AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS

Mehmet Turan; Emin Tenekeci; Kemal Güner

doi:10.54365/adyumbd.1508182

EN TR

AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS

Abstract

The use of GPU in different fields and its successful results initiate efforts to use GPU in database systems. It is also effective in distributed systems and computer networks in that accelerates computational tasks by leveraging parallel processing capabilities across multiple nodes and for tasks that require high computational power, such as network traffic analysis and real-time data processing. Digital transformation in all areas of life has led to the emergence of needs such as increased data diversity and faster data analysis. Upgrading the hardware capacity of the system or software-based studies are possible solutions to analyze this data for meeting the needs. In this study, Apache Spark and GPU performance differences are examined in commonly used SQL queries on big data. In this context, SQL queries such as grouping, sorting, and filtering, which are commonly used in data analysis, are used. While the queries performed with the GPU showed similar results in simple queries compared to the queries performed with Apache Spark, the GPU was completed 3x faster in queries requiring calculation.

Keywords

GPU , Apache Spark , Distributed Networking , Big Data , HPC

DAĞITIK AĞLAR İÇİN VERİ TABANI SQL SORGULARINDA APACHE SPARK VE GPU PERFORMANSLARININ ANALİZİ

Öz

Her geçen gün farklı bir alanda kullanılmaya başlanan ve başarılı sonuçlar sergileyen GPU’nun veri tabanlarında kullanılmasına yönelik çalışmalar giderek yaygınlaşmaktadır. Ayrıca dağıtık sistemlerde ve bilgisayar ağlarında da, birden fazla düğümde paralel işleme yeteneklerinden yararlanarak hesaplama görevlerini hızlandırmaya ve yüksek hesaplama gücü gerektiren ağ trafiği analizi, gerçek zamanlı veri işleme gibi görevlerde etkin olmaktadır. Hayatın her alanda gerçekleşen dijital dönüşüm veri çeşitliliğinde artış, verilerin daha hızlı analiz edilebilmesi vb. ihtiyaçların ortaya çıkmasına neden olmuştur. Bu verilerin analizi için sistem donanım kapasitesinin artırılması veya yazılım temelli çalışmalar ile ihtiyaçların karşılanabilmesine yönelik çözümler bulunmaktadır. Bu çalışmada ise büyük verilerde Apache Spark ve GPU’nun yaygın olarak kullanılan SQL sorgularındaki performans farklılıkları incelenmiştir. Bu kapsamda veri analizinde genel olarak kullanılan gruplandırma, sıralama ve filtreleme gibi SQL sorguları kullanılmıştır. GPU ile gerçekleştirilen sorguların Apache Spark ile gerçekleştirilen sorgulara göre basit sorgularda benzer sonuçlar sergilerken, hesaplama gerektiren sorgularda GPU’nun 3x kadar daha kısa sürede sonuçlandırmıştır.

Anahtar Kelimeler

GPU , Apache Spark , Dağıtık Ağlar , HPC , Büyük Veri

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Bilgisayar Görüşü ve Çoklu Ortam Hesaplama (Diğer) , Eşzamanlı / Paralel Sistemler ve Teknolojiler , Performans Değerlendirmesi , Yüksek Performanslı Hesaplama , Makine Öğrenme (Diğer)

Bölüm

Araştırma Makalesi

Yazarlar

Mehmet Turan
0000-0002-8038-0749
Türkiye

Emin Tenekeci
0000-0001-5944-4704
Türkiye

Kemal Güner ^*
0000-0003-3495-9044
Türkiye

Erken Görünüm Tarihi

29 Aralık 2024

Yayımlanma Tarihi

31 Aralık 2024

Gönderilme Tarihi

1 Temmuz 2024

Kabul Tarihi

3 Ekim 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 11 Sayı: 24

DOI

https://doi.org/10.54365/adyumbd.1508182

IZ

https://izlik.org/JA68JG97SN

APA

Turan, M., Tenekeci, E., & Güner, K. (2024). AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 11(24), 428-437. https://doi.org/10.54365/adyumbd.1508182

AMA

1.Turan M, Tenekeci E, Güner K. AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2024;11(24):428-437. doi:10.54365/adyumbd.1508182

Chicago

Turan, Mehmet, Emin Tenekeci, ve Kemal Güner. 2024. “AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 11 (24): 428-37. https://doi.org/10.54365/adyumbd.1508182.

EndNote

Turan M, Tenekeci E, Güner K (01 Aralık 2024) AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 11 24 428–437.

IEEE

[1]M. Turan, E. Tenekeci, ve K. Güner, “AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS”, Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, c. 11, sy 24, ss. 428–437, Ara. 2024, doi: 10.54365/adyumbd.1508182.

ISNAD

Turan, Mehmet - Tenekeci, Emin - Güner, Kemal. “AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 11/24 (01 Aralık 2024): 428-437. https://doi.org/10.54365/adyumbd.1508182.

JAMA

1.Turan M, Tenekeci E, Güner K. AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2024;11:428–437.

MLA

Turan, Mehmet, vd. “AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, c. 11, sy 24, Aralık 2024, ss. 428-37, doi:10.54365/adyumbd.1508182.

Vancouver

1.Mehmet Turan, Emin Tenekeci, Kemal Güner. AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 01 Aralık 2024;11(24):428-37. doi:10.54365/adyumbd.1508182

AN ANALYSIS OF APACHE SPARK AND GPU PERFORMANCES ON DATABASE SQL QUERIES FOR DISTRIBUTED NETWORKS

Abstract

Keywords

DAĞITIK AĞLAR İÇİN VERİ TABANI SQL SORGULARINDA APACHE SPARK VE GPU PERFORMANSLARININ ANALİZİ

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Erken Görünüm Tarihi

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster