SparkBench – A Spark Performance Testing Suite-Reference-Cited by-同舟云学术

SparkBench – A Spark Performance Testing Suite

Published:2016 Issue: Volume: Page:26-44
ISSN:0302-9743
Container-title:Performance Evaluation and Benchmarking: Traditional to Big Data to Internet of Things
language:
Short-container-title:

Author:

Agrawal Dakshi,Butt Ali,Doshi Kshitij,Larriba-Pey Josep-L.,Li Min,Reiss Frederick R,Raab Francois,Schiefer Berni,Suzumura Toyotaro,Xia Yinglong

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-31409-9_3

Reference29 articles.

1. DataBricks. https://databricks.com/

2. Mahout. http://mahout.apache.org/

3. Lecture Notes in Computer Science;K Huppler,2009

4. Lecture Notes in Computer Science;P Boncz,2014

5. Jacob, B., Mudge, T.N.: Notes on calculating computer performance. University of Michigan, Computer Science and Engineering Division, Department of Electrical Engineering and Computer Science (1995)

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Tiny-Tasks Granularity Trade-Off: Balancing Overhead Versus Performance in Parallel Systems;IEEE Transactions on Parallel and Distributed Systems;2023-04-01

2. A comprehensive study and review of tuning the performance on database scalability in big data analytics;Journal of Intelligent & Fuzzy Systems;2023-03-09

3. UPLIFT;Proceedings of the VLDB Endowment;2022-07

4. Adaptive Code Learning for Spark Configuration Tuning;2022 IEEE 38th International Conference on Data Engineering (ICDE);2022-05

5. SPBench: a framework for creating benchmarks of stream processing applications;Computing;2022-01-10