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Timely and cost-efficient data exploration through adaptive tuning

Publications associées (98)

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Scalable Multi-Query Execution using Reinforcement Learning

Anastasia Ailamaki, Panagiotis Sioulas

The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...

Association for Computing Machinery2021

Access pattern based optimization of memory access

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A method for optimizing memory access for database operations is provided. The method may include identifying an access pattern associated with a database operation. The access pattern may include data required to perform the database operation. One or mor ...

2020

JIT works: decide when all data is known (VLDB Women in Database Research Award talk)

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When the time comes to make a critical decision, it is of paramount importance to prepare enough so that all the information necessary is available at decision time. Under-preparation leads to uninformed decisions; over-preparation, however, may lead to co ...

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Time- and Space-Efficient Spatial Data Analytics

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Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

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Consolidation of database check constraints

Nikola Obrenovic

Independent modeling of various modules of an information system (IS), and consequently database subschemas, may result in formal or semantic conflicts between the modules being modeled. Such conflicts may cause collisions between the integrated database s ...

2019

Efficient Workload Colocation in Modern Data Centers

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Despite the high costs of acquisition and maintenance of modern data centers, machine resource utilization is often low. Servers running online interactive services are over-provisioned to support peak load (which only occurs for a fraction of the time), d ...

EPFL2019

Taster: Self-Tuning, Elastic and Online Approximate Query Processing

Anastasia Ailamaki, Raja Appuswamy, Matthaios Alexandros Olma, Odysseas Papapetrou

Current Approximate Query Processing (AQP) engines are far from silver-bullet solutions, as they adopt several static design decisions that target specific workloads and deployment scenarios. Offline AQP engines target deployments with large storage budget ...

IEEE2019

SixTrack Version 5: Status and New Developments

Igor Zacharov, Riccardo De Maria, Giovanni Iadarola, Dario Pellegrini, Massimo Giovannozzi

SixTrack Version 5 is a major SixTrack release that introduces new features, with improved integration of the existing ones, and extensive code restructuring. New features include dynamic-memory management, scattering-routine integration, a new initial-con ...

IOP PUBLISHING LTD2019

Caching and Distributed Storage

Saeid Sahraei

A simple task of storing a database or transferring it to a different point via a communication channel turns far more complex as the size of the database grows large. Limited bandwidth available for transmission plays a central role in this predicament. I ...

EPFL2018

Building Efficient Query Engines using High-Level Languages

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We are currently witnessing a shift towards the use of high-level programming languages for systems development. These approaches collide with the traditional wisdom which calls for using low-level languages for building efficient software systems. This sh ...

EPFL2017