item[0])).sortByKey()
   

2. Destructure the tuple in the lambda (concise, note compatibility):
   If you prefer a cleaner style, you can unpack the tuple in the lambda parameter. This works in Python 2, and in Python 3 you can adjust to unpack inside the lambda body:

   # Python 2 compatible
   sortedwords = wordcount.map(lambda (word, count): (count, word)).sortByKey()
   

   That said, the index method is safer for cross-version compatibility.

Full Corrected Code #

Here’s your complete script with the fix applied:

import re
def normalizewords(text):
    return re.compile(r'\W+', re.UNICODE).split(text.lower())

inputs = sc.textFile('Book.txt')
words = inputs.flatMap(normalizewords)
wordcount = words.map(lambda x: (x, 1)).reduceByKey(lambda x,y : x + y)
# Fixed line below
sortedwords = wordcount.map(lambda item: (item[1], item[0])).sortByKey()
sortedwords.collect()

Expected Output #

After applying the fix, sortedwords.collect() will return exactly the format you requested:

[(111, 'self'), (75, 'employment'), (33, 'building'), (178, 'an'), (26, 'internet'), (383, 'business'), (970, 'of'), (100, 'one')]

内容的提问来源于stack exchange，提问作者BetaTester