Q1
Q1 Which of the following is NOT a characteristic of Big Data?
Volume
Variety
Veracity
Visualization
Q2
Q2 What does the 'Volume' aspect of Big Data refer to?
The speed of data generation
The variety of data types
The sheer amount of data
The accuracy of data
Q3
Q3 What is a key benefit of Big Data analysis?
Reduced hardware requirements
Improved decision-making
Limited data storage
Lower cost of implementation
Q4
Q4 Which of the following is the best description of Big Data?
A small dataset processed using traditional tools
Data that requires new forms of processing due to its size, variety, or speed
Data stored in SQL databases
Data collected from social media platforms
Q5
Q5 Which of the following statements is true about the relationship between Big Data and traditional data processing?
Big Data can always be processed with traditional methods
Traditional methods can handle the velocity of Big Data
Traditional methods struggle with the volume and variety of Big Data
There is no difference between Big Data and traditional data
Q6
Q6 Which of the following challenges is specifically associated with Big Data's velocity?
Ensuring data accuracy
Handling the speed at which data is generated
Reducing data storage requirements
Visualizing the data
Q7
Q7 Which type of data does the variety aspect of Big Data primarily address?
Structured
Unstructured
Both structured and unstructured
Neither
Q8
Q8 Which command is used to list the files in a Hadoop directory?
hdfs dfs -ls
hdfs dfs -rm
hdfs dfs -put
hdfs dfs -copyFromLocal
Q9
Q9 A Big Data job is failing due to a lack of sufficient memory. What is the most likely cause?
The data is too small for the job
Memory allocation is insufficient
The dataset is too fast
There is no issue with memory
Q10
Q10 Which of the following is NOT one of the 3Vs of Big Data?
Volume
Velocity
Variety
Validation
Q11
Q11 What does the 'Velocity' characteristic of Big Data refer to?
The amount of data
The speed at which data is generated
The different types of data
The source of data
Q12
Q12 What type of data does the 'Variety' aspect of Big Data encompass?
Structured
Unstructured
Both structured and unstructured
Neither
Q13
Q13 Which of the following challenges is most associated with Big Data's 'Volume'?
Managing the large amount of data
Ensuring data security
Processing real-time data
Handling different data formats
Q14
Q14 How does the 'Velocity' of Big Data impact data processing?
It slows down data generation
It increases the need for real-time processing
It reduces the variety of data sources
It has no significant effect on processing
Q15
Q15 What is a common challenge related to the 'Variety' aspect of Big Data?
Maintaining data privacy
Analyzing different data formats
Ensuring data consistency
Reducing data size
Q16
Q16 Which command in Hadoop is used to count the number of files in a directory?
hdfs dfs -count
hdfs dfs -list
hdfs dfs -numFiles
hdfs dfs -fileCount
Q17
Q17 A Big Data pipeline is slowing down due to an excessive amount of incoming data. Which aspect of the '3Vs' is causing this issue?
Volume
Velocity
Variety
Value
Q18
Q18 What is the primary purpose of HDFS in Big Data storage?
To store relational data
To store large files across multiple machines
To store in-memory data
To compress files
Q19
Q19 Which of the following is a benefit of distributed file systems like HDFS?
Increased redundancy
Decreased availability
Reduced fault tolerance
Increased hardware cost
Q20
Q20 What does the term "sharding" refer to in NoSQL databases?
Compressing data
Splitting data across multiple servers
Analyzing data
Encrypting data
Q21
Q21 Which of the following technologies is often used for storing unstructured data in Big Data environments?
SQL databases
Relational databases
NoSQL databases
In-memory databases
Q22
Q22 How does data replication enhance reliability in HDFS?
By reducing the storage space
By creating multiple copies of data
By storing data in the cloud
By using distributed caching
Q23
Q23 What is the role of a DataNode in HDFS?
To manage the metadata
To store actual data blocks
To manage the NameNode
To perform data compression
Q24
Q24 Which command is used to put a file into the Hadoop Distributed File System (HDFS)?
hdfs dfs -put
hdfs dfs -get
hdfs dfs -cp
hdfs dfs -cat
Q25
Q25 Which command in Hadoop is used to delete a directory in HDFS?
hdfs dfs -del
hdfs dfs -rm -r
hdfs dfs -rmdir
hdfs dfs -delete
Q26
Q26 Which command is used to check the disk usage of a directory in HDFS?
hdfs dfs -df
hdfs dfs -du
hdfs dfs -usage
hdfs dfs -checkDisk
Q27
Q27 A Hadoop job is failing because the HDFS NameNode is unreachable. What could be the most likely issue?
Insufficient disk space
Network issues
Corrupt DataNode
Job timeout
Q28
Q28 A file fails to upload to HDFS due to a lack of space. What is the likely cause?
The NameNode is corrupt
Data replication failed
DataNode disks are full
File is too small
Q29
Q29 A Hadoop cluster is running slowly due to frequent garbage collection. What could be a likely reason?
Improper memory management
Incorrect replication factor
Excessive disk space
Network issues
Q30
Q30 What is the primary purpose of Hadoop in distributed computing?
Data compression
Fault tolerance
Real-time analytics
Distributed data storage
