A Hive and SQL Case Study in Cloud Data Analytics

Shireesha Chandra; Aparna S. Varde; Jiayin Wang

doi:10.1109/UEMCON47517.2019.8992925

A Hive and SQL Case Study in Cloud Data Analytics

Shireesha Chandra, Aparna S. Varde, Jiayin Wang

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The digital universe is expanding at a very fast pace generating massive datasets. In order to keep up with the processing and storage needs for this big data, and to discover knowledge, we need scalable infrastructure and technologies that can access data from multiple disks simultaneously. Cloud computing provides paradigms for data analytics over such huge datasets. While SQL continues to be popular among database and data mining professionals, in recent years Hive has established itself as a rapidly advancing technology for big data which makes it highly suitable for use over the cloud. In this paper, we present investigatory research on Hive and SQL with a detailed case study between them, considering cloud data management and mining. Our work here constitutes a thorough scrutiny, focusing on processing Hive queries on cloud infrastructure considering three different approaches, and also delving into SQL processing on the cloud with similar approaches. Real datasets are used for conducting various operations using Hive and SQL. This paper conducts performance comparisons of the two technologies and explains the environment in which one is preferred over the other for processing and analyzing data. It provides recommendations for cloud data analytics, based on the case study.

Original language	English
Title of host publication	2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019
Editors	Satyajit Chakrabarti, Himadri Nath Saha
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	112-118
Number of pages	7
ISBN (Electronic)	9781728138855
DOIs	https://doi.org/10.1109/UEMCON47517.2019.8992925
State	Published - Oct 2019
Event	10th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019 - New York City, United States Duration: 10 Oct 2019 → 12 Oct 2019

Publication series

Name	2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019

Conference

Conference	10th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019
Country/Territory	United States
City	New York City
Period	10/10/19 → 12/10/19

Keywords

Big Data
Cloud Computing
Hadoop and Hive
Performance Comparisons
RDBMS and SQL

Access to Document

10.1109/UEMCON47517.2019.8992925

Cite this

Chandra, S., Varde, A. S., & Wang, J. (2019). A Hive and SQL Case Study in Cloud Data Analytics. In S. Chakrabarti, & H. N. Saha (Eds.), 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019 (pp. 112-118). [8992925] (2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UEMCON47517.2019.8992925

Chandra, Shireesha ; Varde, Aparna S. ; Wang, Jiayin. / A Hive and SQL Case Study in Cloud Data Analytics. 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019. editor / Satyajit Chakrabarti ; Himadri Nath Saha. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 112-118 (2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019).

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title = "A Hive and SQL Case Study in Cloud Data Analytics",

abstract = "The digital universe is expanding at a very fast pace generating massive datasets. In order to keep up with the processing and storage needs for this big data, and to discover knowledge, we need scalable infrastructure and technologies that can access data from multiple disks simultaneously. Cloud computing provides paradigms for data analytics over such huge datasets. While SQL continues to be popular among database and data mining professionals, in recent years Hive has established itself as a rapidly advancing technology for big data which makes it highly suitable for use over the cloud. In this paper, we present investigatory research on Hive and SQL with a detailed case study between them, considering cloud data management and mining. Our work here constitutes a thorough scrutiny, focusing on processing Hive queries on cloud infrastructure considering three different approaches, and also delving into SQL processing on the cloud with similar approaches. Real datasets are used for conducting various operations using Hive and SQL. This paper conducts performance comparisons of the two technologies and explains the environment in which one is preferred over the other for processing and analyzing data. It provides recommendations for cloud data analytics, based on the case study.",

keywords = "Big Data, Cloud Computing, Hadoop and Hive, Performance Comparisons, RDBMS and SQL",

author = "Shireesha Chandra and Varde, {Aparna S.} and Jiayin Wang",

year = "2019",

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doi = "10.1109/UEMCON47517.2019.8992925",

language = "English",

series = "2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Chandra, S, Varde, AS & Wang, J 2019, A Hive and SQL Case Study in Cloud Data Analytics. in S Chakrabarti & HN Saha (eds), 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019., 8992925, 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019, Institute of Electrical and Electronics Engineers Inc., pp. 112-118, 10th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019, New York City, United States, 10/10/19. https://doi.org/10.1109/UEMCON47517.2019.8992925

A Hive and SQL Case Study in Cloud Data Analytics. / Chandra, Shireesha; Varde, Aparna S.; Wang, Jiayin.

2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019. ed. / Satyajit Chakrabarti; Himadri Nath Saha. Institute of Electrical and Electronics Engineers Inc., 2019. p. 112-118 8992925 (2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Varde, Aparna S.

AU - Wang, Jiayin

PY - 2019/10

Y1 - 2019/10

N2 - The digital universe is expanding at a very fast pace generating massive datasets. In order to keep up with the processing and storage needs for this big data, and to discover knowledge, we need scalable infrastructure and technologies that can access data from multiple disks simultaneously. Cloud computing provides paradigms for data analytics over such huge datasets. While SQL continues to be popular among database and data mining professionals, in recent years Hive has established itself as a rapidly advancing technology for big data which makes it highly suitable for use over the cloud. In this paper, we present investigatory research on Hive and SQL with a detailed case study between them, considering cloud data management and mining. Our work here constitutes a thorough scrutiny, focusing on processing Hive queries on cloud infrastructure considering three different approaches, and also delving into SQL processing on the cloud with similar approaches. Real datasets are used for conducting various operations using Hive and SQL. This paper conducts performance comparisons of the two technologies and explains the environment in which one is preferred over the other for processing and analyzing data. It provides recommendations for cloud data analytics, based on the case study.

AB - The digital universe is expanding at a very fast pace generating massive datasets. In order to keep up with the processing and storage needs for this big data, and to discover knowledge, we need scalable infrastructure and technologies that can access data from multiple disks simultaneously. Cloud computing provides paradigms for data analytics over such huge datasets. While SQL continues to be popular among database and data mining professionals, in recent years Hive has established itself as a rapidly advancing technology for big data which makes it highly suitable for use over the cloud. In this paper, we present investigatory research on Hive and SQL with a detailed case study between them, considering cloud data management and mining. Our work here constitutes a thorough scrutiny, focusing on processing Hive queries on cloud infrastructure considering three different approaches, and also delving into SQL processing on the cloud with similar approaches. Real datasets are used for conducting various operations using Hive and SQL. This paper conducts performance comparisons of the two technologies and explains the environment in which one is preferred over the other for processing and analyzing data. It provides recommendations for cloud data analytics, based on the case study.

KW - Big Data

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KW - Hadoop and Hive

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 10 October 2019 through 12 October 2019

ER -

Chandra S, Varde AS , Wang J. A Hive and SQL Case Study in Cloud Data Analytics. In Chakrabarti S, Saha HN, editors, 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 112-118. 8992925. (2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019). doi: 10.1109/UEMCON47517.2019.8992925

A Hive and SQL Case Study in Cloud Data Analytics

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Keywords

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