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| Content Provider | ACM Digital Library |
|---|---|
| Author | Pang, Gene Kraska, Tim Franklin, Michael J. Fekete, Alan |
| Abstract | Latency unpredictability in a database system can come from many factors, such as load spikes in the workload, inter-query interactions from consolidation, or communication costs in cloud computing or geo-replication. High variance and high latency environments make developing interactive applications difficult, because transactions may take too long to complete, or fail unexpectedly. We propose Predictive Latency-Aware NEtworked Transactions (PLANET), a new transaction programming model and underlying system support to address this issue. The model exposes the internal progress of the transaction, provides opportunities for application callbacks, and incorporates commit likelihood prediction to enable good user experience even in the presence of significant transaction delays. The mechanisms underlying PLANET can be used for admission control, thus improving overall performance in high contention situations. In this paper, we present this new transaction programming model, demonstrate its expressiveness via several use cases, and evaluate its performance using a strongly consistent geo-replicated database across five data centers. |
| Starting Page | 3 |
| Ending Page | 14 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450323765 |
| DOI | 10.1145/2588555.2588558 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-06-18 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Geo-replication Speculative commits Transaction programming model Commit likelihood |
| Content Type | Text |
| Resource Type | Article |
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