Appraising SPARK on Large-Scale Social Media Analysis

被引：2

作者：

Belcastro, Loris ^{[1
]}

Marozzo, Fabrizio ^{[1
]}

Talia, Domenico ^{[1
]}

Trunfio, Paolo ^{[1
]}

机构：

[1] Univ Calabria, DIMES, Arcavacata Di Rende, Italy

来源：

EURO-PAR 2017: PARALLEL PROCESSING WORKSHOPS | 2018年 / 10659卷

关键词：

Social data analysis; Scalability; Spark Cloud computing; Parallel library; Big Data; PATTERNS;

D O I：

10.1007/978-3-319-75178-8_39

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Software systems for social media analysis provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a Java library for developing parallel data analysis applications based on the extraction of useful knowledge from social media data. This library aims at reducing the programming skills necessary to implement scalable social data analysis applications. This work describes how the ParSoDA library has been extended to execute applications on Apache Spark. Using a cluster of 12 workers, the Spark version of the library reduces the execution time of two case study applications exploiting social media data up to 42%, compared to the Hadoop version of the library.

引用

页码：483 / 495

页数：13

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