Map reduce with big data

1. MapReduce with Big Data
Jagriti Srivastava

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Tools

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Large volume of data – structured and unstructured
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It’s what organizations do with the data that matters.
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Helps for better decisions and strategic business moves.
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Map Reduce for big data scenario :
– Data of total social media sign up from different countries.
– Listing of those data using Map Reduce technique.
– Search engines could determine page views, and marketers
could perform sentiment analysis using MapReduce.
Big Data with Map Reduce

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MapReduce Implementation
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At Google:
– Index building for Google Search
– – Article clustering for Google News
– Statistical machine translation
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At Yahoo!:
– Index building for Yahoo! Search
– Spam detection for Yahoo! Mail
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At Facebook:
– Data mining
– Ad optimization
– Spam detection Example
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At Amazon:
– Product clustering
– Statistical machine translation

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Why MapReduce in BigData
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Responsible for delegating work to the different nodes in the cluster/map
and
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Collects all the results from the query into one cohesive answer.
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Components of MapReduce :
– JobTracker (the master node),
– TaskTrackers (these are agents within each cluster, with functions of their own) and
– JobHistoryServer (deployed as separate function, but a component that tracks jobs.

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