Query CSV, Parquet, and JSON files with SQL for aggregations and joins.
npx skills add https://github.com/malue-ai/dazee-small --skill duckdb-sql-malue-ai
Please help me install this Agent Skill. Skill: duckdb-sql Source: https://github.com/malue-ai/dazee-small/tree/main/skills/library/duckdb-sql Command: npx skills add https://github.com/malue-ai/dazee-small --skill duckdb-sql-malue-ai
This Skill allows users to query data directly from files like CSV, Parquet, and JSON using SQL, eliminating the need for traditional database setup and data import processes.
sales.csv to find the total revenue per category, or join orders.csv with customers.csv to find high-value orders.Use the duckdb-sql skill to count the number of rows in the file 'data.csv'.
High-intent search queries and answers about installing and using this skill.
You can query CSV and Parquet files directly with SQL using an in-memory analytical engine. This approach eliminates traditional database setup and data import processes, allowing you to run complex aggregations immediately.
Yes, you can join data across multiple CSV files using SQL JOIN operations. This allows you to combine data from multiple files, such as joining orders with customers, without importing them into a relational database.
Analyzing large JSON datasets is best handled by an in-memory analytical SQL engine that queries files directly. This method efficiently processes large-scale data that might be slow for other tools.
Yes, DuckDB supports wildcard file matching for querying multiple Parquet files. This allows you to perform large-scale data analysis across many files simultaneously using SQL.
No, you do not need to install a database to run SQL aggregations on local data files. You can use an in-memory analytical engine to run complex aggregations directly on CSV, Parquet, and JSON files.
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