4 examples of 'concat in pyspark' in Python

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6def main():
7 '''Program entry point'''
8
9 #Intialize a spark context
10 with pyspark.SparkContext("local", "PySparkWordCount") as sc:
11 #Get a RDD containing lines from this script file
12 lines = sc.textFile(__file__)
13 #Split each line into words and assign a frequency of 1 to each word
14 words = lines.flatMap(lambda line: line.split(" ")).map(lambda word: (word, 1))
15 #count the frequency for words
16 counts = words.reduceByKey(operator.add)
17 #Sort the counts in descending order based on the word frequency
18 sorted_counts = counts.sortBy(lambda x: x[1], False)
19 #Get an iterator over the counts to print a word and its frequency
20 for word,count in sorted_counts.toLocalIterator():
21 print(u"{} --> {}".format(word, count))
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250def _transform(self, dataset):
251 self._transfer_params_to_java()
252 return DataFrame(self._java_obj.transform(dataset._jdf), dataset.sql_ctx)
56def test_groupBy():
57 my_rdd = pysparkling.Context().parallelize([4, 7, 2])
58 grouped = my_rdd.groupBy(lambda x: x % 2).collect()
59 assert grouped[0][1][1] == 2
137def test_rightOuterJoin():
138 rdd1 = pysparkling.Context().parallelize([(0, 1), (1, 1)])
139 rdd2 = pysparkling.Context().parallelize([(2, 1), (1, 3)])
140 j = rdd1.rightOuterJoin(rdd2)
141 assert dict(j.collect())[1][1] == 3

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