MCQs

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Overall MCQs for Reference

RDD stands for:
a. Random Data Distribution
b. Resilient Distributed Dataset
c. Reliable Database Daemon
d. Rapid Data Dispatcher
Answer: b. Resilient Distributed Datasetintellipaat+1
Which programming language is NOT commonly used with Spark RDDs?
a. Scala
b. Python
c. Java
d. PHP
Answer: d. PHPfreetimelearning+1
What is the main feature of RDDs?
a. Volatility
b. Mutability
c. Immutability
d. Unstructured
Answer: c. Immutabilitysimplilearn+1
RDDs are primarily stored in:
a. Disk
b. Register
c. RAM (memory)
d. Cloud only
Answer: c. RAM (memory)aloa+1
Which of the following is a transformation operation on RDDs?
a. collect()
b. map()
c. count()
d. take()
Answer: b. map()priyadogra+1
Which of the following performs an action on an RDD?
a. filter()
b. map()
c. reduce()
d. flatMap()
Answer: c. reduce()intellipaat+1
Spark uses RDD lineage to:
a. Secure data
b. Track transformations
c. Release unused space
d. Remove redundancy
Answer: b. Track transformationsaloa+1
Which RDD operation does NOT return a value?
a. collect()
b. foreach()
c. take()
d. count()
Answer: b. foreach()priyadogra+1
RDDs allow Spark to reconstruct lost data using:
a. Backups
b. Lineage information
c. SQL queries
d. Cloud archives
Answer: b. Lineage informationsimplilearn+1
The main advantage of RDD is:
a. Schema support
b. Fault tolerance
c. Only SQL execution
d. Uncompressed storage
Answer: b. Fault tolerancealoa+1
Which is NOT a way to create an RDD?
a. By parallelizing a collection
b. Loading an external dataset
c. Performing transformations on existing RDDs
d. Editing the RDD directly
Answer: d. Editing the RDD directlyintellipaat
RDDs in Spark are divided into:
a. Blocks
b. Chunks
c. Partitions
d. Fragments
Answer: c. Partitionsintellipaat+1
Which API provides the most schema awareness?
a. RDD
b. DataFrame
c. Dataset
d. Hadoop
Answer: b. DataFramefreetimelearning+1
RDD transformation functions generate:
a. Same RDD
b. New RDDs
c. Backups
d. SQL queries
Answer: b. New RDDssimplilearn+1
What is the default persistence level for RDDs?
a. Memory only
b. Disk only
c. Memory and disk
d. No persistence
Answer: a. Memory onlyaloa+1
Which of these is NOT an RDD action?
a. map()
b. count()
c. collect()
d. first()
Answer: a. map()priyadogra+1
RDD actions:
a. Trigger computation
b. Create new RDDs
c. Define schema
d. Store metadata
Answer: a. Trigger computationsimplilearn+1
RDD operations are:
a. Eager
b. Lazy
c. Parallel only
d. Sequential only
Answer: b. Lazyaloa+1
Which Spark component directly manages RDDs?
a. Spark SQL
b. Spark Core
c. Spark MLlib
d. Spark Streaming
Answer: b. Spark Coreintellipaat+1
Data in RDDs is:
a. Editable
b. Mutable
c. Read-only
d. Dynamic
Answer: c. Read-onlyintellipaat+1
Which RDD function aggregates data?
a. reduce()
b. filter()
c. map()
d. take()
Answer: a. reduce()priyadogra+1
Which method gets the number of elements in an RDD?
a. collect()
b. first()
c. count()
d. foreach()
Answer: c. count()priyadogra+1
RDDs optimize:
a. Disk I/O
b. In-memory computation
c. XML parsing
d. Web requests
Answer: b. In-memory computationaloa+1
What is NOT true about RDDs?
a. They are immutable
b. They support schema
c. They’re fault tolerant
d. Can be persisted
Answer: b. They support schemasimplilearn+1
RDDs are suitable for:
a. Unstructured data
b. Relational SQL queries
c. Schema-based operations
d. Binary search
Answer: a. Unstructured datasimplilearn+1
The command to create an RDD from a list in Python is:
a. sc.parallelize()
b. sc.textFile()
c. sc.readList()
d. sc.makeRDD()
Answer: a. sc.parallelize()intellipaat+1
RDD actions include:
a. take(n)
b. map()
c. filter()
d. flatMap()
Answer: a. take(n)intellipaat
RDDs in Spark do NOT benefit from:
a. Catalyst optimizer
b. Lazy evaluation
c. Parallelism
d. Fault tolerance
Answer: a. Catalyst optimizeraloa
Which is the correct way to reference a partition in an RDD?
a. Using index
b. Using name
c. Using schema
d. Using ID
Answer: a. Using indexintellipaat
What is preferred for heavy SQL operations in Spark?
a. RDD
b. DataFrame
c. Dataset
d. Stream
Answer: b. DataFramefreetimelearning+1
Which allows for triggering RDD computations?
a. Transformation
b. Action
c. Filtering
d. Partitioning
Answer: b. Actionsimplilearn+1
What is used to filter elements in RDDs?
a. reduce()
b. map()
c. filter()
d. collect()
Answer: c. filter()priyadogra+1
The RDD lineage graph is a:
a. Directed Acyclic Graph (DAG)
b. Linked list
c. Tree
d. Loop
Answer: a. Directed Acyclic Graph (DAG)simplilearn
A major limitation of RDD is:
a. Lack of persistence
b. No built-in schema
c. No parallelism
d. High network cost
Answer: b. No built-in schemaaloa
Which is NOT an RDD transformation?
a. filter()
b. map()
c. reduceByKey()
d. count()
Answer: d. count()priyadogra+1
Which Spark API supports both batch and real-time data?
a. RDD
b. DataFrame
c. Dataset
d. All of the above
Answer: d. All of the abovefreetimelearning
What does the foreach(action) operation do in RDD?
a. Returns values
b. Triggers computation
c. Performs operation on every element
d. Filters data
Answer: c. Performs operation on every elementpriyadogra+1
To fetch the first element in an RDD, use:
a. first()
b. take()
c. map()
d. collect()
Answer: a. first()priyadogra+1
RDDs were introduced in:
a. Hadoop
b. Spark
c. Hive
d. Flink
Answer: b. Sparksimplilearn+1
RDD can be persisted using:
a. persist()
b. store()
c. freeze()
d. backup()
Answer: a. persist()aloa+1
Fault recovery in RDD is achieved via:
a. Backups
b. Lineage
c. Snapshots
d. Replication
Answer: b. Lineagealoa+1
Which is best suited for complex unstructured computations?
a. DataFrame
b. Dataset
c. RDD
d. Table
Answer: c. RDDsimplilearn+1
What happens when an RDD partition is lost?
a. All data lost
b. Rebuilt using lineage
c. Error thrown
d. Recomputed on another node
Answer: b. Rebuilt using lineagealoa+1
Spark’s driver program interacts with RDDs using:
a. Worker node
b. Cluster manager
c. Transformations and actions
d. Relational schema
Answer: c. Transformations and actionsintellipaat+1
DataFrames provide _____ API than RDDs.
a. Worse
b. User-friendly
c. Slower
d. No
Answer: b. User-friendlyfreetimelearning+1
RDD operations can be performed in:
a. Scala
b. Java
c. Python
d. All of the above
Answer: d. All of the abovefreetimelearning+1
Which Spark API is slowest for SQL-like workloads?
a. RDD
b. DataFrame
c. Dataset
d. Spark SQL
Answer: a. RDDaloa
Which of these is an RDD action?
a. reduce()
b. map()
c. foreach()
d. filter()
Answer: a. reduce()priyadogra+1
Which operation is preferable for mapping every line of a text file in RDD?
a. map()
b. filter()
c. reduceByKey()
d. groupBy()
Answer: a. map()intellipaat+1
The main disadvantage of RDD compared to DataFrames/Datasets is:
a. Poor fault tolerance
b. No schema awareness
c. No parallel execution
d. Limited persistence
Answer: b. No schema awarenesssimplilearn+1

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