Publications associées à Conjunctive query

Parallel-Correctness and Containment for Conjunctive Queries with Union and Negation

Single-round multiway join algorithms first reshuffle data over many servers and then evaluate the query at hand in a parallel and communication-free way. A key question is whether a given distribution policy for the reshuffle is adequate for computing a g ...

ASSOC COMPUTING MACHINERY2019

RAQ: Relationship-Aware Graph Querying in Large Networks

Akhil Arora, Arnab Bhattacharya

The phenomenal growth of graph data from a wide variety of real-world applications has rendered graph querying to be a problem of paramount importance. Traditional techniques use structural as well as node similarities to find matches of a given query grap ...

ASSOC COMPUTING MACHINERY2019

Interactive Visual Exploration of Spatio-Temporal Urban Data Sets using Urbane

Anastasia Ailamaki, Eleni Tzirita Zacharatou, Haoqiong Bian

The recent explosion in the number and size of spatio-temporal data sets from urban environments and social sensors creates new opportunities for data-driven approaches to understand and improve cities. Visual analytics systems like Urbane aim to empower d ...

2018

Parallelizing Query Optimization on Shared-Nothing Architectures

Christoph Koch, Immanuel Trummer

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Assoc Computing Machinery2016

Efficient Incremental Data Analysis

Milos Nikolic

Many data-intensive applications require real-time analytics over streaming data. In a growing number of domains -- sensor network monitoring, social web applications, clickstream analysis, high-frequency algorithmic trading, and fraud detections to name a ...

EPFL2016

Fast Queries Over Heterogeneous Data Through Engine Customization

Anastasia Ailamaki, Ioannis Alagiannis, Manolis Karpathiotakis

Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of heterogeneous datasets to gain insights. The different data models and formats pose a significant challenge on performing anal ...

Assoc Computing Machinery2016

A Query Model to Capture Event Pattern Matching in RDF Stream Processing Query Languages

Jean Paul Calbimonte Perez

The current state of the art in RDF Stream Processing (RSP) proposes several models and implementations to combine Semantic Web technologies with Data Stream Management System (DSMS) operators like windows. Meanwhile, only a few solutions combine Semantic ...

Springer Int Publishing Ag2016

Smooth Scan: Statistics-Oblivious Access Paths

Anastasia Ailamaki, Renata Borovica-Gajic

Query optimizers depend heavily on statistics representing column distributions to create efficient query plans. In many cases, though, statistics are outdated or non-existent, and the process of refreshing statistics is very expensive, especially for ad-h ...

2015

Synthesizing Java Expressions from Free-Form Queries

Viktor Kuncak, Tihomir Gvero

We present a new code assistance tool for integrated development environments. Our system accepts as input free-form queries containing a mixture of English and Java, and produces Java code expressions that take the query into account and respect syntax, t ...

Assoc Computing Machinery2015

Solid-State Storage and Work Sharing for Efficient Scaleup Data Analytics

Manoussos Gavriil Athanassoulis

Today, managing, storing and analyzing data continuously in order to gain additional insight is becoming commonplace. Data analytics engines have been traditionally optimized for read-only queries assuming that the main data reside on mechanical disks. The ...

EPFL2014