What does excessive memory overhead mean?

Excessive memory overhead refers to the extra memory consumed by data structures, caching, or intermediate results beyond the actual data size. In Spark, this can happen when wide transformations create many shuffle files, or when persisting large datasets in MEMORY_ONLY mode causes spill to disk. It can lead to out‑of‑memory errors, increased garbage collection, and degraded performance. To mitigate excessive memory overhead, you can adjust the storage level (e.g., use MEMORY_AND_DISK), increase executor memory, enable compression, or repartition data to reduce shuffle size. Monitoring tools like Spark UI or Ganglia can help identify stages with high memory usage and guide tuning decisions.