Make Wayang More Datalake-Friendly

Apache Wayang currently supports batch engines (Spark, Flink) and OLTP databases via JDBC, but lacks integration with modern data lake engines — Trino, BigQuery, Dremio, and AWS Athena — where most analytical workloads now run. This project integrates these engines into Wayang's optimizer and executor through a shared JDBC Template abstraction layer, so each new engine inherits common infrastructure (connection management, SQL assembly, channel conversions) and only overrides engine-specific behavior. The deliverables are: (1) platform, executor, and plugin implementations for Trino, BigQuery, Dremio, and Athena; (2) operator mappings that translate Wayang logical operators (filter, projection, aggregate, join) into engine-native SQL; (3) per-engine cost models calibrated via TPC-H benchmarks so the optimizer can score data lake engines against Spark/Postgres alternatives; (4) end-to-end demo pipelines and contributor documentation. The approach has already been verified with working Trino, BigQuery, and Dremio demonstrations for table scan, filter, and projection operators.