{
  "key_concepts": [
    "RDD transformations (map, filter, flatMap, groupByKey)",
    "RDD actions (collect, reduce, count, saveAsTextFile)",
    "Lazy evaluation and execution triggers",
    "Lineage graphs and recomputation for fault tolerance",
    "RDD immutability and persistence/caching semantics",
    "DAG/stage concepts and job scheduling in Spark"
  ],
  "primary_domain": "technical",
  "use_cases": [
    "Screening candidates for data-engineer or Spark developer roles to verify practical knowledge of RDD APIs and execution model",
    "Assessing learning outcomes after a Spark training focused on core RDD concepts (transformations, actions, lazy evaluation)",
    "Validating candidates' understanding of Spark fault-tolerance and execution planning for roles requiring performance debugging or optimization"
  ]
}