A Runtime System for Interruptible Query Processing – When Incremental Computing Meets(…)
summary
Pitstop implements interruptible query processing by partitioning graphs into legs with pit stops, letting queries pause and resume at fine-grained boundaries and opportunistically batch when co-located. It modifies the Cypher runtime in Neo4j, runs on a 96-core Google Cloud VM, and evaluates on real datasets (42M Twitter users, 12M Stack Overflow; 4.4M GitHub). It preserves sequential consistency with a formal supplement proof, reduces single-core latency from 16→13 intervals and two-core to 9, and reports up-to nearly two orders of magnitude speedup over unmodified Neo4j.
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chapters (11)
- 0:00Interruptible query processing intro
- 1:24Motivation for graph workloads
- 3:07Pit Stop runtime system
- 5:18Monolithic vs incremental demo
- 8:55Why Pit Stop outperforms
- 11:02Evaluation setup and datasets
- 12:08Performance results and speedup
- 14:54Conclusion and future work
- 15:14Q&A memory and JVM
- 16:17Q&A garbage collection
- 17:21Q&A batching benefits
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