Exploiting Sharing Join Opportunities in Big Data Multiquery Optimization with Flink
Multiway join queries incur high-cost I/Os operations over large-scale data. Exploiting sharing join opportunities among multiple multiway joins could be beneficial to reduce query execution time and shuffled intermediate data. Although multiway join optimization has been carried out in MapReduce, d...
Saved in:
Main Authors: | Xiao-Yan Gao, Radhya Sahal, Gui-Xiu Chen, Mohammed H. Khafagy, Fatma A. Omara |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/6617149 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Integration of Multi-Source Landslide Disaster Data Based on Flink Framework and APSO Load Balancing Task Scheduling
by: Zongmin Wang, et al.
Published: (2024-12-01) -
Supporting Efficient Family Joins for Big Data Tables via Multiple Freedom Family Index
by: Qiang Zhu, et al.
Published: (2025-01-01) -
Identifying Opportunities for Exploiting Cross-Layer Interactions in Adaptive Wireless Systems
by: Troy Weingart, et al.
Published: (2007-01-01) -
Explainable Artificial Intelligence (XAI) to Enhance Trust Management in Intrusion Detection Systems Using Decision Tree Model
by: Basim Mahbooba, et al.
Published: (2021-01-01) -
Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models
by: Basim Mahbooba, et al.
Published: (2021-01-01)