Intro to MapReduce

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Delhi Hadoop User Group MeetUp - 10th Sept. 2011 - Slides

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Intro to Map/Reduce - Somil Asthana

Agenda ,[object Object]

Map / Reduce Pipe.

Map / Reduce Computation and Cube Generation (Example),[object Object]

Works with a model where computation moves to Data rather than Data moving to Computing Machine.

Takes care of issue arises due to distributed computing.

Performs load Balancing (makes system reliable and fault tolerant).,[object Object]

Map Reduce Pipe Raw Data Mapper (Key, Value Format) Shuffle & Sort (based on Key) Reducer (For Each Key list of Values) Output (Key, Value Format)

ABC Ecommerce Company interested in analytics ,[object Object]

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Intro to MapReduce

1. Intro to Map/Reduce - Somil Asthana

2.

3. Map / Reduce Pipe.

4.

5. Works with a model where computation moves to Data rather than Data moving to Computing Machine.

6. Takes care of issue arises due to distributed computing.

7.

8. Map Reduce Pipe Raw Data Mapper (Key, Value Format) Shuffle & Sort (based on Key) Reducer (For Each Key list of Values) Output (Key, Value Format)

9.

10. The Data is in 9-tuple format: <OrderID, EmailID, MobileNum, ProductID, PayableAmount, DeliveryCharges, ModeofPayment, OrderStatus, OrderSite>

11. ModeofPayment = (COD,Credit,Check)

12. OrderStatus = (Ordered, Clicked, Verified, Rejected, Dispatched, Returned from Client, Delivered)

13.

14. Cube Generation for ABC Company Mapper Reducer

15.