scholarly journals Correction to: Data dependencies for query optimization: a survey

2021 ◽  
Author(s):  
Jan Kossmann ◽  
Thorsten Papenbrock ◽  
Felix Naumann
Keyword(s):  
Query Optimization ◽  
Data Dependencies

scholarly journals Data dependencies for query optimization: a survey

2021 ◽  
Author(s):  
Jan Kossmann ◽  
Thorsten Papenbrock ◽  
Felix Naumann
Keyword(s):  
Query Optimization ◽  
Relational Database ◽  
Database Management ◽  
Optimization Techniques ◽  
Database Management System ◽  
Database Queries ◽  
Data Dependencies ◽  
Open Research ◽  
Core Feature ◽  
Research Questions

AbstractEffective query optimization is a core feature of any database management system. While most query optimization techniques make use of simple metadata, such as cardinalities and other basic statistics, other optimization techniques are based on more advanced metadata including data dependencies, such as functional, uniqueness, order, or inclusion dependencies. This survey provides an overview, intuitive descriptions, and classifications of query optimization and execution strategies that are enabled by data dependencies. We consider the most popular types of data dependencies and focus on optimization strategies that target the optimization of relational database queries. The survey supports database vendors to identify optimization opportunities as well as DBMS researchers to find related work and open research questions.

Multi-dimensional query optimization algorithm for bitmap index with binning

2010 ◽  
Vol 30 (8) ◽  
pp. 2013-2016 ◽  
Author(s):  
Li-ming WANG ◽  
Xiao CHENG ◽  
Yu-mei CHAI
Keyword(s):  
Query Optimization ◽  
Optimization Algorithm ◽  
Bitmap Index

A Query Optimization Method Based on User Profiles Reasoning

2011 ◽  
Vol 30 (1) ◽  
pp. 33-37
Author(s):  
Xiang Mei ◽  
Xiang-wu Meng ◽  
Jun-Liang Chen ◽  
Meng Xu
Keyword(s):  
Query Optimization ◽  
Optimization Method ◽  
User Profiles

An Optimal Framework for Spatial Query Optimization Using Hadoop in Big Data Analytics

2019 ◽  
Vol 12 ◽  
Author(s):  
Pankaj Dadheech ◽  
Dinesh Goyal ◽  
Sumit Srivastava ◽  
Ankit Kumar
Keyword(s):  
Big Data ◽  
Query Optimization ◽  
Spatial Data ◽  
Spatial Information ◽  
Big Data Analytics ◽  
Spatial Query ◽  
Data Process ◽  
Boolean Queries ◽  
Spatial Query Optimization ◽  
Hadoop System

Spatial queries frequently used in Hadoop for significant data process. However, vast and massive size of spatial information makes it difficult to process the spatial inquiries proficiently, so they utilized the Hadoop system for process Big Data. We have used Boolean Queries & Geometry Boolean Spatial Data for Query Optimization using Hadoop System. In this paper, we show a lightweight and adaptable spatial data index for big data which will process in Hadoop frameworks. Results demonstrate the proficiency and adequacy of our spatial ordering system for various spatial inquiries.

scholarly journals Query Rewriting for Incremental Continuous Query Evaluation in HIFUN

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 149
Author(s):  
Petros Zervoudakis ◽  
Haridimos Kondylakis ◽  
Nicolas Spyratos ◽  
Dimitris Plexousakis
Keyword(s):  
Query Optimization ◽  
Query Language ◽  
Computational Cost ◽  
Continuous Queries ◽  
Continuous Query ◽  
Query Rewriting ◽  
Query Evaluation ◽  
Clear Separation ◽  
Complete Dataset ◽  
High Level

HIFUN is a high-level query language for expressing analytic queries of big datasets, offering a clear separation between the conceptual layer, where analytic queries are defined independently of the nature and location of data, and the physical layer, where queries are evaluated. In this paper, we present a methodology based on the HIFUN language, and the corresponding algorithms for the incremental evaluation of continuous queries. In essence, our approach is able to process the most recent data batch by exploiting already computed information, without requiring the evaluation of the query over the complete dataset. We present the generic algorithm which we translated to both SQL and MapReduce using SPARK; it implements various query rewriting methods. We demonstrate the effectiveness of our approach in temrs of query answering efficiency. Finally, we show that by exploiting the formal query rewriting methods of HIFUN, we can further reduce the computational cost, adding another layer of query optimization to our implementation.

A cost model for NDP-aware query optimization for KV-stores

2021 ◽  
Author(s):  
Christian Knödler ◽  
Tobias Vinçon ◽  
Arthur Bernhardt ◽  
Ilia Petrov ◽  
Leonardo Solis-Vasquez ◽  
...  
Keyword(s):  
Query Optimization ◽  
Cost Model

scholarly journals A Survey of Software-Defined Networks-on-Chip: Motivations, Challenges and Opportunities

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 183
Author(s):  
Jose Ricardo Gomez-Rodriguez ◽  
Remberto Sandoval-Arechiga ◽  
Salvador Ibarra-Delgado ◽  
Viktor Ivan Rodriguez-Abdala ◽  
Jose Luis Vazquez-Avila ◽  
...  
Keyword(s):  
Single Chip ◽  
Synthesis Time ◽  
Networks On Chip ◽  
Data Dependencies ◽  
Layered Architecture ◽  
Systems On Chip ◽  
Challenges And Opportunities ◽  
Computing Platforms ◽  
On Chip ◽  
Many Core

Current computing platforms encourage the integration of thousands of processing cores, and their interconnections, into a single chip. Mobile smartphones, IoT, embedded devices, desktops, and data centers use Many-Core Systems-on-Chip (SoCs) to exploit their compute power and parallelism to meet the dynamic workload requirements. Networks-on-Chip (NoCs) lead to scalable connectivity for diverse applications with distinct traffic patterns and data dependencies. However, when the system executes various applications in traditional NoCs—optimized and fixed at synthesis time—the interconnection nonconformity with the different applications’ requirements generates limitations in the performance. In the literature, NoC designs embraced the Software-Defined Networking (SDN) strategy to evolve into an adaptable interconnection solution for future chips. However, the works surveyed implement a partial Software-Defined Network-on-Chip (SDNoC) approach, leaving aside the SDN layered architecture that brings interoperability in conventional networking. This paper explores the SDNoC literature and classifies it regarding the desired SDN features that each work presents. Then, we described the challenges and opportunities detected from the literature survey. Moreover, we explain the motivation for an SDNoC approach, and we expose both SDN and SDNoC concepts and architectures. We observe that works in the literature employed an uncomplete layered SDNoC approach. This fact creates various fertile areas in the SDNoC architecture where researchers may contribute to Many-Core SoCs designs.

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