Assume you have a file named foo.txt in your local directory. You issue the following three commands:
Hadoop fs -mkdir input
Hadoop fs -put foo.txt input/foo.txt
Hadoop fs -put foo.txt input
What happens when you issue that third command?

• A. The write silently fails
• B. You get an error message telling you that foo.txt already exists, and asking you if you would like to overwrite
• C. The write succeeds, overwriting foo.txt in HDFS with no warning
• D. The file is uploaded and stored as a plain named input
• E. You get a error message telling you that foo.txt already exists. The file is not written to HDFS
• F. You get a warning that foo.txt is being overwritten
• G. You get an error message telling you that input is not a directory

You suspect that your NameNode is incorrectly configured, and is swapping memory to disk. Which Linux commands help you to identify whether swapping is occurring? (Select 3)

• A. df
• B. top
• C. free
• D. swapinfo
• E. memcat
• F. vmstat

You have converted your Hadoop cluster from a MapReduce 1 (MRv1) architecture to a MapReduce 2 (MRv2) on YARN architecture. Your developers are accustomed to specifying map and reduce tasks (resource allocation) tasks when they run jobs. A developer wants to know how specify to reduce tasks when a specific job runs. Which method should you tell that developer to implement?

• A. In YARN, resource allocation is a function of megabytes of memory in multiple of 1024mb. Thus, they should specify the amount of memory resource they need by executing -D mapreduce.reduce.memory-mp-2040
• B. Developers specify reduce tasks in the exact same way for both MapReduce version 1 (MRv1) and MapReduce version 2 (MRv2) on YARN. Thus, executing -p mapreduce.job.reduce-2 will specify 2 reduce tasks.
• C. In YARN, the ApplicationMaster is responsible for requesting the resources required for a specific job. Thus, executing -p yarn.applicationmaster.reduce.tasks-2 will specify that the ApplicationMaster launch two task containers on the worker nodes.
• D. In YARN, resource allocation is a function of virtual cores specified by the ApplicationMaster making requests to the NodeManager where a reduce task is handled by a single container (and this a single virtual core). Thus, the developer needs to specify the number of virtual cores to the NodeManager by executing -p yarn.nodemanager.cpuvcores=2
• E. MapReduce version 2 (MRv2) on YARN abstracts resource allocation away from the idea of "tasks" into memory and virtual cores, thus eliminating the need for a developer to specify the number of reduce tasks, and indeed preventing the developer from specifying the number of reduce tasks.

Your cluster implements HDFS High Availability (HA). Your two NameNodes are named nn01 and nn02. What occurs when you execute the command: hdfs haadmin -failover nn01 nn02

• A. nn02 is fenced, and nn01 becomes the active NameNode
• B. nn01 becomes the standby NamNode and nn02 becomes the active NAmeNode
• C. nn01 is fenced, and nn02 becomes the active NameNode
• D. nn02 becomes the standby NameNode and nn01 becomes the active NameNode