**Steps**: (1) Install Spark (SPARK_HOME). (2) `pip install pyspark`. (3) `spark-submit --master yarn --deploy-mode client /path/script.py`. Or `--master local[*]` without YARN. (4) `--conf spark.executor.memory=4g` for config. (5) `--py-files` for zip dependencies.
**Why Care**: EC2 = raw VMs; no managed Spark. EMR provides managed Spark on EC2.
**Scalability Trade-offs**: Local mode = single machine. YARN = multi-node....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Carelon. The answer also includes follow-up discussion points that interviewers commonly explore.
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