DBToaster: higher-order delta processing for dynamic, frequently fresh views
Publications associées (32)
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Is the human brain wired for wealth? The setting is the high-velocity financial environment. Undoubtedly, the development of sophisticated derivative instruments has improved the allocation of risk across economies, highlighting the nexus between banking a ...
Applications ranging from algorithmic trading to scientific data analysis require realtime analytics based on views over databases that change at very high rates. Such views have to be kept fresh at low maintenance cost and latencies. At the same time, the ...
The explosion of available data in the last few years has increased the importance of physical database design, since the selection of proper physical structures (e.g. indices, partitions and materialized views) may improve query execution performance by s ...
This paper calls for a new breed of lightweight systems - dynamic data management systems (DDMS). In a nutshell, a DDMS manages large dynamic data structures with agile, frequently fresh views, and provides a facility for monitoring these views and trigger ...
With technological advances, the sources of available information have become more and more diverse. Recently, a new source of information has gained growing importance: sensor data. Sensors are devices sensing their environment in various ways and reporti ...
Conventional data warehouses employ the query- at-a-time model, which maps each query to a distinct physical plan. When several queries execute concurrently, this model introduces contention and thrashing, because the physical plans—unaware of each other—c ...
We present DBToaster, a novel query compilation framework for producing high performance compiled query executors that incrementally and continuously answer standing aggregate queries using in-memory views. DBToaster targets applications that require effic ...
Conventional data warehouses employ the query-at-a-time model, which maps each query to a distinct physical plan. When several queries execute concurrently, this model introduces contention, because the physical plans—unaware of each other—compete for acce ...
We design and deploy a trading strategy that mirrors the Exchange Traded Fund (ETF) arbitrage technique for sector trading. Artificial Neural Networks (ANNs) are used to capture pricing relationships within a sector using intra-day trade data. The fair pric ...
Nowadays, sensor data is generated in large amounts. Stor- ing or transmitting all the sensor’s measurements might not be the ideal choice because of the volume (and rate) at which it is generated. But we also cannot easily discard it, since ev- ery data m ...