Hi @michelleliu 

This sawtooth pattern in DLT processing times is actually quite common and typically indicates one of several underlying issues. Here are the most likely causes and solutions:

Common Causes
1. Memory Pressure & Garbage Collection

Processing times increase as memory fills up with cached data, shuffle files, or intermediate results
Eventually triggers major garbage collection or memory cleanup, causing the "drop" back to baseline
More common with streaming workloads that accumulate state over time

2. Checkpoint Growth

Streaming checkpoints grow over time, making recovery operations slower
Periodic checkpoint cleanup causes the reset to faster times

3. Auto-scaling Behavior

Cluster starts with optimal resources, gradually loses executors due to perceived idle time
Eventually scales back up when performance degrades enough
The "drop" represents fresh executors joining

4. State Store Compaction

Stateful streaming operations accumulate state files
Periodic compaction/cleanup resets performance