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When would you choose a broadcast join over a shuffle join? Any memory risks?

Spark/Big Datamedium0.4 min readPremium
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**Choose Broadcast**: When one table is small (<~100MB). Avoids shuffle of large table. 10–100x faster. **Choose Shuffle**: When both tables large. Broadcast would OOM. **Memory Risk**: Broadcast table sent to every executor. Must fit in executor memory. Oversized = driver or executor OOM. **Mitigation**: Monitor broadcast size. spark.sql.autoBroadcastJoinThreshold (default 10MB). Manual broadcast() when appropriate....
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