Hadoop on Big Data Platform - Convey Tech Labs

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Hadoop On Big Data Platform
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• Introduction of Hadoop-
• Hadoop is the advanced technology with complete
  eco-system of open source which provides to deal
  with Big Data.

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Below following which deal in Big Data-

• Program query building difficulty
• Enormous time has taken
• High capital investment in procuring a server
  with high processing capacity in big data.
• If any error happens on the last step then you
  will waste of the time making these iterations.

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Hadoop Background-

• AS the immense of the usage of internet and
  people using the internet in the world, Google
  has captured the data increase year on year. For
  example, 2007 Google collected on an average 270
  PB of data every month of user data. Google ran
  these MapReduce operations on a special file
  system called Google File System (GFS) and it's
  not open source.

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Hadoop Activities performed on Big Data-

• Storage- Big Data has the huge collection of
  Data in the repository and it is not necessary to
  store in a single database.
• Processing- The process became tedious than
  traditional one in terms of cleansing,
  transforming, enriching, calculating, enriching,
  and running algorithms.
• Accessing- No Business scene without the data
  cannot be searched, retrieved easily, and data
  can be shown virtually along the business.
• Goals-
• Hardware Failure A core architectural goal of
  HDFS is a detection of faults, quick, automatic
  recovery from them.

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• Streaming Data Access To run the application
  HDFS is designed more for batch processing rather
  than interactive users data streaming.
• Large Data Sets It use designed in such a way
  to support huge files and it provides large
  aggregate data bandwidth and scale to many nodes
  in a single cluster.
• Simple Coherency Model HDFS applications need a
  one write with many model access model for
  accessing the file. A web crawler application or
  MapReduce application perfect model to data
  collecting.
• Portability Issues The HDFS has been designed to
  portable easily from one platform to another. It
  works Across Software Platforms and Heterogeneous
  Hardware.
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