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spark:recipes:using-perl-via-pipes [2014/11/07 13:17]
straka 		spark:recipes:using-perl-via-pipes [2014/11/07 14:11]
straka
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 </file> </file>
  
-==== Complete Example using Simple Perl Tokenizer ====+==== Complete Example using Simple Perl Tokenizer and Python ====
  
 Suppose we want to write program which uses Perl Tokenizer and then produces token counts. Suppose we want to write program which uses Perl Tokenizer and then produces token counts.
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 sc = SparkContext() sc = SparkContext()
 (sc.textFile(input) (sc.textFile(input)
-   .map(json.dumps).pipe("perl tokenize.pl", os.environ).map(json.loads)+   .map(json.dumps).pipe("env perl tokenize.pl", os.environ).map(json.loads)
    .flatMap(lambda tokens: map(lambda x: (x, 1), tokens))    .flatMap(lambda tokens: map(lambda x: (x, 1), tokens))
    .reduceByKey(lambda x,y: x + y)    .reduceByKey(lambda x,y: x + y)
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 </file> </file>
  
-It can be executed using ''spark-submit --files tokenize.pl perl_integration.py input output''.+It can be executed using ''spark-submit perl_integration.py input output''.
  
 ===== Using Scala and JSON ===== ===== Using Scala and JSON =====
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 rdd.map(encodeJson).pipe("perl script.pl").map(decodeJson[ProcessedType]) rdd.map(encodeJson).pipe("perl script.pl").map(decodeJson[ProcessedType])
 </file> </file>
 +

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