Exam Certified Associate Developer for Apache Spark topic 1 question 3 discussion

Slots are the basic unit of parallelism in Spark, and represent a unit of resource allocation on a single executor. If there are more slots than there are tasks, it means that some of the slots will be idle and not being used to execute any tasks, leading to inefficient resource utilization. In this scenario, the Spark job will likely not run as efficiently as possible. However, it is still possible for the Spark job to complete successfully. Therefore, option A is the correct answer.

If there are more slots (i.e., available cores) than tasks, some of the slots will remain idle, leading to underutilization of resources. This can result in less efficient execution because the available resources are not being fully utilized.

A is correct

Answer - A

it is A

C. Some executors will shut down and allocate all slots on larger executors first. explanation :If there are more slots than there are tasks in Apache Spark, some executors may shut down, and the available slots will be allocated to larger executors first. This process is part of the dynamic resource allocation mechanism in Spark, where resources are adjusted based on the workload. It helps in efficient resource utilization by shutting down unnecessary executors and allocating resources to larger executors to perform tasks more efficiently.

E , When there are more available slots than tasks, Spark will use a single slot to perform all tasks, which may result in inefficient use of resources.

E es Correct

A is correct

A is correct

A. IF there are more slots than there are tasks, the extra slots will not be utilized, and they will remain idle, resulting in some resource waste. To maximize resource usage efficiency, it is essential to configure the cluster properly and adjust the number of tasks and slots based on the workload demands. Dynamic resource allocation features in cluster managers can also help improve resource utilization by adjusting the cluster size dynamically based on the task requirements.

A. The Spark job will likely not run as efficiently as possible. In Spark, a slot represents a unit of processing capacity that an executor can offer to run a task. If there are more slots than there are tasks, some of the slots will remain unused, and the Spark job will likely not run as efficiently as possible. Spark automatically assigns tasks to slots, and if there are more slots than necessary, some of them may remain idle, resulting in wasted resources and slower job execution. However, the job will not fail as long as there are enough resources to execute the tasks, and Spark will not generate more tasks than needed. Also, executors will not shut down because there are unused slots. They will remain active until the end of the job or until explicitly terminated.