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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.

How does Hadoop handle node failures in a cluster?

  1. A. By replicating data across multiple nodes
  2. B. By increasing the block size of HDFS
  3. C. By compressing data in HDFS
  4. D. By decreasing the replication factor
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What is the role of the Fair Scheduler in Hadoop?

  1. A. Ensures fair distribution of resources
  2. B. Prioritizes tasks based on input size
  3. C. Allocates resources based on task complexity
  4. D. Randomly assigns resources to tasks
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What is the purpose of Hadoop's speculative execution feature?

  1. A. To handle speculative workloads
  2. B. To minimize resource usage
  3. C. To mitigate the impact of slow-running tasks
  4. D. To speed up task completion
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How can you optimize the performance of a Hadoop cluster when dealing with small files?

  1. A. Use Hadoop Archive (HAR) files
  2. B. Increase the block size of HDFS
  3. C. Decrease the replication factor of small files
  4. D. Merge small files into larger ones
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What is the purpose of the Hadoop speculative execution?

  1. A. To handle speculative workloads
  2. B. To minimize resource usage
  3. C. To mitigate the impact of slow-running tasks
  4. D. To speed up task completion
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Which parameter in Hadoop configuration controls the maximum number of attempts for task execution?

  1. A. mapreduce.task.max-attempts
  2. B. mapreduce.task.attempt.max
  3. C. mapreduce.task.max-retries
  4. D. mapreduce.task.retry.max
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How can the Hadoop block size affect job performance?

  1. A. Larger blocks can improve data locality
  2. B. Smaller blocks lead to faster processing
  3. C. Block size has no impact on job performance
  4. D. Larger blocks cause increased network traffic
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What is the purpose of the Hadoop balancer tool?

  1. A. To balance the load across Hadoop nodes
  2. B. To optimize Hadoop's network performance
  3. C. To allocate more resources to specific nodes
  4. D. To compress data in HDFS
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What is speculative execution in Hadoop, and when is it triggered?

  1. A. Executing tasks simultaneously on multiple nodes
  2. B. Re-executing a task when it fails
  3. C. Executing a task multiple times in parallel
  4. D. Running a task on a random node
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Which Hadoop component is responsible for resource negotiation between the client and the Hadoop cluster?

  1. A. ResourceManager
  2. B. NameNode
  3. C. JobTracker
  4. D. DataNode
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What is the purpose of the Hadoop Distributed Cache?

  1. A. To cache frequently used HDFS data
  2. B. To cache frequently used MapReduce code
  3. C. To cache frequently used input data
  4. D. To cache intermediate MapReduce results
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How can data skew in a Hadoop job be addressed for optimization?

  1. A. Increase the number of reducers
  2. B. Decrease the number of reducers
  3. C. Use a combiner function
  4. D. Use a custom partitioner
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