MCQs

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Overall MCQs for Reference

Which core architectural model does MapReduce follow?
a. Peer-to-peer
b. Master–slave
c. Client–server
d. Bus
Answer: b. Master–slavegeeksforgeeks
What is the primary role of the Client in MapReduce architecture?
a. Execute compute tasks
b. Submit the job to the system
c. Store output data
d. Manage data locality
Answer: b. Submit the job to the systemgeeksforgeeks
In MapReduce, what divides a job into smaller tasks?
a. Task Tracker
b. Job Tracker
c. Client
d. Reducer
Answer: b. Job Trackergeeksforgeeks
What process does the Map phase perform?
a. Data aggregation
b. Input data splitting and processing
c. Data shuffling
d. Sorting keys
Answer: b. Input data splitting and processinggeeksforgeeks
Which phase immediately follows the Map phase in MapReduce?
a. Input
b. Shuffle & Sort
c. Output
d. Data Load
Answer: b. Shuffle & Sortgeeksforgeeks
What is the function of the Reducer in MapReduce?
a. Store input data
b. Aggregate and process results
c. Divide job into tasks
d. Track task execution
Answer: b. Aggregate and process resultseasyexamnotes+1
What is the MapReduce responsible for in Hadoop?
a. Coordinating storage
b. Batch data processing
c. Scheduling network traffic
d. Executing machine learning only
Answer: b. Batch data processingscribd+1
Where is the final output from the Reduce phase written?
a. Local disk
b. Job Tracker
c. HDFS
d. Mapper output
Answer: c. HDFSgeeksforgeeks
What ensures tasks are executed near the data in Hadoop MapReduce?
a. Data replication
b. Data locality
c. Load balancing
d. Pipeline execution
Answer: b. Data localitygeeksforgeeks
Which of the following best describes shuffle in MapReduce?
a. Grouping values by key
b. Sorting values by output
c. Mapping values to inputs
d. Aggregating data into blocks
Answer: a. Grouping values by keygeeksforgeeks
What happens during the sort step after the Map phase?
a. Aggregates values
b. Orders keys
c. Discards duplicates
d. Combines inputs
Answer: b. Orders keysgeeksforgeeks
What is speculative execution in MapReduce?
a. Redundant task launch for performance
b. Task reassignment for failure
c. Aggregating key-value pairs
d. Load balancing across nodes
Answer: a. Redundant task launch for performancegeeksforgeeks
Which component coordinates job tasks in MapReduce?
a. Job Tracker
b. Client
c. DataNode
d. Replication Manager
Answer: a. Job Trackergeeksforgeeks
Why is fault tolerance crucial in MapReduce?
a. Ensures single point execution
b. Handles task/node failure automatically
c. Reduces output volume
d. Avoids data storage
Answer: b. Handles task/node failure automaticallycloudfoundation+1
How are tasks assigned in MapReduce to maximize efficiency?
a. Random allocation
b. Data locality-aware scheduling
c. FIFO scheduling
d. Manual assignment
Answer: b. Data locality-aware schedulingstudocu+1
What is the purpose of the RecordReader in MapReduce?
a. Splits input into key-value pairs
b. Stores final output
c. Assigns tasks
d. Tracks speculative execution
Answer: a. Splits input into key-value pairsgeeksforgeeks
Which part of MapReduce writes the output data?
a. Map Task
b. Client
c. Reduce Task
d. Job Tracker
Answer: c. Reduce Taskgeeksforgeeks
What is meant by pipeline execution in MapReduce?
a. Preprocessing before mapping
b. Multiple tasks run concurrently
c. Chaining reducers
d. Parallel data transfer
Answer: b. Multiple tasks run concurrentlygeeksforgeeks
When is a Combiner most useful in MapReduce?
a. After shuffling
b. To reduce data transferred to reducer
c. Before sorting
d. At output writing
Answer: b. To reduce data transferred to reducercloudfoundation
Which phase aggregates key-value pairs by key?
a. Map
b. Shuffle
c. Reduce
d. Split
Answer: c. Reducecloudfoundation+1
What is a Task Tracker?
a. Tracks job submission
b. Executes assigned tasks on nodes
c. Manages HDFS
d. Schedules reducers
Answer: b. Executes assigned tasks on nodesgeeksforgeeks
How does MapReduce achieve scalability?
a. Fixed number of tasks
b. Parallel task execution across nodes
c. Centralized data processing
d. Limiting reducer count
Answer: b. Parallel task execution across nodesibm+1
The main input format for MapReduce is:
a. XML
b. SequenceFile
c. Key-Value pair
d. SQL Table
Answer: c. Key-Value paircloudfoundation+1
Which phase can use a Combiner?
a. Reduce
b. Mapping
c. Shuffle
d. Sorting
Answer: b. Mappingcloudfoundation+1
Which of the following best describes the job of the Mapper?
a. Aggregates data
b. Translates input splits to key-value pairs
c. Writes output to HDFS
d. Syncs reducers
Answer: b. Translates input splits to key-value pairsgeeksforgeeks
MapReduce achieves fault tolerance by:
a. Restarting failed nodes manually
b. Reassigning failed tasks
c. Discarding failed jobs
d. Ignoring errors
Answer: b. Reassigning failed taskscloudfoundation+1
The output from the Mapper is typically:
a. Unsorted
b. Aggregated
c. Deleted
d. Sorted
Answer: a. Unsortedcloudfoundation+1
What is the role of the Partitioner in MapReduce?
a. Breaks input data
b. Split job into tasks
c. Determines which reducer a key goes to
d. Sorts values
Answer: c. Determines which reducer a key goes tocloudfoundation
In MapReduce, data transfer between map and reduce phases is via:
a. Disk only
b. Shuffle and sort step
c. Memory only
d. Combiner
Answer: b. Shuffle and sort stepcloudfoundation+1
If a reducer fails during execution, MapReduce will:
a. Halt the job
b. Restart only the failed reducer
c. Restart all reducers
d. Ignore failure
Answer: b. Restart only the failed reducercloudfoundation+1
The number of reducers in a MapReduce job is:
a. Fixed at 1
b. Based on number of Mappers
c. User-defined or system optimized
d. Equal to number of nodes
Answer: c. User-defined or system optimizedfreshersnow+1
Which process provides load balancing in MapReduce architecture?
a. Client job submission
b. Task distribution by Job Tracker
c. Combiner execution
d. Shuffle process
Answer: b. Task distribution by Job Trackergeeksforgeeks
Output files from reducers are written in:
a. Local disk
b. Output directory of HDFS
c. Shuffle memory
d. Map output buffer
Answer: b. Output directory of HDFSgeeksforgeeks
Which of the following is an optimization technique in MapReduce?
a. Data scavenging
b. Speculative execution
c. Centralized scheduling
d. Checkpointing only
Answer: b. Speculative executiongeeksforgeeks
How does MapReduce handle slow tasks?
a. Ignores slow tasks
b. Launches duplicate (speculative) tasks
c. Kills slow mappers
d. Delays reduce phase
Answer: b. Launches duplicate (speculative) tasksgeeksforgeeks
Which is not a valid phase in MapReduce?
a. Shuffle
b. Sort
c. Partition
d. Join
Answer: d. Joincloudfoundation+1
What is the main advantage of MapReduce architecture?
a. Real-time processing
b. Scalability and fault tolerance
c. High administrative overhead
d. Expensive servers needed
Answer: b. Scalability and fault toleranceibm+1
Which Hadoop component is responsible for resource management in modern Hadoop systems?
a. Job Tracker
b. Name Node
c. YARN
d. Combiner
Answer: c. YARNslideshare
What is the input split in MapReduce?
a. Entire dataset
b. HDFS Block
c. Subset of input assigned to a Mapper
d. Reducer output
Answer: c. Subset of input assigned to a Mappergeeksforgeeks
During which step are intermediate key groups sent to the Reducer?
a. Mapping
b. Output
c. Shuffle and sort
d. Input split
Answer: c. Shuffle and sortgeeksforgeeks
The output of Map tasks is:
a. Final result
b. Intermediate key-value pairs
c. Raw input data
d. Reducer instructions
Answer: b. Intermediate key-value pairscloudfoundation+1
Which protocol is MapReduce fundamentally based upon?
a. Serial computation
b. Distributed parallel computation
c. Quantum communication
d. Token passing
Answer: b. Distributed parallel computationibm+1
The Job Tracker splits a job into:
a. Blocks
b. Tasks
c. Reducers
d. Files
Answer: b. Tasksgeeksforgeeks
The intermediate data from Mappers is:
a. Sent directly to storage
b. Passed through shuffle and sort before reducing
c. Aggregated by Job Tracker
d. Lost if not reduced
Answer: b. Passed through shuffle and sort before reducinggeeksforgeeks
Which statement defines combiner’s function?
a. Optimizes reducer by pre-aggregation
b. Increases task splits
c. Reduces block size
d. Manages speculative execution
Answer: a. Optimizes reducer by pre-aggregationcloudfoundation
What feature minimizes network congestion in MapReduce?
a. Task Tracker polling
b. Data locality and combiner
c. Single reducer job
d. No mapping
Answer: b. Data locality and combinercloudfoundation+1
The process of transforming input into key-value pairs in MapReduce is done by:
a. Reducer
b. Mapper
c. Partitioner
d. Joiner
Answer: b. Mappercloudfoundation+1
Which file contains user code for Mapper and Reducer?
a. HDFS XML
b. JAR file submitted by Client
c. Shuffle buffer
d. ResourceManager script
Answer: b. JAR file submitted by Clientgeeksforgeeks
What ensures MapReduce can process petabyte-scale data efficiently?
a. Manual task assignment
b. Task parallelism and fault tolerance
c. Single thread execution
d. Reducer only workflow
Answer: b. Task parallelism and fault toleranceibm+1
Which of these is not a responsibility of the MapReduce Job Tracker?
a. Coordinating task execution
b. Assigning tasks based on data locality
c. Writing output to HDFS
d. Packaging user’s client code
Answer: d. Packaging user’s client codegeeksforgeeks

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