Identify the Role of Core Components of Apache Spark™'s Architecture, Including Cluster, Driver Node, Worker Nodes/executors, CPU Cores, and Memory. ASSOCIATE-DEVELOPER-APACHE-SPARK Practice Questions (Page 4)

Questions 16–20

1. 16expert · hard

   A Spark application is running with executors that have 8 GB of memory. The application caches a large DataFrame and also performs a shuffle. The team notices that the cached data is evicted during the shuffle, causing the application to recompute the DataFrame. They want to avoid this eviction. Which action would most directly help?

   • AIncrease the number of executors
   • BIncrease the storage memory fraction
   • CDisable the shuffle
   • DReduce the number of partitions
   Reveal Solution Discussion Select an answer first
2. 17application · medium

   A Spark application is configured with executors that have 8 cores each. The application has a stage with 16 tasks. How many tasks can run concurrently across all executors if there are 4 executors?

   • A8
   • B16
   • C64
   • D32
   Reveal Solution Discussion Select an answer first
4. 18application · medium

   A company is planning to run Spark applications. They have a set of machines that will be used for this purpose. They need to understand the relationship between the machines and the Spark components. Which statement correctly describes the relationship?

   • AThe driver is a machine, and workers are processes on that machine
   • BThe cluster is the collection of machines; the driver and workers are roles on those machines
   • CThe driver and workers are all processes on a single machine
   • DThe cluster is a process, and the driver is a machine
   Reveal Solution Discussion Select an answer first
5. 19expert · hard

   A Spark cluster has 10 worker nodes, each with 32 GB of RAM. The team is running an application that requires significant memory for caching and shuffle. They notice that the application is slow and suspect that memory is being underutilized. Which action would most directly improve memory utilization?

   • AReduce the number of worker nodes
   • BIncrease the number of executors per worker node
   • CIncrease the memory per executor
   • DDisable caching
   Reveal Solution Discussion Select an answer first
6. 20foundation · easy

   How do CPU cores affect Spark's performance?

   • AThey increase the amount of data that can be cached
   • BThey control the number of executors on a worker node
   • CThey reduce the need for memory in executors
   • DThey determine the level of parallelism for task execution
   Reveal Solution Discussion Select an answer first