Free CCA-500 – Cloudera Certified Administrator for Apache Hadoop (CCAH) Practice Test Question

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  HMaster

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  ResourceManager

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  TaskManager

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  JobTracker

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  NameNode

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  DataNode
  

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  When Job B gets submitted, it will get assigned tasks, while job A continues to run with fewer tasks.

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  When Job B gets submitted, Job A has to finish first, before job B can gets scheduled.

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  When Job A gets submitted, it doesn’t consumes all the task slots.

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  When Job A gets submitted, it consumes all the task slots.
  

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  Standardize on a single MapReduce API

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  Single point of failure in the NameNode

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  Reduce complexity of the MapReduce APIs

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  Resource pressure on the JobTracker

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  Ability to run framework other than MapReduce, such as MPI

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  HDFS latency
  

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  To ensure that there is capacity in HDFS for additional data

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  To ensure that all blocks in the cluster are 128MB in size

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  To help HDFS deliver consistent performance under heavy loads

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  To ensure that there is consistent disk utilization across the DataNodes

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  To improve data locality MapReduce
  

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  User authentication on all remote procedure calls (RPCs)

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  Encryption for data during transfer between the Mappers and Reducers

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  Encryption for data on disk (“at rest”)

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  Authentication for user access to the cluster against a central server

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  Root access to the cluster for users hdfs and mapred but non-root access for clients
  

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  We cannot say; the number of Mappers is determined by the ResourceManager

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  We cannot say; the number of Mappers is determined by the developer

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  30

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  3

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  10

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  We cannot say; the number of mappers is determined by the ApplicationMaster
  

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  The client queries the NameNode for the locations of the block, and reads all three copies. The first copy to complete transfer to the client is the one the client reads as part of hadoop’s speculative execution framework.

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  The client queries the NameNode for the locations of the block, and reads from the first location in the list it receives.

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  The client queries the NameNode for the locations of the block, and reads from a random location in the list it receives to eliminate network I/O loads by balancing which nodes it retrieves data from any given time.

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  The client queries the NameNode which retrieves the block from the nearest DataNode to the client then passes that block back to the client.
  

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  nn02 is fenced, and nn01 becomes the active NameNode

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  nn01 is fenced, and nn02 becomes the active NameNode

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  nn01 becomes the standby NameNode and nn02 becomes the active NameNode

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  nn02 becomes the standby NameNode and nn01 becomes the active NameNode
  

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  NodeManager

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  ApplicationMaster

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  ApplicationManager

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  ResourceManager
  

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  You can specify new queue name when user submits a job and new queue can be created dynamically if the property yarn.scheduler.fair.allow-undecleared-pools = true

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  Yarn.scheduler.fair.user.fair-as-default-queue = false and yarn.scheduler.fair.allow-undecleared-pools = true

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  You can specify new queue name when user submits a job and new queue can be created dynamically if yarn .schedule.fair.user-as-default-queue = false

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  You can specify new queue name per application in allocations.xml file and have new jobs automatically assigned to the application queue