Github user HyukjinKwon commented on a diff in the pull request: https://github.com/apache/spark/pull/14830#discussion_r101257317 --- Diff: examples/src/main/python/streaming/network_wordjoinsentiments.py --- @@ -54,22 +54,25 @@ def print_happiest_words(rdd): # Read in the word-sentiment list and create a static RDD from it word_sentiments_file_path = "data/streaming/AFINN-111.txt" - word_sentiments = ssc.sparkContext.textFile(word_sentiments_file_path) \ - .map(lambda line: tuple(line.split("\t"))) + word_sentiments = (ssc.sparkContext + .textFile(word_sentiments_file_path) + .map(lambda line: tuple(line.split("\t")))) lines = ssc.socketTextStream(sys.argv[1], int(sys.argv[2])) - word_counts = lines.flatMap(lambda line: line.split(" ")) \ - .map(lambda word: (word, 1)) \ - .reduceByKey(lambda a, b: a + b) + word_counts = (lines + .flatMap(lambda line: line.split(" ")) + .map(lambda word: (word, 1)) + .reduceByKey(lambda a, b: a + b)) # Determine the words with the highest sentiment values by joining the streaming RDD # with the static RDD inside the transform() method and then multiplying # the frequency of the words by its sentiment value - happiest_words = word_counts.transform(lambda rdd: word_sentiments.join(rdd)) \ - .map(lambda word_tuples: (word_tuples[0], float(word_tuples[1][0]) * word_tuples[1][1])) \ - .map(lambda word_happiness: (word_happiness[1], word_happiness[0])) \ - .transform(lambda rdd: rdd.sortByKey(False)) + happiest_words = (word_counts + .map(lambda word_tuples: (word_tuples[0], + float(word_tuples[1][0]) * word_tuples[1][1])) --- End diff -- multiline lines in `lambda`? Is this really recommanded in pep8?
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