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AWS EC2 Real Story on Elastic Cloud Computing

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The short name for Amazon Elastic Computing Cloud is EC2. You can keep this point as an interview question. The computing capacity has an elastic property. Based on your requirement you can increase or decrease computing power.
You need to be very attentive when you enable Auto scaling feature. It is a responsibility on Admins. Amazon AWS EC2Making your existing hardware to the requirement, always is not so easy. So the EC2 feature in AWS helps you to allocate computing power according to your needs. AWS EC2 instance acts as your physical server.It has memory.You can increase the instance size in terms of CPU, Memory, Storage and GPU.EC2 auto scaling is a property, where it automatically increase your computing power. List of Top Security Features in EC2  1#. Virtual Private CloudThe responsibility of Virtual Private Cloud, is to safeguard each instance separately. That means, you cannot access others instance, which is already created by other organization.
2#. Network Access Control L…
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Apache Yarn to Manage Resources a Solution

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Apache Hadoop is one of the most popular tools for big data processing. It has been successfully deployed in production by many companies for several years. 

Though Hadoop is considered a reliable, scalable, and cost-effective solution, it is constantly being improved by a large community of developers. As a result, the 2.0 version offers several revolutionary features, including Yet Another Resource Negotiator (YARN), HDFS Federation, and a highly available NameNode, which make the Hadoop cluster much more efficient, powerful, and reliable. 

Apache Yarn

Apache Hadoop 2.0 includes YARN, which separates the resource management and processing components. The YARN-based architecture is not constrained to MapReduce.
  • New developmens in Hadoop 2.0 Architecture with YARN: 
  • ResourceManager instead of a cluster manager 
  • ApplicationMaster instead of a dedicated and short-lived JobTracker 
  • NodeManager instead of TaskTracker 
  • A distributed application instead of a MapReduce job 

Basic changes in Hadoop 2.0 architecture

  • The ResourceManager, the NodeManager, and a container are not concerned about the type of application or task.
  • All application framework-specific code is simply moved to its ApplicationMaster so that any distributed framework can be supported by YARN — as long as someone implements an appropriate ApplicationMaster for it.
  • Thanks to this generic approach, the dream of a Hadoop YARN cluster running many various workloads comes true. Imagine: a single Hadoop cluster in your data center that can run MapReduce, Giraph, Storm, Spark, Tez/Impala, MPI, and more.

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AWS EC2 Real Story on Elastic Cloud Computing

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The short name for Amazon Elastic Computing Cloud is EC2. You can keep this point as an interview question. The computing capacity has an elastic property. Based on your requirement you can increase or decrease computing power.
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Python Syntax Rules Eliminate Errors Before you start debugging

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Python Improved Logic Easy Way to Calculate Factorial

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