TLDR Tech / Data
Smart caching with CTE on Spark
Spark recomputes reused and nested CTEs by default, so cache selectively at fan-out points when intermediate results are complex, fit in memory, and reused. Avoid caching huge or trivial datasets, use eager caching for clearer monitoring, and materialize deep transformation chains to reduce redundant work and prevent stack overflows.
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