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

Publications associées (67)

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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

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

Interleaving with Coroutines: A Practical Approach for Robust Index Joins

Anastasia Ailamaki, Georgios Psaropoulos

Index join performance is determined by the efficiency of the lookup operation on the involved index. Although database indexes are highly optimized to leverage processor caches, main memory accesses inevitably increase lookup runtime when the index outsiz ...

VLDB Endowment Inc.2017

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...

2017

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

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

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

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

Visual Patterns Discovery in Large Databases of Paintings

Frédéric Kaplan, Isabella Di Lenardo, Benoît Laurent Auguste Seguin

The digitization of large databases of works of arts photographs opens new avenue for research in art history. For instance, collecting and analyzing painting representations beyond the relatively small number of commonly accessible works was previously ex ...

2016

Fast Queries Over Heterogeneous Data Through Engine Customization

Anastasia Ailamaki, Manolis Karpathiotakis, Ioannis Alagiannis

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