Yuya Ebihara is a seasoned back-end engineer and open-source maintainer with 11 years of experience, focused on query engines and table formats for data lakehouse architectures. As a Trino maintainer, Apache Polaris committer, and contributor to Apache Iceberg, he drives connector improvements and engine features that make large-scale SQL on data lakes more reliable and performant. At Starburst and previously LINE and Teradata, he shipped features from GROUP BY AUTO and set-operation extensions to deletion-vector support and Spark expression conversion, bridging query semantics with storage formats. His contributions include fixing core Parquet metrics, DynamoDB integrations for Iceberg, and enhancing the Trino Python client with DBAPI executemany support—demonstrating attention to both runtime correctness and developer ergonomics. Based in Japan, he combines production-grade engineering with deep open-source collaboration across projects like Trino, Iceberg, Presto and Coral. A less obvious strength: he routinely moves work across layers—from compiler/expression improvements to connector and client tooling—so optimizations translate end-to-end.
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Role in this project:
Back-end Developer
Contributions:6094 reviews, 192 commits, 3858 PRs in 8 months
Contributions summary:Yuya's contributions primarily involve enhancing the Iceberg and Delta Lake connectors within the Trino project. They worked on implementing support for complex data types in the Iceberg connector and improving functionality within the Delta Lake connector, specifically related to deletion vectors and partition filtering. Additionally, the user implemented `streamRelationColumns` and contributed code to support the addition of new features in both Iceberg and Delta Lake.
Contributions:199 reviews, 22 commits, 62 PRs in 2 years 6 months
Contributions summary:Yuya primarily focused on enhancing the functionality and testing of the Trino Python client. Their contributions involved integrating with the Trino ecosystem, demonstrated by their use of official Docker images for testing. They also added support for the `executemany` method in the DBAPI, expanding the client's database interaction capabilities. Furthermore, the user worked on improving the test suite by using Trino JSON responses and bumping the client version.
data-analyticspythondbmssingerpython-client
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