Evaluating SPARQL Queries on Massive RDF Datasets
Summary: AdHash is a distributed RDF system that uses lightweight hash partitioning to minimize startup cost and parallelize subject-based joins with no inter-node communication. It dynamically adapts to the workload by redistributing and replicating hot data, drastically reducing future communication and enabling subsecond queries on billion-scale RDF data. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Razen Harbi
- 2. Ibrahim Abdelaziz
- 3. Panos Kalnis
- 4. Nikos Mamoulis
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 582 | Scalable SPARQL Querying of Large RDF Graphs | 2011 | VLDB | 0.00019723083 |
| 1,213 | RDF-3X: a RISC-style Engine for RDF | 2008 | VLDB | 0.0001325231 |
| 1,675 | A Distributed Graph Engine for Web Scale RDF Data | 2013 | VLDB | 0.00010947606 |
| 2,554 | TripleBit: a Fast and Compact System for Large Scale RDF Data | 2013 | VLDB | 8.549897e-05 |
| 2,803 | TriAD: A Distributed Shared-Nothing RDF Engine based on Asynchronous Message Passing | 2014 | SIGMOD | 8.0940362e-05 |
| 4,729 | Workload Matters: Why RDF Databases Need a New Design | 2014 | VLDB | 5.9675136e-05 |
| 6,401 | Scaling Queries over Big RDF Graphs with Semantic Hash Partitioning | 2013 | VLDB | 5.0801167e-05 |
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