A PySpark ETL on EMR must minimize cost volatility while handling variable daily loads. What EMR setup is a strong default?
💡 Model Answer
The recommended default is to use Instance Fleets with managed scaling, combining On‑Demand and Spot instances, and enabling EMRFS consistent view. Instance Fleets allow the cluster to automatically add or remove Spot and On‑Demand nodes based on workload and capacity. Managed scaling policies can be set to maintain a minimum core count while scaling the number of instances up or down as the job progresses, which smooths cost spikes. Spot instances provide significant savings, and the mix with On‑Demand ensures reliability. Enabling EMRFS consistent view guarantees that all nodes see the same S3 data state, reducing data skew and re‑processing. This configuration balances cost, performance, and resilience, making it a strong default for variable daily ETL loads.
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