Flash technology trends have shown that greater densities between flash memory cells increase read/write error rates and shorten solid-state drive (SSD) device lifetimes. This is critical for enterprise systems, causing such problems as service instability and increased total cost of ownership (TCO) because of SSD replacement. Therefore, numerous studies have focused on decreasing the amount of the DBMS writes. However, there has been no research that focused on decreasing the amount of temporary writes, which are primarily created by join processing. In DBMSs, there are two major join-processing algorithms, i.e., hybrid hash join (HHJ) and sort merge join (SMJ), proven to be the best according to DBMS workload; however, the two algorithms produce temporary writes of intermediate results. Therefore, we instead look to the block-nested loop join (BNLJ); it is well-known that the two algorithms are better than BNLJ, but BNLJ creates no intermediate result writes. It is reasonable to use BNLJ for a major join algorithm if its performance can be enhanced similar to those of HHJ and SMJ, considering BNLJ's advantage of extending SSD lifetimes. Therefore, in this paper, we propose an advanced BNLJ (ANLJ) algorithm that can match the performance of the two main join algorithms.
|Number of pages||14|
|Journal||IEEE Transactions on Knowledge and Data Engineering|
|Publication status||Published - 2017 Apr 1|
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Computational Theory and Mathematics