**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams.
Shuffle join: both sides distributed by key; SortMergeJoin or HashJoin; large data movement. Broadcast join: small table sent to all executors; no shuffle for large table; efficient when one side is small (under 100MB). Use broadcast when one table fits in memory: df1.join(broadcast(df2)). Use shuffle when both large....
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