Trino, the distributed SQL query engine formerly known as PrestoSQL, is engineered for high-performance, interactive analytics across a multitude of heterogeneous data sources.1 Its architecture is particularly well-suited for querying large datasets residing in data lakes, whether deployed on-premises using HDFS or in the cloud on object storage systems like Amazon S3, Google Cloud Storage, or Azure Blob Storage.2 A key capability enabling this is Trino's schema-on-read approach, allowing users to query data in various formats directly where it resides, without requiring upfront transformation and loading into a proprietary storage system.3
JSON (JavaScript Object Notation) has become ubiquitous in modern data ecosystems, frequently used for API payloads, application logs, configuration files, and semi-structured data exchange.7 However, querying JSON efficiently at scale presents significant challen