duckdb-analytics

DuckDB analytics can be protected from out-of-memory errors by configuring explicit memory limits. This Skill automates memory-aware analytics by setting memory limits for OOM protection, optionally utilizing psutil for dynamic memory sizing to ensure stability.

To benchmark query performance on large datasets, you run ClickBench-style benchmarks. This Skill automates performance benchmarking to evaluate query execution times on big data, providing repeatable metrics for analytical workloads.

Yes, you can export DuckDB query results to Parquet, CSV, and JSON formats. This Skill provides an export_analytics_report function that writes analytic outputs to these formats, enabling downstream reporting and data sharing.

No, psutil is an optional dependency for memory management. This Skill configures DuckDB memory limits by default, but can optionally use psutil-based memory sizing to dynamically allocate resources based on available system memory.

The best way to establish a memory-safe DuckDB connection is using a dedicated Python API. This Skill exposes a get_connection function that initializes DuckDB with configured memory limits, ensuring repeatable and memory-safe analytics.