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NEW QUESTION: 1
You need to select and configure compute resources for a set of batch processing jobs. These jobs take around 2 hours to complete and are run nightly. You want to minimize service costs. What should you do?
A. Select Google Kubernetes Engine. Use a single-node cluster with a small instance type.
B. Select Compute Engine. Use VM instance types that support micro bursting.
C. Select Google Kubernetes Engine. Use a three-node cluster with micro instance types.
D. Select Compute Engine. Use preemptible VM instances of the appropriate standard machine type.
Answer: D

NEW QUESTION: 2
Which process describes the lifecycle of a Mapper?
A. The JobTracker spawns a new Mapper to process all records in a single file.
B. The JobTracker calls the TaskTracker's configure () method, then its map () method and finally its close () method.
C. The TaskTracker spawns a new Mapper to process each key-value pair.
D. The TaskTracker spawns a new Mapper to process all records in a single input split.
Answer: C
Explanation:
Explanation/Reference:
For each map instance that runs, the TaskTracker creates a new instance of your mapper.
Note:
* The Mapper is responsible for processing Key/Value pairs obtained from the InputFormat. The mapper may perform a number of Extraction and Transformation functions on the Key/Value pair before ultimately outputting none, one or many Key/Value pairs of the same, or different Key/Value type.
* With the new Hadoop API, mappers extend the org.apache.hadoop.mapreduce.Mapper class. This class defines an 'Identity' map function by default - every input Key/Value pair obtained from the InputFormat is written out.
Examining the run() method, we can see the lifecycle of the mapper:
/**
* Expert users can override this method for more complete control over the
* execution of the Mapper.
* @param context
* @throws IOException
*/
public void run(Context context) throws IOException, InterruptedException { setup(context); while (context.nextKeyValue()) {
map(context.getCurrentKey(), context.getCurrentValue(), context);
}
cleanup(context);
}
setup(Context) - Perform any setup for the mapper. The default implementation is a no-op method.
map(Key, Value, Context) - Perform a map operation in the given Key / Value pair. The default implementation calls Context.write(Key, Value) cleanup(Context) - Perform any cleanup for the mapper. The default implementation is a no-op method.
Reference: Hadoop/MapReduce/Mapper

NEW QUESTION: 3
Which two statements about NPIV are true? (Choose two.)
A. NPIV is supported on the Cisco MDS, N7K, and N5K families of switches.
B. A director class switch should not be placed into NPIV mode.
C. After enabling NPIV, switch interfaces can only be placed into NP, F, or SD modes of operation.
D. NPV devices log in to NPIV devices.
E. NPIV requires the Enterprise License Package.
Answer: A,D
Explanation:
N port virtualization (NPV) reduces the number of Fibre Channel domain IDs in SANs. Switches operating in the NPV mode do not join a fabric. They pass traffic between NPV core switch links and end devices, which eliminates the domain IDs for these edge switches.
NPV is supported by the following Cisco MDS 9000 switches and Cisco Nexus 5000 Series switches only:
Reference: http://www.cisco.com/c/en/us/td/docs/switches/datacenter/mds9000/sw/5_0/configuration/guides/i nt/fm/fm_interfaces/npv.html