Publications associées à Scalable Delivery of Stream Query Result

Publications associées (31)

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

EPFL2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

arXiv2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in r ...

Assoc Computing Machinery2023

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Zhekai Jiang, Christoph Koch, Sachin Basil John, Peter Lindner

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Association for Computing Machinery2023

Sampling-Based AQP in Modern Analytical Engines

Anastasia Ailamaki, Viktor Sanca

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

ACM2022

Dalton: Learned Partitioning for Distributed Data Streams

Anastasia Ailamaki, Ioannis Mytilinis, Eleni Zapridou

To sustain the input rate of high-throughput streams, modern stream processing systems rely on parallel execution. However, skewed data yield imbalanced load assignments and create stragglers that hinder scalability. Deciding on a static partitioning for a ...

2022

Dynamic Personalized Ranking

Jérémie Rappaz

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

EPFL2022

Edit Based Grading of SQL Queries

Bikash Chandra

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

ASSOC COMPUTING MACHINERY2021

How Many CPU Cores is an FPGA Worth? Lessons Learned from Accelerating String Sorting on a CPU-FPGA System

Paolo Ienne, Mikhail Asiatici

String sorting is a fundamental kernel of string matching and database index construction; yet, it has not been studied as extensively as fixed-length keys sorting. Because processing variable-length keys in hardware is challenging, it is no surprise that ...

SPRINGER2021

Micro-architectural Analysis of Database Workloads

Utku Sirin

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

EPFL2021

Pipeline Synthesis and Optimization from Branched Feedback Dataflow Programs

Marco Mattavelli, Endri Bezati, Simone Casale Brunet, Anatoly Prihozhy

Large dataflow designs are a result of behavioral specification of modern complex digital systems and/or a result of unfolding and transforming looped and branched programs. Since deep-submicron silicon technology provides large amounts of available resour ...

SPRINGER2020

Sub-Matrix Factorization for Real-Time Vote Prediction

Patrick Thiran, Matthias Grossglauser, Victor Kristof

We address the problem of predicting aggregate vote outcomes (e.g., national) from partial outcomes (e.g., regional) that are revealed sequentially. We combine matrix factorization techniques and generalized linear models (GLMs) to obtain a flexible, effic ...

2020

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Mohammadhossein Gorji

The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...

2019

Timely and cost-efficient data exploration through adaptive tuning

Matthaios Alexandros Olma

Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up. Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...

EPFL2019

Time- and Space-Efficient Spatial Data Analytics

Mirjana Pavlovic

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 ...

EPFL2019

Efficient Learning from Comparisons

Lucas Maystre

Humans are comparison machines: comparing and choosing an item among a set of alternatives (such as objects or concepts) is arguably one of the most natural ways for us to express our preferences and opinions. In many applications, the analysis of data con ...

EPFL2018

Monitoring distributed fragmented skylines

Odysseas Papapetrou

Distributed skyline computation is important for a wide range of domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is ...

2018

Benchmarking Touchscreen Biometrics for Mobile Authentication

We study user interaction with touchscreens based on swipe gestures for personal authentication. This approach has been analyzed only recently in the last few years in a series of disconnected and limited works. We summarize those recent efforts and then c ...

2018

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Matthias Grossglauser, Lucas Maystre

We address the problem of learning a ranking by using adaptively chosen pairwise comparisons. Our goal is to recover the ranking accurately but to sample the comparisons sparingly. If all comparison outcomes are consistent with the ranking, the optimal sol ...

2017

Distributed Time Series Analytics

Tian Guo

In recent years time series data has become ubiquitous thanks to affordable sensors and advances in embedded technology. Large amount of time-series data are continuously produced in a wide spectrum of applications, such as sensor networks, medical monitor ...

EPFL2017