You have a cluster running with the fair Scheduler enabled. There are currently no jobs
running on the cluster, and you submit a job A, so that only job A is running on the cluster. A
while later, you submit Job B. now Job A and Job B are running on the cluster at the same
time. How will the Fair Scheduler handle these two jobs?
A.
When Job B gets submitted, Job A has to finish first, before job B can gets scheduled.
B.
When Job A gets submitted, it doesn’t consumes all the task slots.
C.
When Job A gets submitted, it consumes all the task slots.
D.
When Job B gets submitted, it will get assigned tasks, while job A continues to run with
fewer tasks.
C,D
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A and C are correct answers.
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D
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Based on this, I would go with C and D
“Fair scheduling is a method of assigning resources to jobs such that all jobs get, on average, an equal share of resources over time. When there is a single job running, that job uses the entire cluster. When other jobs are submitted, tasks slots that free up are assigned to the new jobs, so that each job gets roughly the same amount of CPU time. Unlike the default Hadoop scheduler, which forms a queue of jobs, this lets short jobs finish in reasonable time while not starving long jobs. It is also an easy way to share a cluster between multiple of users. Fair sharing can also work with job priorities – the priorities are used as weights to determine the fraction of total compute time that each job gets.”
https://hadoop.apache.org/docs/r1.2.1/fair_scheduler.html
Couldn’t find the documentation for a more recent version
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C and D
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while Job A is in process there should be at least one task available to start the application master in order to initiate the Job B
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