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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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Top requirements for successful MapReduce jobs

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The following techniques are needed to be successful of your map reduce jobs:
  • The mapper must be able to ingest the input and process the input record, sending forward the records that can be passed to the reduce task or to the final output directly, if no reduce step is required.
Mapreduce Jobs in Hadoop
Hadoop-MapReduce
  • The reducer must be able to accept the key and value groups that passed through the mapper, and generate the final output of this MapReduce step.
  • The job must be configured with the location and type of the input data, the mapper class to use, the number of reduce tasks required, and the reducer class and I/O types.
  • The TaskTracker service will actually run your map and reduce tasks, and the JobTracker service will distribute the tasks and their input split to the various trackers.
  • The cluster must be configured with the nodes that will run the TaskTrackers, and with the number of TaskTrackers to run per node. The TaskTrackers need to be configured with the JVM parameters, including the classpath for both the TaskTracker and the JVMs that will execute the individual tasks.
  • There are three levels of configuration to address to configure MapReduce on your cluster. From the bottom up, you need to configure the machines, the Hadoop MapReduce framework, and the jobs themselves.
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AWS EC2 Real Story on Elastic Cloud Computing

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