SparkCruise: Handsfree Computation Reuse in Spark
Summary: SparkCruise automatically detects and materializes common subexpressions across interactive Spark workloads for automatic reuse. Integrated into background query processing with no code changes, it enables pay-as-you-go reuse guided by historical queries. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Abhishek Roy
- 2. Alekh Jindal
- 3. Hiren Patel
- 4. Ashit Gosalia
- 5. Subru Krishnan
- 6. Carlo Curino
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,625 | Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings | 2020 | SIGMOD | 6.9055212e-05 |
| 7,655 | Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward | 2021 | VLDB | 4.6872456e-05 |
| 7,684 | AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft | 2020 | VLDB | 4.6796855e-05 |
| 8,197 | SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft | 2021 | VLDB | 4.5607121e-05 |
| 10,761 | SIEVE: Effective Filtered Vector Search with Collection of Indexes | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,922 | Selecting Subexpressions to Materialize at Datacenter Scale | 2018 | VLDB | 0.00010082599 |
| 4,174 | Computation Reuse in Analytics Job Service at Microsoft | 2018 | SIGMOD | 6.3856219e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,516 | [Demo] Low-latency Spark Queries on Updatable Data | 2019 | SIGMOD | 4.3335877e-05 |
| 11,197 | QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark | 2023 | SIGMOD | 4.1945683e-05 |
| 6,784 | SparkR: Scaling R Programs with Spark | 2016 | SIGMOD | 4.9265155e-05 |
| 8,617 | A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning | 2024 | VLDB | 4.4846425e-05 |
| 7,019 | Bridging the Gap Between HPC and Big Data Frameworks | 2017 | VLDB | 4.860057e-05 |
| 3,200 | Big Data Analytics with Datalog Queries on Spark | 2016 | SIGMOD | 7.3912411e-05 |
| 4,174 | Computation Reuse in Analytics Job Service at Microsoft | 2018 | SIGMOD | 6.3856219e-05 |
| 9,155 | Towards Resource Efficiency: Practical Insights into Large-Scale Spark Workloads at ByteDance | 2024 | VLDB | 4.3849295e-05 |
| 3,535 | Scaling Spark in the Real World: Performance and Usability | 2015 | VLDB | 6.9992495e-05 |
| 8,197 | SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft | 2021 | VLDB | 4.5607121e-05 |