Disk spilling occurs when memory is exceeded—often 10–100x slower. WHY: Spilling indicates memory-pressure; it kills SLAs and increases I/O cost. MONITOR: Spark UI (spilled_bytes), Snowflake query_history (bytes_spilled_to_local_storage), Redshift SVL_QUERY_METRICS. REDUCE: (1) Increase executor memory or use memory-optimized instances. (2) Broadcast joins for small tables—tune spark.sql.autoBroadcastJoinThreshold. (3) Repartition before expensive ops to distribute load....
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