CrypQ: A Database Benchmark Based on Dynamic, Ever-Evolving Ethereum Data
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913587316916224 |
|---|---|
| author | Capol, Vincent Liu, Yuxi Xiu, Haibo Yang, Jun |
| author_facet | Capol, Vincent Liu, Yuxi Xiu, Haibo Yang, Jun |
| contents | Modern database systems are expected to handle dynamic data whose characteristics may evolve over time. Many popular database benchmarks are limited in their ability to evaluate this dynamic aspect of the database systems. Those that use synthetic data generators often fail to capture the complexity and unpredictable nature of real data, while most real-world datasets are static and difficult to create high-volume, realistic updates for. This paper introduces CrypQ, a database benchmark leveraging dynamic, public Ethereum blockchain data. CrypQ offers a high-volume, ever-evolving dataset reflecting the unpredictable nature of a real and active cryptocurrency market. We detail CrypQ's schema, procedures for creating data snapshots and update sequences, and a suite of relevant SQL queries. As an example, we demonstrate CrypQ's utility in evaluating cost-based query optimizers on complex, evolving data distributions with real-world skewness and dependencies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_17913 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | CrypQ: A Database Benchmark Based on Dynamic, Ever-Evolving Ethereum Data Capol, Vincent Liu, Yuxi Xiu, Haibo Yang, Jun Databases Modern database systems are expected to handle dynamic data whose characteristics may evolve over time. Many popular database benchmarks are limited in their ability to evaluate this dynamic aspect of the database systems. Those that use synthetic data generators often fail to capture the complexity and unpredictable nature of real data, while most real-world datasets are static and difficult to create high-volume, realistic updates for. This paper introduces CrypQ, a database benchmark leveraging dynamic, public Ethereum blockchain data. CrypQ offers a high-volume, ever-evolving dataset reflecting the unpredictable nature of a real and active cryptocurrency market. We detail CrypQ's schema, procedures for creating data snapshots and update sequences, and a suite of relevant SQL queries. As an example, we demonstrate CrypQ's utility in evaluating cost-based query optimizers on complex, evolving data distributions with real-world skewness and dependencies. |
| title | CrypQ: A Database Benchmark Based on Dynamic, Ever-Evolving Ethereum Data |
| topic | Databases |
| url | https://arxiv.org/abs/2411.17913 |