About vinayreddy536

vinayreddy536 · ‎06-12-2016

Thank you for your response @Timothy Spann

vinayreddy536 · ‎06-12-2016

As Spark has much more advantages over the Map-Reduce framework like in-memory processing, Faster Real-time data analysis and also it claims to process data 100x faster than MapReduce, while 10x faster with the disks. So, Will it be replacing the Map-Reduce? or will it be used paralelly?

vinayreddy536 · ‎05-23-2016

Lets assume a NameNode crashes in the HDFS HA (High Availability) setup and the Secondary/Fallback NameNode takes over, What will happen to the currently running MapReduce Jobs? Will they also fail? > Also will the secondary NameNode takes over for the failed Primary NameNode automatically or do we need any administrator to manually redirect the client requests to the Secondary NameNode? Thanks.

vinayreddy536 · ‎05-22-2016

Thank you for the response @Benjamin Leonhardi... This explains the types of Joins clearly, So does this mean that 'Distributed Cache' is only used for Broadcast join (Mapside join)?

vinayreddy536 · ‎05-21-2016

Hi All, I am new to the Hadoop and just started learning about it. While some research i have come across some concepts like Mapper & Reducer joins and Distributed Cache. > Are these joins similar to traditional database joins? > Under what scenarios/conditions these joins are used? > Also need some information regarding the "Distributed Cache" concept and exactly how this is used in Mapper & Reducer Joins. Thanks.

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Date Registered	‎05-21-2016 10:44 AM
Last Visited	‎06-12-2016 11:31 AM
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Re: Will the Spark replace the Map-Reduce in Hadoo...

Will the Spark replace the Map-Reduce in Hadoop?

Will the MapReduce jobs fail when the NameNode cra...

Re: Mapper & reducer Joins and Distributed Cache?

Mapper & reducer Joins and Distributed Cache?