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Exam Certified Associate Developer for Apache Spark All Questions

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

Which of the following describes the Spark driver?

  • A. The Spark driver is responsible for performing all execution in all execution modes – it is the entire Spark application.
  • B. The Spare driver is fault tolerant – if it fails, it will recover the entire Spark application.
  • C. The Spark driver is the coarsest level of the Spark execution hierarchy – it is synonymous with the Spark application.
  • D. The Spark driver is the program space in which the Spark application’s main method runs coordinating the Spark entire application.
  • E. The Spark driver is horizontally scaled to increase overall processing throughput of a Spark application.
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Suggested Answer: D 🗳️

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dirdun081
1 week, 1 day ago
Selected Answer: D
D. The Spark driver is the program space in which the Spark application’s main method runs coordinating the Spark entire application. big thanks to https://bit.ly/4haiKbC Their JN0-105 material was the key to my exam success. The Spark driver is responsible for coordinating the execution of a Spark application, and it runs in the program space where the Spark application's main method runs. It manages the scheduling, distribution, and monitoring of tasks across the cluster, and it communicates with the cluster manager to acquire resources and allocate them to the application. The driver also maintains the state of the application and collects results. It is not responsible for performing all execution in all execution modes, nor is it fault-tolerant or horizontally scalable.
upvoted 1 times
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s127
1 month, 3 weeks ago
Selected Answer: D
spark is responsible for executing the main method of program and also collaborates with cluster manager and worker nodes as well.
upvoted 1 times
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zic00
5 months, 3 weeks ago
Selected Answer: D
The Spark driver is responsible for orchestrating the execution of a Spark application, managing the SparkContext, and coordinating the execution of tasks across the Spark cluster. It does not perform the execution of tasks itself but rather schedules tasks on the worker nodes. The Spark driver is not fault-tolerant in the sense that if it fails, the entire Spark application usually fails. It also does not scale horizontally; only the executors (worker nodes) do that.
upvoted 1 times
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Raheel_te
7 months, 2 weeks ago
ignore my previous comment. E is the answer as per the sample exam in Databricks site.
upvoted 1 times
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Raheel_te
7 months, 2 weeks ago
B is the answer as per the sample exam in Databricks site.
upvoted 1 times
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SnData
8 months, 2 weeks ago
D is the answer
upvoted 1 times
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Vikram1710
9 months, 2 weeks ago
Answer -D
upvoted 1 times
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Pankaj_Shet
1 year, 3 months ago
Please let me know what are these dumps used for? Scala - Spark or Python Spark?
upvoted 1 times
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singh100
1 year, 6 months ago
Answer: D Receives the user's code and breaks it into tasks for execution. Orchestrates the execution plan and optimizes the Spark job. Coordinates with cluster managers to allocate resources for tasks. Collects and aggregates results from distributed workers. Maintains the metadata and state of the Spark application during its execution.
upvoted 4 times
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TmData
1 year, 7 months ago
The correct answer is D. The Spark driver is the program space in which the Spark application's main method runs, coordinating the entire Spark application. Explanation: The Spark driver is a program that runs the main method of a Spark application and coordinates the execution of the entire application. It is responsible for defining the SparkContext, which is the entry point for any Spark functionality. The driver program is responsible for dividing the Spark application into tasks, scheduling them on the cluster, and managing the overall execution. The driver communicates with the cluster manager to allocate resources and coordinate the distribution of tasks to the worker nodes. It also maintains the overall control and monitoring of the application. Horizontal scaling, fault tolerance, and execution modes are not directly related to the Spark driver.
upvoted 4 times
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4be8126
1 year, 9 months ago
Selected Answer: D
D. The Spark driver is the program space in which the Spark application’s main method runs coordinating the Spark entire application. The Spark driver is responsible for coordinating the execution of a Spark application, and it runs in the program space where the Spark application's main method runs. It manages the scheduling, distribution, and monitoring of tasks across the cluster, and it communicates with the cluster manager to acquire resources and allocate them to the application. The driver also maintains the state of the application and collects results. It is not responsible for performing all execution in all execution modes, nor is it fault-tolerant or horizontally scalable.
upvoted 3 times
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