duckdb-processor-builder

Building a TPC-H query processor competitive with DuckDB requires end-to-end scaffolding including dataset generation scripts, benchmarking infrastructure with a one-command runner, DuckDB baseline integration, validation tooling, and templates for reports and slides to ensure correctness and completeness.

Generating TPC-H datasets for single-thread query benchmarking requires specialized scripts that produce standardized data for benchmarking against a DuckDB baseline. This skill provides dataset generation scripts within its project skeleton to automate this preparation step.

Yes, this TPC-H processor workflow supports university database courses like CS465 by providing end-to-end project scaffolding, benchmarking infrastructure, and deliverable templates for reports and presentations. It is explicitly designed for educational scenarios requiring production-grade data-engineering pipelines.

Validating query correctness when benchmarking against DuckDB requires dedicated validation tooling that compares your processor's output against the DuckDB baseline. This skill includes validation infrastructure alongside its one-command runner to ensure your TPC-H queries return correct results.

Yes, this skill supports single-thread query processing for TPC-H benchmarks by providing specialized benchmarking infrastructure and a DuckDB baseline for comparison. It enables developers to measure and optimize single-thread query performance within a production-grade workflow.

The best way to scaffold an end-to-end data engineering pipeline for Parquet data is using a one-command runner that generates the project skeleton, dataset generation scripts, and benchmarking infrastructure. This skill automates that scaffolding specifically for TPC-H processors competing with DuckDB.