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NEW QUESTION: 1
After delegated administration is granted for a custom object, what action can the delegated administrator complete? Choose 2 answers
A. Create a custom tab for the object
B. Add a custom picklist field to the object
C. Change organization-wide sharing rules for the object
D. Change the relationship with other object
Answer: A,B

NEW QUESTION: 2
A clerk is using the Human Resources form, which displays a department and its associated employees on the same canvas. Only two Items in the form are enabled.
Possible navigation units that can occur during navigation of this form are:
1. Outside the form
2. The Human Resources form
3. The Departments block
4. The Employees block
5. The current Departments record
6. The current Employees record
7. The Department_Id item
8. The Employee_Id item
With the cursor in : Departments.Department_Id, the clerk clicks the
:Employees.Employee_Id item.
What is the sequence of navigational unit movement that occurs?
A. 7 and 8 only
B. 1, 2, 3, 4, 5, 6, 7, and 8
C. 7, 5, 3, 2, 4, 6, and 8 only
D. 7, 5, 3, 2, 4, 6, and 8
E. 7, 5, 3, 4, 6, and 8 only
Answer: E
Explanation:
Explanation:

NEW QUESTION: 3
What determines the number of Reduces that run a given MapReduce job on a cluster running MapReduce v1 (MRv1)?
A. It is set and fixed by the cluster administrator in mapred-site.xml. The number set always run for any submitted job.
B. It is set by the developer.
C. It is set by the Hadoop framework and is based on the number of InputSplits of the job.
D. It is set by the JobTracker based on the amount of intermediate data.
Answer: B
Explanation:
Number of Reduces
The right number of reduces seems to be 0.95 or 1.75 * (nodes * mapred.tasktracker.tasks.maximum). At 0.95 all of the reduces can launch immediately and start transfering map outputs as the maps finish. At 1.75 the faster nodes will finish their first round of reduces and launch a second round of reduces doing a much better job of load balancing.
Currently the number of reduces is limited to roughly 1000 by the buffer size for the output files (io.buffer.size * 2 * numReduces << heapSize). This will be fixed at some point, but until it is it provides a pretty firm upper bound.
The number of reduces also controls the number of output files in the output directory, but usually that is not important because the next map/reduce step will split them into even smaller splits for the maps.
The number of reduce tasks can also be increased in the same way as the map tasks, via JobConf's conf.setNumReduceTasks(int num).
Reference:org.apache.hadoop.mapred
Class JobConf

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