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Towards a General Framework for ML-based Self-tuning Databases
Machine learning (ML) methods have recently emerged as an effective way ...
11/16/2020 ∙ by Thomas Schmied, et al. ∙
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Toward a Better Understanding and Evaluation of Tree Structures on Flash SSDs
Solid-state drives (SSDs) are extensively used to deploy persistent data...
06/08/2020 ∙ by Diego Didona, et al. ∙
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Lynceus: Tuning and Provisioning Data Analytic Jobs on a Budget
Many enterprises need to run data analytic jobs on the cloud. Significan...
05/06/2019 ∙ by Maria Casimiro, et al. ∙
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Distributed Transactional Systems Cannot Be Fast
We prove that no fully transactional system can provide fast read transa...
03/21/2019 ∙ by Diego Didona, et al. ∙
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PaRiS: Causally Consistent Transactions with Non-blocking Reads and Partial Replication
Geo-replicated data platforms are at the backbone of several large-scale...
02/25/2019 ∙ by Kristina Spirovska, et al. ∙
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Distributed Transactions: Dissecting the Nightmare
Many distributed storage systems are transactional and a lot of work has...
03/16/2018 ∙ by Diego Didona, et al. ∙
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Causal Consistency and Latency Optimality: Friend or Foe?
Causal consistency is an attractive consistency model for replicated dat...
03/12/2018 ∙ by Diego Didona, et al. ∙
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Size-aware Sharding For Improving Tail Latencies in In-memory Key-value Stores
This paper introduces the concept of size-aware sharding to improve tail...
02/02/2018 ∙ by Diego Didona, et al. ∙
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