Big data analysis on yelp user-generated reviews

Denish K Kalariya, Shubham Vyas, Dev Savasni, Samir Patel
{"title":"Big data analysis on yelp user-generated reviews","authors":"Denish K Kalariya, Shubham Vyas, Dev Savasni, Samir Patel","doi":"10.1109/ICONAT53423.2022.9726108","DOIUrl":null,"url":null,"abstract":"The goal of this project is to demostrate the use of PySpark and Spark SQL to query and analyze the Yelp Open Dataset. Specifically, the aim is to analyze the Yelp Reviews dataset, which consists of 8.6 million user-generated reviews of businesses on Yelp. we also perform JOIN operations with the Yelp Business and Yelp User datasets to describe relations between review ratings and characteristics of the business, such as geographic location. To perform some of these queries, we demonstrate the use of user-defined functions (UDFs) in Spark SQL queries. Lastly, we briefly examine how partitioning of the underlying data abstraction changes computational speed.","PeriodicalId":377501,"journal":{"name":"2022 International Conference for Advancement in Technology (ICONAT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference for Advancement in Technology (ICONAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONAT53423.2022.9726108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The goal of this project is to demostrate the use of PySpark and Spark SQL to query and analyze the Yelp Open Dataset. Specifically, the aim is to analyze the Yelp Reviews dataset, which consists of 8.6 million user-generated reviews of businesses on Yelp. we also perform JOIN operations with the Yelp Business and Yelp User datasets to describe relations between review ratings and characteristics of the business, such as geographic location. To perform some of these queries, we demonstrate the use of user-defined functions (UDFs) in Spark SQL queries. Lastly, we briefly examine how partitioning of the underlying data abstraction changes computational speed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
yelp用户评论的大数据分析
这个项目的目标是演示使用PySpark和Spark SQL来查询和分析Yelp开放数据集。具体来说,目的是分析Yelp评论数据集,该数据集由Yelp上860万用户生成的企业评论组成。我们还对Yelp Business和Yelp User数据集执行JOIN操作,以描述评论评级和业务特征(如地理位置)之间的关系。为了执行其中一些查询,我们将演示在Spark SQL查询中使用用户定义函数(udf)。最后,我们简要地研究了底层数据抽象的划分如何改变计算速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Data Security Using Multiple Image Steganography and Hybrid Data Encryption Techniques Analysis of Signal Integrity in Coupled MWCNT and Comparison with Copper Interconnects Operational Constraints Governed Loadability Characteristics of EHV/UHV Transmission Lines Gait Step Length Classification Using Force Myography Face Recognition utilizing Novel Face Descriptor & Algorithm of Feature Extraction
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1