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Chanho Jeong

dblp:243/2367 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Query processing and optimization · 75% Database system architecture and tuning · 25%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization
iterative query processing
0.412019
Iterative Query Processing based on Unified Optimization Techniques · SIGMOD Conference 2019
Query processing and optimization
cost model
0.112019
Iterative Query Processing based on Unified Optimization Techniques · SIGMOD Conference 2019

Methods — techniques the papers use, named apart from their topics

visualization · 0.4end-to-end graph · 0.4query motion · 0.4loop-invariant code motion · 0.4
YearPublicationVenuePosition
2020 ProcAnalyzer: Effective Code Analyzer for Tuning Imperative Programs in SAP HANA
abstract
Troubleshooting imperative programs at runtime is very challenging because the final optimized plan is quite different from the original design time model. In this demonstration, we present ProcAnalyzer, an expressive and intuitive tool for troubleshooting issues related to performance, code quality, and security. We propose end-to-end graph (E2EGraph) that provides a holistic view of design time, compile time, and runtime behavior so that end users and engine developers easily find the correlations between design time and runtime. ProcAnalyzer provides suggestions and visualization to find problematic statements through the E2EGraph.
Kisung Park 0001, Taeyoung Jeong, Chanho Jeong, Jaeha Lee, Donghun Lee 0001, Young-Koo Lee
SIGMOD Conference3
2019 Iterative Query Processing based on Unified Optimization Techniques
abstract
Hybrid transactional and analytical processing (HTAP) systems like SAP HANA make it much simpler to manage both operational load and analytical queries without ETL, separate data warehouses, et al. To represent both transactional and analytical business logic in a single database system, stored procedures are often used to express analytical queries using control flow logic and DMLs. Optimizing these complex procedures requires a fair knowledge of imperative programming languages as well as the declarative query language. Therefore, unified optimization techniques considering both program and query optimization techniques are essential for achieving optimal query performance. In this paper, we propose a novel unified optimization technique for efficient iterative query processing. We present a notion of query motion that allows the movement of SQL queries in and out of a loop. Additionally, we exploit a new cost model that measures the quality of the execution plan with consideration for queries and loop iterations. We describe our experimental evaluation that demonstrates the benefit of our technique using both a standard decision support benchmark and real-world workloads. An extensive evaluation shows that our unified optimization technique enumerates plans that achieve performance improvements of up to an order of magnitude faster than plans generated by the existing loop-invariant code motion technique.
Kisung Park 0001, Hojin Seo, Mostofa Kamal Rasel, Young-Koo Lee, Chanho Jeong, Sung Yeol Lee, Chungmin Lee, Donghun Lee 0001
SIGMOD Conference5