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 |
|---|---|---|---|---|
| 3,623 | Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings | 2020 | SIGMOD | 6.9017341e-05 |
| 7,652 | Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward | 2021 | VLDB | 4.6831938e-05 |
| 7,685 | AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft | 2020 | VLDB | 4.6753414e-05 |
| 8,196 | SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft | 2021 | VLDB | 4.5568952e-05 |
| 10,767 | SIEVE: Effective Filtered Vector Search with Collection of Indexes | 2025 | VLDB | 4.1905499e-05 |
Previous
Page 1 / 1
Next
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 |
|---|---|---|---|---|
| 1,921 | Selecting Subexpressions to Materialize at Datacenter Scale | 2018 | VLDB | 0.00010085899 |
| 4,171 | Computation Reuse in Analytics Job Service at Microsoft | 2018 | SIGMOD | 6.3800823e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,517 | [Demo] Low-latency Spark Queries on Updatable Data | 2019 | SIGMOD | 4.3294347e-05 |
| 11,199 | QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark | 2023 | SIGMOD | 4.1905499e-05 |
| 6,783 | SparkR: Scaling R Programs with Spark | 2016 | SIGMOD | 4.9221272e-05 |
| 8,585 | A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning | 2024 | VLDB | 4.4856045e-05 |
| 7,019 | Bridging the Gap Between HPC and Big Data Frameworks | 2017 | VLDB | 4.8553946e-05 |
| 3,207 | Big Data Analytics with Datalog Queries on Spark | 2016 | SIGMOD | 7.3847098e-05 |
| 8,454 | Towards Resource Efficiency: Practical Insights into Large-Scale Spark Workloads at ByteDance | 2024 | VLDB | 4.5022073e-05 |
| 4,171 | Computation Reuse in Analytics Job Service at Microsoft | 2018 | SIGMOD | 6.3800823e-05 |
| 3,536 | Scaling Spark in the Real World: Performance and Usability | 2015 | VLDB | 6.9938207e-05 |
| 8,196 | SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft | 2021 | VLDB | 4.5568952e-05 |