About projection-selection-join queries addressed to possibilistic relational databases

2005 ◽  
Vol 13 (1) ◽  
pp. 124-139 ◽  
Author(s):  
P. Bosc ◽  
O. Pivert
Keyword(s):  
Relational Databases ◽  
Join Queries

scholarly journals Supporting top-k join queries in relational databases

2004 ◽  
Vol 13 (3) ◽  
Author(s):  
IhabF. Ilyas ◽  
WalidG. Aref ◽  
AhmedK. Elmagarmid
Keyword(s):  
Relational Databases ◽  
Join Queries

scholarly journals Supporting Top-k Join Queries in Relational Databases

2003 ◽  
pp. 754-765 ◽  
Author(s):  
Ihab F. Ilyas ◽  
Walid G. Aref ◽  
Ahmed K. Elmagarmid
Keyword(s):  
Relational Databases ◽  
Join Queries

XML Modeling of Fuzzy Data with Relational Databases

2011 ◽  
Vol 34 (2) ◽  
pp. 291-303 ◽  
Author(s):  
Li YAN ◽  
Zong-Min MA ◽  
Jian LIU ◽  
Fu ZHANG
Keyword(s):  
Relational Databases ◽  
Fuzzy Data

scholarly journals Bloom Filter-Based Parallel Architecture for Accelerating Equi-Join Operation on FPGA

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1778
Author(s):  
Binhao He ◽  
Meiting Xue ◽  
Shubiao Liu ◽  
Wei Luo
Keyword(s):  
Relational Databases ◽  
Parallel Architecture ◽  
Operation Time ◽  
Bloom Filter ◽  
Search Tree ◽  
Binary Search Tree ◽  
Maximum Acceleration ◽  
Data Intensive ◽  
Match Rate ◽  
Field Programmable

As one of the most important operations in relational databases, the join is data-intensive and time-consuming. Thus, offloading this operation using field-programmable gate arrays (FPGAs) has attracted much interest and has been broadly researched in recent years. However, the available SRAM-based join architectures are often resource-intensive, power-consuming, or low-throughput. Besides, a lower match rate does not lead to a shorter operation time. To address these issues, a Bloom filter (BF)-based parallel join architecture is presented in this paper. This architecture first leverages the BF to discard the tuples that are not in the join result and classifies the remaining tuples into different channels. Second, a binary search tree is used to reduce the number of comparisons. The proposed method was implemented on a Xilinx FPGA, and the experimental results show that under a match rate of 50%, our architecture achieved a high join throughput of 145.8 million tuples per second and a maximum acceleration factor of 2.3 compared to the existing SRAM-based join architectures.

Sign in / Sign up

Export Citation Format

Share Document