43 citations · 50 across the 12 of their papers we have counts for
16 papers
Learned spatial data partitioning
Keizo Hori, Yuya Sasaki, Daichi Amagata +2
Due to the significant increase in the size of spatial data, it is essential to use distributed parallel processing systems to efficiently analyze spatial data. In this paper, we f…
GuP: Fast Subgraph Matching by Guard-based Pruning
Junya Arai, Yasuhiro Fujiwara, Makoto Onizuka
Subgraph matching, which finds subgraphs isomorphic to a query, is the key to information retrieval from data represented as a graph. To avoid redundant exploration in the data, ex…
A Simple and Scalable Graph Neural Network for Large Directed Graphs
Seiji Maekawa, Yuya Sasaki, Makoto Onizuka
Node classification is one of the hottest tasks in graph analysis. Though existing studies have explored various node representations in directed and undirected graphs, they have o…
Scardina: Scalable Join Cardinality Estimation by Multiple Density Estimators
Ryuichi Ito, Yuya Sasaki, Chuan Xiao +1
In recent years, machine learning-based cardinality estimation methods are replacing traditional methods. This change is expected to contribute to one of the most important applica…
NoSQL Schema Design for Time-Dependent Workloads
Yusuke Wakuta, Michael Mior, Teruyoshi Zenmyo +2
In this paper, we propose a schema optimization method for time-dependent workloads for NoSQL databases. In our proposed method, we migrate schema according to changing workloads,…
Journey of Migrating Millions of Queries on The Cloud
Taro L. Saito, Naoki Takezoe, Yukihiro Okada +11
Treasure Data is processing millions of distributed SQL queries every day on the cloud. Upgrading the query engine service at this scale is challenging because we need to migrate a…