Search results for "Spark"
showing 4 items of 124 documents
Mining Maximal Frequent Patterns in Transactional Databases and Dynamic Data Streams: A Spark-based Approach
2018
Mining maximal frequent patterns (MFPs) in transactional databases (TDBs) and dynamic data streams (DDSs) is substantially important for business intelligence. MFPs, as the smallest set of patterns, help to reveal customers’ purchase rules and market basket analysis (MBA). Although, numerous studies have been carried out in this area, most of them extend the main-memory based Apriori or FP-growth algorithms. Therefore, these approaches are not only unscalable but also lack parallelism. Consequently, ever increasing big data sources requirements cannot be met. In addition, mining performance in some existing approaches degrade drastically due to the presence of null transactions. We, therefo…
Administration of Second-Generation Extracorporeal Shock Waves without Waterbath for Fragmentation of Extra- and Intrahepatic Bile Duct Stones
1990
First-generation extracorporeal shock-wave sources disintegrate 97% of kidney stones [1, 2]. Recently, in selected patients gallbladder and common bile duct stones were also treated. The technique available so far, however, requires immersion of the patient’s body in a tank of degassed water. The procedure is therefore inconvenient, time consuming, and relatively expensive. The high pressure of shocks (up to 1000 bar) generated by underwater spark discharge causes pain, and general anesthesia is necessary in most patients [3, 4].
Microbial resources and sparkling wine differentiation : state of the arts
2022
Consumers’ increasing interest in sparkling wine has enhanced the global market’s demand. The pro-technological yeasts strains selected for the formulation of microbial starter cultures are a fundamental parameter for exalting the quality and safety of the final product. Nowadays, the management of the employed microbial resource is highly requested by stakeholders, because of the increasing economic importance of this oenological sector. Here, we report an overview of the production processes of sparkling wine and the main characterisation criteria to select Saccharomyces and non-Saccharomyces strains appropriate for the preparation of commercial starter cultures dedicated to the primary a…
Scalable implementation of dependence clustering in Apache Spark
2017
This article proposes a scalable version of the Dependence Clustering algorithm which belongs to the class of spectral clustering methods. The method is implemented in Apache Spark using GraphX API primitives. Moreover, a fast approximate diffusion procedure that enables algorithms of spectral clustering type in Spark environment is introduced. In addition, the proposed algorithm is benchmarked against Spectral clustering. Results of applying the method to real-life data allow concluding that the implementation scales well, yet demonstrating good performance for densely connected graphs. peerReviewed