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Best Practices And Optimization Of Hadoop MCQs

Practice Best Practices And Optimization Of Hadoop MCQs for competitive exams.

Best Practices And Optimization Of Hadoop MCQs

Practice questions from this topic.

What is the purpose of Hadoop's Block Placement Policy?

  1. A. Determines where to place the first replica
  2. B. Balances the number of replicas per block
  3. C. Controls block replication across the cluster
  4. D. Manages block deletion in HDFS
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How does the Hadoop Fair Scheduler allocate resources among jobs in a fair manner?

  1. A. Based on the configured weights for each job
  2. B. Based on the job's input size
  3. C. Based on the job's execution time
  4. D. Randomly assigns resources to jobs
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What is Hadoop's speculative execution policy for reducing job completion times?

  1. A. Speculatively run tasks that are likely to finish slower
  2. B. Speculatively run tasks that are likely to finish faster
  3. C. Speculatively run tasks randomly
  4. D. Do not use speculative execution
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How can the Hadoop job's input split size impact job performance?

  1. A. Larger splits can improve data locality
  2. B. Smaller splits lead to faster processing
  3. C. Split size has no impact on job performance
  4. D. Larger splits cause increased network traffic
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In Hadoop, what is the purpose of the Fair Scheduler's pool concept?

  1. A. To group jobs based on priority
  2. B. To segregate tasks based on input size
  3. C. To allocate resources based on task complexity
  4. D. To randomly assign resources to tasks
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Which Hadoop configuration property controls the maximum number of containers a node can run concurrently?

  1. A. yarn.nodemanager.resource.memory-mb
  2. B. yarn.nodemanager.container-max-heap-mb
  3. C. yarn.scheduler.maximum-allocation-mb
  4. D. yarn.scheduler.maximum-container-mb
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How can Hadoop Namenode High Availability (HA) be achieved?

  1. A. By configuring multiple active Namenodes
  2. B. By using backup Namenodes
  3. C. By replicating the Namenode metadata
  4. D. By compressing Namenode data
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What is the significance of the Hadoop Rack Awareness feature?

  1. A. Optimizes data locality by considering rack information
  2. B. Balances data across racks
  3. C. Allocates more resources to specific racks
  4. D. Randomly assigns tasks to racks
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How does Hadoop handle speculative execution at the task level?

  1. A. By running a copy of the task on another node
  2. B. By increasing the task timeout period
  3. C. By ignoring speculative execution
  4. D. By reducing the replication factor
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What is the purpose of the Hadoop CapacityScheduler?

  1. A. Ensures fair distribution of resources
  2. B. Prioritizes tasks based on input size
  3. C. Provides guaranteed capacity to specific users
  4. D. Randomly assigns resources to tasks
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How can you improve the performance of a Hadoop job by optimizing the use of Combiners?

  1. A. Increase the number of Combiners
  2. B. Decrease the number of Combiners
  3. C. Use Combiners only for map tasks
  4. D. Use Combiners for both map and reduce tasks
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Which Hadoop feature helps in fault tolerance by storing multiple copies of data across the cluster?

  1. A. Data Replication
  2. B. Speculative Execution
  3. C. Block Size
  4. D. Compression Codec
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