Topic
Spark (mathematics)
About: Spark (mathematics) is a research topic. Over the lifetime, 7304 publications have been published within this topic receiving 63322 citations.
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13 Oct 1981TL;DR: In this paper, information is derived from two given sets of sensor output pulses relating to crankshaft position for use in determining the proper cylinder to be fired, the spark time and the dwell.
Abstract: Information is derived from two given sets of sensor output pulses relating to crankshaft position for use in determining the proper cylinder to be fired, the spark time and the dwell. The spark is enabled only after the crankshaft position is known, and noise, including the spark itself, is prevented from interfering with the system operation.
23 citations
26 Aug 2015
TL;DR: This paper analyzes the shortcomings of classical Apriori algorithm, then improves it by constructing a new data structure and optimizing the prepruning step, and proposes the SIAP algorithms.
Abstract: Apriori algorithm is one of the classical algorithm in the association rule mining field, this paper analyzes the shortcomings of classical Apriori algorithm, then improves it by constructing a new data structure and optimizing the prepruning step. Based on the improved Apriori algorithm and combined with the Spark support for fine-grained data processing, we elaborate the idea of the improved Apriori algorithm's parallel processing, and propose the SIAP algorithms. We experimented by comparing with the Apriori algorithms based on Hadoop and the Apriori algorithms based on Spark, and the results show that the SIAP algorithm has a higher efficiency.
23 citations
TL;DR: In this paper, the authors propose an online query processing for large-scale, incremental data analysis on a distributed stream processing engine (DSPE), which converts any SQL-like query to an incremental DSPE program automatically.
Abstract: This paper addresses online query processing for large-scale, incremental data analysis on a distributed stream processing engine (DSPE). Our goal is to convert any SQL-like query to an incremental DSPE program automatically. In contrast to other approaches, we derive incremental programs that return accurate results, not approximate answers, by retaining a minimal state during the query evaluation lifetime and by using a novel incremental evaluation technique, which, at each time interval, returns an accurate snapshot answer that depends on the current state and the latest batches of data. Our methods can handle many forms of queries on nested data collections, including iterative and nested queries, group-by with aggregation, and equi-joins. Finally, we report on a prototype implementation of our framework, called MRQL Streaming, running on top of Spark and we experimentally validate the effectiveness of our methods.
23 citations
11 May 2010-Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment
TL;DR: Fermilab began exploring the technologies for vertically integrated circuits (also commonly known as 3D circuits) in 2006 as discussed by the authors, which include through silicon vias (TSV), circuit thinning, and bonding techniques to replace conventional bump bonds.
Abstract: Fermilab began exploring the technologies for vertically integrated circuits (also commonly known as 3D circuits) in 2006. These technologies include through silicon vias (TSV), circuit thinning, and bonding techniques to replace conventional bump bonds. Since then, the interest within the High Energy Physics community has grown considerably. This paper will present an overview of the activities at Fermilab over the last 3 years which have helped spark this interest.
23 citations