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Tag: mapreduce metapatterns

job merging optimization to process two unrelated jobs that are loading the same data to share the mapreduce pipeline

June, 2017 adarsh

job merging is an optimization aimed to reduce the amount of I/O through the MapReduce pipeline. Job merging is a…

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Posted in: Data Analytics, Map Reduce Filed under: map reduce, map reduce design pattern, mapreduce metapatterns

Chain folding optimization in mapreduce using chainmapper and chainreducer approach

adarsh

Chain folding is an optimization that is applied to MapReduce job chains.Take a look at the map phases in the…

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Posted in: Data Analytics, Map Reduce Filed under: map reduce, map reduce design pattern, mapreduce metapatterns

job chaining in mapreduce with jobcontrol ,controlledJob and driver

June, 2017 adarsh

Job chaining is extremely important to understand and have an operational plan for in your environment. Many people find that…

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Posted in: Data Analytics, Map Reduce Filed under: map reduce, map reduce design pattern, mapreduce metapatterns

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