When a query spills to both local and remote storage, what does that imply about memory usage?

• A. Memory may be insufficient to hold intermediate results
• B. The data is too large to fit in a single node's cache
• C. The network is experiencing high latency
• D. The query was misconfigured

Answer: (A)

The main idea is memory pressure during query execution. When a query processes data, it creates intermediate results in memory. If there isn’t enough RAM to keep those intermediates, the system writes them out to storage—both on the local node and on remote storage—to free up memory for continuing work. This spilling to disk and across storage helps the engine complete the query despite limited memory, but it often slows things down due to I/O. It isn’t necessarily a sign of a misconfiguration or a network issue, though those factors can influence performance.