GeoTP: Latency-aware Geo-Distributed Transaction Processing in Database Middlewares (Extended Version)

Fuente: arXiv
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Main Authors: Zhuang, Qiyu, Shi, Xinyue, Liu, Shuang, Lu, Wei, Zhao, Zhanhao, Chen, Yuxing, Li, Tong, Pan, Anqun, Du, Xiaoyong
Format: Preprint
Published: 2024
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author Zhuang, Qiyu
Shi, Xinyue
Liu, Shuang
Lu, Wei
Zhao, Zhanhao
Chen, Yuxing
Li, Tong
Pan, Anqun
Du, Xiaoyong
author_facet Zhuang, Qiyu
Shi, Xinyue
Liu, Shuang
Lu, Wei
Zhao, Zhanhao
Chen, Yuxing
Li, Tong
Pan, Anqun
Du, Xiaoyong
contents The widespread adoption of database middleware for supporting distributed transaction processing is prevalent in numerous applications, with heterogeneous data sources deployed across national and international boundaries. However, transaction processing performance significantly drops due to the high network latency between the middleware and data sources and the long lock contention span, where transactions may be blocked while waiting for the locks held by concurrent transactions. In this paper, we propose GeoTP, a latency-aware geo-distributed transaction processing approach in database middlewares. GeoTP incorporates three key techniques to enhance geo-distributed transaction performance. First, we propose a decentralized prepare mechanism, which diminishes the requirement of network round trips for distributed transactions. Second, we design a latency-aware scheduler to minimize the lock contention span by strategically postponing the lock acquisition time point. Third, heuristic optimizations are proposed for the scheduler to reduce the lock contention span further. We implemented GeoTP on Apache Shardingsphere, a state-of-the-art middleware, and extended it into Apache ScalarDB. Experimental results on YCSB and TPC-C demonstrate that GeoTP achieves up to 17.7x performance improvement over Shardingsphere.
format Preprint
id arxiv_https___arxiv_org_abs_2412_01213
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GeoTP: Latency-aware Geo-Distributed Transaction Processing in Database Middlewares (Extended Version)
Zhuang, Qiyu
Shi, Xinyue
Liu, Shuang
Lu, Wei
Zhao, Zhanhao
Chen, Yuxing
Li, Tong
Pan, Anqun
Du, Xiaoyong
Databases
The widespread adoption of database middleware for supporting distributed transaction processing is prevalent in numerous applications, with heterogeneous data sources deployed across national and international boundaries. However, transaction processing performance significantly drops due to the high network latency between the middleware and data sources and the long lock contention span, where transactions may be blocked while waiting for the locks held by concurrent transactions. In this paper, we propose GeoTP, a latency-aware geo-distributed transaction processing approach in database middlewares. GeoTP incorporates three key techniques to enhance geo-distributed transaction performance. First, we propose a decentralized prepare mechanism, which diminishes the requirement of network round trips for distributed transactions. Second, we design a latency-aware scheduler to minimize the lock contention span by strategically postponing the lock acquisition time point. Third, heuristic optimizations are proposed for the scheduler to reduce the lock contention span further. We implemented GeoTP on Apache Shardingsphere, a state-of-the-art middleware, and extended it into Apache ScalarDB. Experimental results on YCSB and TPC-C demonstrate that GeoTP achieves up to 17.7x performance improvement over Shardingsphere.
title GeoTP: Latency-aware Geo-Distributed Transaction Processing in Database Middlewares (Extended Version)
topic Databases
url https://arxiv.org/abs/2412.01213