Publication

Scalable Delivery of Stream Query Result

Publications associées (30)

Building Efficient Query Engines using High-Level Languages

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

Integration of a Real-Time Node for Magnetic Perturbations Signal Analysis in the Distributed Digital Control System of the TCV Tokamak

Basil Duval, Xavier Llobet, Jean-Marc Moret, Olivier Sauter, Stefano Coda, Duccio Testa, Cristian Galperti

This paper presents the integration of an acquisition and computing unit capable of acquiring and processing fast magnetic signals in real time in the control system of the tokamak a configuration variabile tokamak. All aspects of system integration and te ...

2017

No data left behind: real-time insights from a complex data ecosystem

Anastasia Ailamaki, Manolis Karpathiotakis

The typical enterprise data architecture consists of several actively updated data sources (e.g., NoSQL systems, data warehouses), and a central data lake such as HDFS, in which all the data is periodically loaded through ETL processes. To simplify query p ...

2017

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

Parallelizing Query Optimization on Shared-Nothing Architectures

Immanuel Trummer, Christoph Koch

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

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

Scaling Up Concurrent Analytical Workloads on Multi-Core Servers

Iraklis Psaroudakis

Today, an ever-increasing number of researchers, businesses, and data scientists collect and analyze massive amounts of data in database systems. The database system needs to process the resulting highly concurrent analytical workloads by exploiting modern ...

EPFL2016

Synthesizing efficient systems in probabilistic environments

Barbara Jobstmann, David Parker

We present a formalism, algorithms and tools to synthesise reactive systems that behave efficiently, i.e., which achieve an optimal trade-off between a given cost and reward model. Synthesis aims to automatically generate a program from a specification. Mo ...

Springer2016

From Massive Parallelization to Quantum Computing: Seven Novel Approaches to Query Optimization

Immanuel Trummer

The goal of query optimization is to map a declarative query (describing data to generate) to a query plan (describing how to generate the data) with optimal execution cost. Query optimization is required to support declarative query interfaces. It is a co ...

EPFL2016

Toward timely, predictable and cost-effective data analytics

Renata Borovica-Gajic

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

EPFL2016