Q121
Q121 What role does Apache Ranger play in Hadoop security?
It provides a framework for encryption
It is primarily used for data auditing
It manages detailed access control policies
It is used for network traffic monitoring
Q122
Q122 What is the primary security challenge that Hadoop faces due to its distributed computing model?
Coordination between different data nodes
Protection of data integrity across multiple systems
Ensuring consistent network performance
Managing varying data formats
Q123
Q123 How do you enable HTTPS for a Hadoop cluster to secure data in transit?
Set dfs.http.policy to HTTPS_ONLY in hdfs-site.xml
Change hadoop.ssl.enabled to true in core-site.xml
Update hadoop.security.authentication to ssl
Modify the dfs.datanode.https.address property
Q124
Q124 How can you configure Hadoop to use a custom encryption algorithm for data at rest?
Define the custom algorithm in the hdfs-site.xml under the dfs.encrypt.data.transfer.algorithm property
Update hdfs-site.xml with dfs.encryption.key.provider.uri set to your key provider
Modify core-site.xml with hadoop.security.encryption.algorithm set to your algorithm
Adjust hdfs-site.xml with dfs.data.encryption.algorithm set to your algorithm
Q125
Q125 What is the first step to troubleshoot if you cannot authenticate with a Hadoop cluster using Kerberos?
Verify the Kerberos server status
Check the network connectivity
Review the Hadoop and Kerberos configuration files
Check the system time settings on your machine
Q126
Q126 How do you resolve issues related to data encryption keys not being accessible in Hadoop?
Reconfigure the key management service settings
Restart the Hadoop cluster
Update the encryption policies
Generate new encryption keys
Q127
Q127 What is the main purpose of the Hadoop JobTracker?
To store data on HDFS
To manage resources across the cluster
To track the execution of MapReduce tasks
To coordinate data replication
Q128
Q128 How does Hadoop handle hardware failures to maintain data availability?
By immediately replicating data to other data centers
By using RAID configurations
By replicating data blocks across multiple nodes
By storing multiple copies of data in the same node
Q129
Q129 What is the impact of a poorly configured Hadoop cluster on data processing?
Increased processing speed
Decreased data security
Irregular data processing times
Reduced resource utilization
Q130
Q130 How can administrators optimize a Hadoop cluster's performance during high data load periods?
By increasing the memory of each node
By adding more nodes to the cluster
By prioritizing high-load jobs
By reconfiguring network settings
Q131
Q131 How do you manually start the Hadoop daemons on a specific node?
start-daemon.sh
hadoop-daemon.sh start
start-node.sh
node-start.sh
Q132
Q132 What command is used to rebalance the Hadoop cluster to ensure even distribution of data across all nodes?
hadoop balancer
dfsadmin -rebalance
hdfs dfs -rebalance
hadoop fs -balance
Q133
Q133 What should you check if a node repeatedly fails in a Hadoop cluster?
Node hardware issues
HDFS permissions
The validity of data blocks
The JobTracker status
Q134
Q134 What is a crucial step in troubleshooting a slow-running MapReduce job in Hadoop?
Check the configuration of task trackers
Examine the job's code for inefficiencies
Monitor network traffic
Review data input sizes and formats
Q135
Q135 What is the primary tool used for monitoring Hadoop cluster performance?
Ganglia
Nagios
Ambari
HDFS Audit Logger
Q136
Q136 How do resource managers contribute to the troubleshooting process in a Hadoop cluster?
They allocate resources optimally to prevent job failures
They provide logs for failed jobs
They reroute traffic during node failures
They automatically correct configuration errors
Q137
Q137 What role does log aggregation play in Hadoop troubleshooting?
It decreases the volume of logs for faster processing
It centralizes logs for easier access and analysis
It encrypts logs for security
It filters out unnecessary log information
Q138
Q138 What command is used to view the current status of all nodes in a Hadoop cluster?
hdfs dfsadmin -report
hadoop fs -status
yarn node -list
mapred listnodes
Q139
Q139 How can you configure the logging level of a running Hadoop daemon without restarting it?
By modifying the log4j.properties file and reloading it via the command line
By using the hadoop log -setlevel command with the appropriate daemon and level
By editing the hadoop-env.sh file
By updating the Hadoop configuration XMLs and performing a rolling restart
Q140
Q140 What should you check first if a node in a Hadoop cluster is unexpectedly slow in processing tasks?
Network connectivity between the node and the rest of the cluster
Disk health of the node
CPU utilization rates of the node
Configuration settings of Hadoop on the node
Q141
Q141 How do you identify and handle memory leaks in a Hadoop cluster?
By restarting nodes regularly
By monitoring garbage collection logs and Java heap usage
By increasing the memory allocation to Java processes
By reconfiguring Hadoop's use of swap space
Q142
Q142 What steps should be taken when a critical Hadoop daemon such as the NameNode or ResourceManager crashes?
Immediately restart the daemon
Analyze logs to determine the cause before restarting
Increase virtual memory settings
Contact support
Q143
Q143 What is the impact of data locality on Hadoop performance?
It increases data redundancy
It decreases job execution time
It increases network traffic
It decreases data availability
Q144
Q144 How does increasing the block size in HDFS affect performance?
It increases the overhead of managing metadata
It decreases the time to read data due to fewer seek operations
It increases the complexity of data replication
It decreases the efficiency of data processing
Q145
Q145 What is the benefit of using compression in Hadoop data processing?
It increases the storage capacity on HDFS
It speeds up data transfer across the network by reducing the amount of data transferred
It simplifies data management
It enhances data security
Q146
Q146 How do you enable compression for MapReduce output in Hadoop?
Set mapreduce.output.fileoutputformat.compress to true in the job configuration
Set mapreduce.job.output.compression to true
Set hadoop.mapreduce.compress.map.output to true
Enable compression in core-site.xml
Q147
Q147 How can you specifically control the distribution of data to reducers in a Hadoop job?
Specify mapreduce.job.reduces in the job's configuration
Use a custom partitioner
Modify mapred-site.xml
Adjust reducer capacity
Q148
Q148 What should you check first if MapReduce jobs are taking longer than expected to write their output?
The configuration of the output format
The health of the HDFS nodes
The network conditions
The reducer phase settings
Q149
Q149 How do you diagnose and resolve data skew in a Hadoop job that causes some reducers to take much longer than others?
Check and adjust the partitioner logic
Increase the number of reducers
Reconfigure the cluster to add more nodes
Manually redistribute the input data
Q150
Q150 How do you optimize memory usage for MapReduce tasks to handle large datasets without running into memory issues?
Increase the Java heap space setting
Implement in-memory data management
Optimize data processing algorithms
Adjust task configuration
