MCQs

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Overall MCQs for Reference

What does RDD stand for in Apache Spark?
a. Reliable Data Dump
b. Resilient Distributed Dataset
c. Random Data Drive
d. Real-time Data Division
Answer: b. Resilient Distributed Datasetjavaguides+1
Which property makes RDDs suitable for cluster computing?
a. Mutability
b. Distributed
c. Volatility
d. Unstructured
Answer: b. Distributeddatacamp+1
RDDs in Spark are:
a. Mutable
b. Immutable
c. Variable in length
d. Always stored on disk
Answer: b. Immutableprojectpro+1
What is the key advantage of Spark RDD’s in-memory computation?
a. Data is always secure
b. Reduces computation speed
c. Enhances processing speed
d. Disables parallelism
Answer: c. Enhances processing speedprojectpro
Which is the primary method to create an RDD?
a. By using SQL queries
b. By loading external data
c. By using JavaScript
d. By using REST APIs
Answer: b. By loading external datadata-flair+1
Which operation produces a new RDD from an existing one?
a. Action
b. Transformation
c. Commitment
d. Deletion
Answer: b. Transformationfreshersnow+1
What is an example of a Spark RDD action?
a. filter()
b. map()
c. count()
d. groupBy()
Answer: c. count()freshersnow
Which function is used to transform one RDD into another RDD?
a. map()
b. reduce()
c. collect()
d. join()
Answer: a. map()javaguides+1
RDDs achieve fault tolerance through:
a. Replication
b. Lineage
c. Caching only
d. Authentication
Answer: b. Lineagefreshersnow+1
How are RDDs evaluated in Spark?
a. Upon transformation
b. When created
c. Upon action
d. During shutdown
Answer: c. Upon actionfreetimelearning+1
Which Spark method is used to cache an RDD in memory?
a. rdd.store()
b. rdd.keep()
c. rdd.cache()
d. rdd.save()
Answer: c. rdd.cache()javaguides+1
What is the default number of partitions for a text file loaded as an RDD?
a. 1
b. 2
c. Based on the HDFS block size
d. 8
Answer: c. Based on the HDFS block sizeedureka
Which is NOT a valid RDD action?
a. count()
b. reduce()
c. filter()
d. collect()
Answer: c. filter()freshersnow
Which describes lazy evaluation in RDD?
a. All operations are executed immediately
b. None are executed
c. Transformations are delayed until an action is called
d. Every step returns output instantly
Answer: c. Transformations are delayed until an action is calleddatacamp+1
What benefit does RDD immutability provide?
a. Security
b. Fault tolerance
c. Real-time writes
d. Inline editing
Answer: b. Fault tolerancedatacamp+1
Which is an example of a narrow transformation?
a. groupByKey
b. reduceByKey
c. map
d. join
Answer: c. mapprojectpro
What does RDD persistence enable?
a. Encryption
b. Reuse of data
c. Data deletion
d. Data anonymization
Answer: b. Reuse of datajavaguides+1
Which RDD method is used to change storage of a persisted RDD?
a. storage()
b. saveAs()
c. persist()
d. sync()
Answer: c. persist()projectpro
What type of operation is filter() in RDD?
a. Action
b. Transformation
c. Join
d. Aggregation
Answer: b. Transformationjavaguides+1
How can you repartition data in an RDD?
a. withColumn()
b. repartition()
c. groupByKey()
d. flatMap()
Answer: b. repartition()edureka
What happens if an RDD partition is lost?
a. Entire computation fails
b. RDD lineage recomputes lost data
c. Partition is skipped
d. Data is unrecoverable
Answer: b. RDD lineage recomputes lost datafreshersnow+1
Which of the following is NOT a persistence level in RDD?
a. MEMORY_ONLY
b. MEMORY_AND_DISK
c. DISK_AND_MEMORY
d. MEMORY_ONLY_SER
Answer: c. DISK_AND_MEMORYprojectpro
What is a Spark executor?
a. A type of RDD
b. Type of DataFrame
c. Process running computations on workers
d. A Spark SQL function
Answer: c. Process running computations on workersfreshersnow+1
Which RDD method returns elements of the dataset as an array to the driver program?
a. reduce()
b. filter()
c. collect()
d. map()
Answer: c. collect()javaguides+1
Which programming languages does Spark RDD API support?
a. Java, Scala, Python
b. Only Scala
c. Only Java
d. Perl
Answer: a. Java, Scala, Pythonprojectpro
What is the minimum number of partitions for an RDD?
a. 0
b. 1
c. 2
d. 3
Answer: b. 1edureka
Which is not a recommended use case for RDDs?
a. Low-level transformations
b. Structured data
c. Unstructured data
d. Complex functions
Answer: b. Structured dataprojectpro
What is a Spark driver?
a. Node running main application
b. Node managing RDD partitions
c. Data lake
d. Hadoop storage
Answer: a. Node running main applicationprojectpro
In RDD, what does sc.textFile() do?
a. Loads text file into an RDD
b. Compresses text file
c. Deletes file
d. Transfers file to storage
Answer: a. Loads text file into an RDDedureka+1
Which operation causes RDD transformations to execute?
a. Action
b. Transformation
c. Scheduling
d. Shuffle
Answer: a. Actionprojectpro
Which method saves an RDD as a text file?
a. saveAsTextFile()
b. writeText()
c. store()
d. archive()
Answer: a. saveAsTextFile()projectpro
What is the output type of the map() transformation?
a. Same type as input
b. Always a string
c. Pair RDD
d. RDD of result type
Answer: d. RDD of result typejavaguides
What type of Spark RDD transformation splits each input into multiple outputs?
a. filter()
b. flatMap()
c. map()
d. reduce()
Answer: b. flatMap()projectpro
What is an RDD partition?
a. Temporary disk file
b. Division of data for parallel processing
c. Copy of dataset
d. Result of an action
Answer: b. Division of data for parallel processingdatacamp+1
Which method returns the first element of an RDD?
a. first()
b. head()
c. one()
d. single()
Answer: a. first()javaguides+1
Which RDD operation combines values with the same key?
a. map()
b. groupByKey()
c. reduceByKey()
d. filter()
Answer: c. reduceByKey()projectpro
What information does RDD lineage provide?
a. Original data schema
b. History of transformations
c. Query plan
d. Persistence storage
Answer: b. History of transformationsfreshersnow
Which is NOT a benefit of RDDs?
a. Fault tolerance
b. Parallel processing
c. In-place updates
d. Lazy evaluation
Answer: c. In-place updatesdatacamp+1
Which is a driver method in Spark?
a. rdd.parallelize()
b. sc.parallelize()
c. session.parallelize()
d. item.parallelize()
Answer: b. sc.parallelize()edureka
What is ‘shuffling’ in Spark?
a. Repartitioning data for joins or aggregations
b. Starting the Spark shell
c. Removing duplicates
d. Increasing memory allocation
Answer: a. Repartitioning data for joins or aggregationsprojectpro
Which statement is TRUE about Spark RDDs?
a. RDDs are mutable
b. Each transformation creates a new RDD
c. RDDs require a schema
d. RDDs can’t be cached
Answer: b. Each transformation creates a new RDDdatacamp+1
Which algorithm is available in Spark ML over RDDs?
a. Random Forest
b. Decision Trees
c. K-means clustering
d. SVM only
Answer: c. K-means clusteringfreshersnow
Which RDD method provides unique element count?
a. count()
b. distinct()
c. unique()
d. groupBy()
Answer: b. distinct()projectpro
What happens on calling rdd.unpersist()?
a. RDD is removed from memory
b. RDD is split
c. RDD is duplicated
d. No effect
Answer: a. RDD is removed from memoryprojectpro
How is a Pair RDD created?
a. By mapping tuples
b. By flattening
c. By using split()
d. By filtering
Answer: a. By mapping tuplesprojectpro
Which shared variables type does Apache Spark NOT support?
a. Broadcast variables
b. Accumulators
c. Generic globals
d. None of the above
Answer: c. Generic globalsincludehelp
Which partitioning technique is NOT supported by Spark?
a. Hash partitioning
b. Range partitioning
c. Central partitioning
d. Custom partitioning
Answer: c. Central partitioningprojectpro
What does the flatMap() function do?
a. Applies a function to each element and flattens the result
b. Filters data
c. Collects element
d. Returns frequency
Answer: a. Applies a function to each element and flattens the resultprojectpro
How can RDDs enable iterative machine learning algorithms?
a. By enabling in-memory cache
b. By supporting SQL
c. By storing as CSV
d. By limiting data
Answer: a. By enabling in-memory cacheprojectpro
What is the major limitation of RDDs for big data analytics in Spark?
a. Lack of parallelism
b. Lack of optimization for structured data
c. Only works in Python
d. Cannot be persisted
Answer: b. Lack of optimization for structured datadatacamp+1ack of optimization for structured datafreshersnow+1

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