Publications associées à MapReduce

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

Scalable Robust Graph Embedding with Spark

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong, Trung-Dung Hoang

Graph embedding aims at learning a vector-based representation of vertices that incorporates the structure of the graph. This representation then enables inference of graph properties. Existing graph embedding techniques, however, do not scale well to larg ...

ASSOC COMPUTING MACHINERY2021

Communication trade-offs for Local-SGD with large step size

Aymeric Daphnis Kévin Dieuleveut

Synchronous mini-batch SGD is state-of-the-art for large-scale distributed machine learning. However, in practice, its convergence is bottlenecked by slow communication rounds between worker nodes. A natural solution to reduce communication is to use the " ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

Formal Approaches to Querying Big Data in Shared-Nothing Systems

Bas Ketsman

To meet today's data management needs, it is a widespread practice to use distributed data storage and processing systems. Since the publication of the MapReduce paradigm, a plethora of such systems arose, but although widespread, the capabilities of these ...

ASSOC COMPUTING MACHINERY2019

System Support for Efficient Replication in Distributed Systems

Dragos-Adrian Seredinschi

Current online applications, such as search engines, social networks, or file sharing services, execute across a distributed network of machines. They provide non-stop services to their users despite failures in the underlying network. To achieve such a hi ...

EPFL2019

Compilation Techniques for Incremental Collection Processing

Daniel Lupei

Many map-reduce frameworks as well as NoSQL systems rely on collection programming as their interface of choice due to its rich semantics along with an easily parallelizable set of primitives. Unfortunately, the potential of collection programming is not ...

EPFL2017

Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop

Adrien Raphaël Depeursinge

Many medical image analysis tasks require complex learning strategies to reach a quality of image-based decision support that is sufficient in clinical practice. The analysis of medical texture in tomographic images, for example of lung tissue, is no excep ...

2016

High Performance Transaction Processing on Non-Uniform Hardware Topologies

Danica Porobic

Transaction processing is a mission critical enterprise application that runs on high-end servers. Traditionally, transaction processing systems have been designed for uniform core-to-core communication latencies. In the past decade, with the emergence of ...

EPFL2016

SigCO: Mining Significant Correlations via a Distributed Real-time Computation Engine

Karl Aberer, Jean Paul Calbimonte Perez, Tian Guo, Hao Zhuang

The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...

2015

Online indexing and distributed querying model-view sensor data in the cloud

Karl Aberer, Tian Guo, Hao Zhuang

As various kinds of sensors penetrate our daily life (e.g., sensor networks for environmental monitoring, GPS for localization and navigation), the efficient management of massive amount of sensor data becomes increasingly important at present. Many sensor ...

Springer-Verlag Berlin2014

DiNoDB: Efficient Large-Scale Raw Data Analytics

Anastasia Ailamaki, Marko Vukolic, Ioannis Alagiannis, Erietta Liarou, Yongchao Tian

Modern big data workflows, found in e.g., machine learning use cases, often involve iterations of cycles of batch analytics and interactive analytics on temporary data. Whereas batch analytics solutions for large volumes of raw data are well established (e ...

2014

Near Optimal Work-Stealing Tree Scheduler for Highly Irregular Data-Parallel Workloads

Martin Odersky, Aleksandar Prokopec

We present a work-stealing algorithm for runtime scheduling of data-parallel operations in the context of shared-memory architectures on data sets with highly-irregular workloads that are not known a priori to the scheduler. This scheduler can parallelize ...

Springer-Verlag Berlin2014

Spatiotemporal Coherence Tracking

Mohammad Alisafaee

Chip-multiprocessors require a coherence directory to track data sharing and order accesses to the shared data. Scaling coherence directories to support a large number of cores is challenging due to excessive area requirements of the directories. The state ...

2012

Model Checking of Distributed Algorithm Implementations

Maysam Yabandeh

It is notoriously difficult to develop reliable, high-performance distributed systems that run over asynchronous networks. Even if a distributed system is based on a well-understood distributed algorithm, its implementation can contain errors arising from ...

EPFL2011

Adaptive query execution for data management in the cloud

Anastasia Ailamaki, Debabrata Dash, Adrian Daniel Popescu

A major component of many cloud services is query processing on data stored in the underlying cloud cluster. The traditional techniques for query processing on a cluster are those offered by parallel DBMS. These techniques however, cannot guarantee high pe ...

ACM Press2010

PaxosInside

Rachid Guerraoui, Maysam Yabandeh

Amodernmanycore architecture can be viewed as a distributed system with explicit message passing to communicate between cores. Ensuring the consistency of shared state replicated over several cores is the key to the well functioning of such a system. Yet, ...

2010

Making Cluster Applications Energy-Aware

Dejan Kostic, Nedeljko Vasic, Vincent Salzgeber, Martin Barisits

Power consumption has become a critical issue in large scale clusters. Existing solutions for addressing the servers' energy consumption suggest ``shrinking'' the set of active machines, at least until the more power-proport-ional hardware devices become a ...

2009

Streaming of Scalable Video from Multiple Servers using Rateless Codes

Pascal Frossard, Jean-Paul Wagner

This paper presents a framework for efficiently streaming scalable video from multiple servers over heterogeneous network paths. We propose to use rateless codes, or Fountain codes, such that each server acts as an independent source, without the need to c ...

2006