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Hadoop Online Training Classes With Real Time Support From India - Panaji

buysellify.com 22/9/2016 05:05 PM   ||   buysellify.com Panaji, Goa, India
Type : Coaching Class
Hadoop Online Training
KITS Online Trainings understand the need for a quality training curriculum along with real-time implementation exposure as it forms the very essence of your future career in Hadoop. Our well-structured online training course in Hadoop extensively covers all the core aspects of Hadoop with an emphasis on live scenarios. Users get the complete flexibility in choosing their batch timings from weekend or weekday slots. Access to expert trainers and instructor led training sessions ensure that you can easily clear your doubts and get the exact guidance that is expected from a classroom training session.

Please open below link for complete course content
http://kitsonlinetrainings.com/hadoop-online-training.html

Hadoop Course Content
Introduction to Hadoop
Introduction to Bigdata
Hadoop Distributed File System
The Hadoop Online Training Distributed File System
Map Reduce
Map / Reduce Programming-Java Programming
NOSQL
HBase
Hive
Pig
SQOOP
HCATALOG
FLUME
More Ecosystem
Oozie
SPARK

The Advantage you get with KITS Online Hadoop Course:

1) Distribute data and computation.The computation local to data prevents the network overload.
2) Tasks are independent The task are independent so,
We can easy to handle partial failure. Here the entire nodes can fail and restart.
it avoids crawling horrors of failure and tolerant synchronous distributed systems.
Speculative execution to work around stragglers.
3) Linear scaling in the ideal case.It used to design for cheap, commodity hardware.
4) Simple programming model.The end-user programmer only writes map-reduce tasks.
6) HDFS store large amount of information
7) HDFS is simple and robust coherency model
8 ) That is it should store data reliably.
9) HDFS is scalable and fast access to this information and it also possible to serve s large number of clients by simply adding more machines to the cluster.
10) HDFS should integrate well with Hadoop MapReduce, allowing data to be read and computed upon locally when possible.
11) HDFS provide streaming read performance.
12) Data will be written to the HDFS once and then read several times.
13) The overhead of cashing is helps the data should simply be re-read from HDFS source.
14) Fault tolerance by detecting faults and applying quick, automatic recovery

Please contact for more details

KITS Online Technologies
India Ph : +91 9959766329
+91 8374387485
Mail : kitsonlinetraining@gmail.com
Website : www.kitsonlinetrainings.com

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