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spark:spark-introduction [2022/12/14 12:29]
straka [Running Spark Shell in Python] 		spark:spark-introduction [2022/12/14 12:34]
straka [Word Count Example]
Line 27: Line 27:
 We start by simple word count example. We load the RDD from text file, every line of the input file becoming an element of RDD. We then split every line into words, count every word occurrence and sort the words by the occurrences. Copy the following to the opened Python shell: We start by simple word count example. We load the RDD from text file, every line of the input file becoming an element of RDD. We then split every line into words, count every word occurrence and sort the words by the occurrences. Copy the following to the opened Python shell:
 <file python> <file python>
-wiki = sc.textFile("/net/projects/spark-example-data/wiki-cs")+wiki = sc.textFile("/lnet/troja/data/npfl118/wiki/cs/wiki.txt")
 words = wiki.flatMap(lambda line: line.split()) words = wiki.flatMap(lambda line: line.split())
-counts = words.map(lambda word: (word, 1)).reduceByKey(lambda c1,c2: c1+c2) +counts = words.map(lambda word: (word, 1)).reduceByKey(lambda c1, c2: c1+c2) 
-sorted = counts.sortBy(lambda (word,count): count, ascending=False) +sorted = counts.sortBy(lambda word_count: word_count[1], ascending=False) 
-sorted.saveAsTextFile('output')+sorted.saveAsTextFile("output")
  
 # Alternatively, we can avoid variables: # Alternatively, we can avoid variables:
-(sc.textFile("/net/projects/spark-example-data/wiki-cs")+(sc.textFile("/lnet/troja/data/npfl118/wiki/cs/wiki.txt")
    .flatMap(lambda line: line.split())    .flatMap(lambda line: line.split())
    .map(lambda word: (word, 1))    .map(lambda word: (word, 1))
-   .reduceByKey(lambda c1,c2: c1+c2) +   .reduceByKey(lambda c1, c2: c1+c2) 
-   .sortBy(lambda (word,count): count, ascending=False)+   .sortBy(lambda word_count: word_count[1], ascending=False)
    .take(10)) # Instead of saveAsTextFile, we only print 10 most frequent words    .take(10)) # Instead of saveAsTextFile, we only print 10 most frequent words
 </file> </file>

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