PGCAS: A Parallelized Graph Clustering Algorithm Based on Spark

Liu, Dongjiang

doi:10.1007/978-3-030-28061-1_20

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Parallel Clustering Algorithm For Special Dataset1

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2020

2023

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Cited by 2 publications

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“…In addition to the high-dimensional data, there are also parallel clustering methods [81,82] for the streaming data realized by Spark streaming and parallel clustering methods [83][84][85][86] for the graph data realized by Spark graph x, which expands the types of the dataset that can be parallel clustered based on Spark. e comparison of key features of various algorithms is shown in Table 1.…”

Section: Parallel Clustering Algorithm For Special Datasetmentioning

confidence: 99%

A Survey of Parallel Clustering Algorithms Based on Spark

Xiao

2020

Scientific Programming

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Clustering is one of the most important unsupervised machine learning tasks, which is widely used in information retrieval, social network analysis, image processing, and other fields. With the explosive growth of data, the classical clustering algorithms cannot meet the requirements of clustering for big data. Spark is one of the most popular parallel processing platforms for big data, and many researchers have proposed many parallel clustering algorithms based on Spark. In this paper, the existing parallel clustering algorithms based on Spark are classified and summarized, the parallel design framework of each kind of algorithms is discussed, and after comparing different kinds of algorithms, the direction of the future research is discussed.

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