• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.747-754
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• 2004

Database administrators should be aware of performance characteristics of database systems in order to manage database system effectively. The usages of system resources in database systems could be quite different under database workloads. The objective of this paper is to identify and analyze performance characteristics of database systems in different workloads, which could help database tuners tune database systems Under the TPC-C and TPC-W workloads, which represent typical workloads of online transaction processing and electronic commerce respectively, we investigated usage types of resource that are determined by fourteen performance indicator, and are behaved in response to changes of four tuning parameters (data buffer, private memory, I/O process, shared memory). Eight out of the fourteen performance indicators cleary show the performance differences under the workloads. Changes of data buffer parameter give a influences to database system. The tuning parameter that affects the system performance significantly is the database buffer size in the both workloads.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1041-1048
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• 2004

Database logs contain various information on database operations, but they are used to recover database systems from failures generally. This paper proposes a log analysis tool that provides useful information for database tuning. This tool provides users with information on work-load organization, database schemas, and resources usages of queries. This paper describes the tool in views of its architecture, functions, implementation, and verification. The tool is verified by running the TPC-W benchmark, and representative analysis results are also presented.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.400-410
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• 2008

Flash memory has been widely used in mobile devices, such as mobile phone and digital camera. Recently flash SSD(Solid State Disk), having same interface of the disk drive, is replacing the hard disk of some laptop computers. However, flash memory still cannot be considered as the storage of database systems. The FTL(Flash Translation Layer) of commercial flash SSD, making flash memory operate exactly same as a hard disk, shows poor performance on the workload of databases with many random overwrites. Recently In-Page Logging(IPL) approach was proposed to solve this problem. In this paper, we implement IPL approach on SQLite, a popular open source embedded DBMS, and evaluate its performance. It improves the performance by up to 30 factors for update queries.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.369-376
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• 2002

Although LRU is not adequate for database that has non-uniform reference pattern, it has been adopted in most database systems due to the absence of the proper alternative. We analyze database block reference pattern with the realistic database trace. Based on this analysis, we propose a new cache replacement policy. Trace analysis shows that extremely non-popular blocks take up about 70 % of the entire blocks. The influence of recency on blocks' re-reference likelihood is at first strong due to temporal locality, however, it rapidly decreases and eventually becomes negligible as stack distance increases. Based on this observation, RCB(Reference Characteristic Based) cache replacement policy, which we propose in this paper, classifies the entire blocks into four block groups by blocks' recency and re-reference likelihood, and operates different priority evaluation methods for each block group. RCB policy evicts non-popular blocks more quickly than the others and evaluates the priority of the block by frequency that has not been referenced for a long time. In a trace-driven simulation, RCB delivers a better performance than the existing polices(LRU, 2Q, LRU-K, LRFU). Especially compared to LRU. It reduces miss count by 5~l2.7%. Time complexity of RCB is O(1), which is the same with LRU and 2Q and superior to LRU-K(O(log$_2$N)) and LRFU(O(l) ~ O(log$_2$N)).

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.133-140
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• 2007

Flash memory has penetrated our life in various forms. For example, flash memory is important storage component of ubiquitous computing or mobile products such as cell phone, MP3 player, PDA, and portable storage kits. Behind of the wide acceptance as memory is many advantages of flash memory: for instances, low power consumption, nonvolatile, stability and portability. In addition to mentioned strengths, the recent development of gigabyte range capacity flash memory makes a careful prediction that the flash memory might replace some of storage area dominated by hard disks. In order to have overwriting function, one block must be erased before overwriting is performed. This difference results in the cost of reading, writing and erasing in flash memory[1][5][6]. Since this difference has not been considered in traditional buffer replacement technologies adopted in system software such as OS and DBMS, a new buffer replacement strategy becomes necessary. In this paper, a new buffer replacement strategy, reflecting difference I/O cost and applicable to flash memory, suggest and compares with other buffer replacement strategies using workloads as Zipfian distribution and real data.