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Cascading
 

Cascading

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High level overview of Cascading.

High level overview of Cascading.

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Cascading Cascading Presentation Transcript

  • Cascading Nathan Marz BackType
  • What is Cascading? Cascading is a Java library that makes development of complex Hadoop MapReduce workflows easy
  • Why Hadoop? • Process large amounts of data in a scalable, fault-tolerant way
  • Why Cascading? Tool How you feel Hadoop MapReduce Cascading
  • Tuples Cascading represents all data as “Tuples” (“the man sat” , 25) (“hello dolly” , 42) (“say hello” ,1 ) (“the woman sat”, 10)
  • Tuples Tuples are named, ordered fields [“sentence”, “value”] (“the man sat” , 25) (“hello dolly” , 42) (“say hello” ,1 ) (“the woman sat”, 10)
  • Flow A flow is a sequence of manipulations on pipes of tuple streams • Flow compiles to one or more MapReduce jobs • Inputs and outputs called “Taps”. • Each Tap produces or receives a pipe of tuples with the same format • Multiple inputs, multiple outputs
  • Example [“sentence”, “value”] [“word”, “sum”] Get the sum of the values for each word
  • Example [“sentence”, “value”] Split(“sentence”) -> “word” [“word”, “value”] GroupBy(“word”) [“word”, list<[“value”]>] Sum(“value”) -> “sum” [“word”, “sum”]
  • Example Split(“sentence”) -> “word” [“sentence”, “value”] [“word”, “value”] (“the” , 25) (“the man sat” , 25) (“man” , 25) (“hello dolly” , 42) (“sat” , 25) (“say hello” ,1 ) (“hello” , 42) (“the woman sat”, 10) (“dolly” , 42) (“say” ,1 ) (“hello” , 1 ) (“the” , 10) (“woman” , 10) (“sat” , 10)
  • Example GroupBy(“word”) [“word”, “value”] [“word”, list<[“value”]>] (“the” , 25) (“man” , 25) (“the” , [25, 10]) (“sat” , 25) (“man” , [25] ) (“hello” , 42) (“sat” , [25, 10]) (“dolly” , 42) (“hello” , [42, 1] ) (“say” ,1 ) (“dolly” , [42] ) (“hello” , 1 ) (“say” , [1] ) (“the” , 10) (“woman” , [10] ) (“woman” , 10) (“sat” , 10)
  • Example Sum(“value”) -> “sum” [“word”, list<[“value”]>] [“word”, “sum”] (“the” , [25, 10]) (“the” , 35) (“man” , [25] ) (“man” , 25) (“sat” , [25, 10]) (“sat” , 35) (“hello” , [42, 1] ) (“hello” , 43) (“dolly” , [42] ) (“dolly” , 42) (“say” , [1] ) (“say” ,1 ) (“woman” , [10] ) (“woman” , 10)
  • More functionality • Inner and outer joins natively supported • Seamlessly branch and merge pipes of tuples • Integrate diverse data sources
  • Why not Pig? • Pig is a custom language for writing MapReduce workflows • Because it’s a custom language, intermixing “plain logic” in between flows is painful • Not nearly as flexible as Cascading for custom needs
  • Learn more • Tutorial: http://blog.rapleaf.com/dev/?p=33 • Website: http://www.cascading.org
  • Questions?