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NEW QUESTION: 1
What do project reports show during the Sprint review meeting?
A. Earned value measurement (EVM)
B. Actual results to the plan
C. Estimates compared to the baseline
D. Return on investment (ROI)
Answer: D
NEW QUESTION: 2
When is the earliest point at which the reduce method of a given Reducer can be called?
A. It depends on the InputFormat used for the job.
B. Not until all mappers have finished processing all records.
C. As soon as a mapper has emitted at least one record.
D. As soon as at least one mapper has finished processing its input split.
Answer: B
Explanation:
In a MapReduce job reducers do not start executing the reduce method until the all Map jobs have completed. Reducers start copying intermediate key-value pairs from the mappers as soon as they are available. The programmer defined reduce method is called only after all the mappers have finished.
Note: The reduce phase has 3 steps: shuffle, sort, reduce. Shuffle is where the data is collected by the reducer from each mapper. This can happen while mappers are generating data since it is only a data transfer. On the other hand, sort and reduce can only start once all the mappers are done.
Why is starting the reducers early a good thing? Because it spreads out the data transfer from the mappers to the reducers over time, which is a good thing if your network is the bottleneck.
Why is starting the reducers early a bad thing? Because they "hog up" reduce slots while only copying data. Another job that starts later that will actually use the reduce slots now can't use them.
You can customize when the reducers startup by changing the default value of mapred.reduce.slowstart.completed.maps in mapred-site.xml. A value of 1.00 will wait for all the mappers to finish before starting the reducers. A value of 0.0 will start the reducers right away. A value of 0.5 will start the reducers when half of the mappers are complete. You can also change mapred.reduce.slowstart.completed.maps on a job-by-job basis.
Typically, keep mapred.reduce.slowstart.completed.maps above 0.9 if the system ever has multiple jobs running at once. This way the job doesn't hog up reducers when they aren't doing anything but copying data. If you only ever have one job running at a time, doing 0.1 would probably be appropriate.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, When is the reducers are started in a MapReduce job?
NEW QUESTION: 3
Drag the technology on the left to the data type the technology provides on the right.
Answer:
Explanation:
NEW QUESTION: 4
Exhibit:
What will be the egress interface if the traffic's ingress interface is ethernet1/6 sourcing from 192.168.111.3 and to the destination 10.46.41.113 during the time shown in the image?
A. ethernet1/5
B. ethernet1/3
C. ethernet1/6
D. ethernet1/7
Answer: B