108 citations · 267 across the 14 of their papers we have counts for
13 papers · 1 filter
CADENZA: Compiling Natural-Language Intent into Task-Specific Operator DAGs for Semantic Query Processing
Jaehyun Ha, Yongjoo Park, Wook-Shin Han
Semantic query processing engines (SQPEs) extend relational query processing with semantic operators that are executed via model inference over unstructured data. Optimizing such q…
CADENZA in Action: Breaking the Monolith with Intent-Dependent Plan Spaces for Semantic Queries
Jaehyun Ha, Yongjoo Park, Wook-Shin Han
Semantic query processing engines execute semantic operators, whose behavior is specified by natural-language intents, via model inference over multimodal data. Most existing optim…
PBE Meets LLM: When Few Examples Aren't Few-Shot Enough
Shuning Zhang, Yongjoo Park
Large language models (LLMs) can generate code from natural language descriptions. Their performance is typically evaluated using programming benchmarks that simulate real-world ta…
AirIndex: Versatile Index Tuning Through Data and Storage
Supawit Chockchowwat, Wenjie Liu, Yongjoo Park
The end-to-end lookup latency of a hierarchical index -- such as a B-tree or a learned index -- is determined by its structure such as the number of layers, the kinds of branching…
Transactional Python for Durable Machine Learning: Vision, Challenges, and Feasibility
Supawit Chockchowwat, Zhaoheng Li, Yongjoo Park
In machine learning (ML), Python serves as a convenient abstraction for working with key libraries such as PyTorch, scikit-learn, and others. Unlike DBMS, however, Python applicati…
S/C: Speeding up Data Materialization with Bounded Memory
Zhaoheng Li, Xinyu Pi, Yongjoo Park
With data pipeline tools and the expressiveness of SQL, managing interdependent materialized views (MVs) are becoming increasingly easy. These MVs are updated repeatedly upon new d…
A Step Toward Deep Online Aggregation (Extended Version)
Nikhil Sheoran, Supawit Chockchowwat, Arav Chheda +3
For exploratory data analysis, it is often desirable to know what answers you are likely to get before actually obtaining those answers. This can potentially be achieved by designi…
Automatically Finding Optimal Index Structure
Supawit Chockchowwat, Wenjie Liu, Yongjoo Park
Existing learned indexes (e.g., RMI, ALEX, PGM) optimize the internal regressor of each node, not the overall structure such as index height, the size of each layer, etc. In this p…
Airphant: Cloud-oriented Document Indexing
Supawit Chockchowwat, Chaitanya Sood, Yongjoo Park
Modern data warehouses can scale compute nodes independently of storage. These systems persist their data on cloud storage, which is always available and cost-efficient. Ad-hoc com…
QuickSel: Quick Selectivity Learning with Mixture Models
Yongjoo Park, Shucheng Zhong, Barzan Mozafari
Estimating the selectivity of a query is a key step in almost any cost-based query optimizer. Most of today's databases rely on histograms or samples that are periodically refreshe…
VerdictDB: Universalizing Approximate Query Processing
Yongjoo Park, Barzan Mozafari, Joseph Sorenson +1
Despite 25 years of research in academia, approximate query processing (AQP) has had little industrial adoption. One of the major causes of this slow adoption is the reluctance of…
Database Learning: Toward a Database that Becomes Smarter Every Time
Yongjoo Park, Ahmad Shahab Tajik, Michael Cafarella +1
In today's databases, previous query answers rarely benefit answering future queries. For the first time, to the best of our knowledge, we change this paradigm in an approximate qu…
Visualization-Aware Sampling for Very Large Databases
Yongjoo Park, Michael Cafarella, Barzan Mozafari
Interactive visualizations are crucial in ad hoc data exploration and analysis. However, with the growing number of massive datasets, generating visualizations in interactive times…