EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Jul 30·5 min read
Paging Through a Parquet File in DuckDB: File_row_number or Offset?
TL;DR
A method for efficiently paging through large Parquet files in DuckDB was developed, allowing for scalable data retrieval without exceeding API limits. This approach ensures each request is self-contained and reconstructible by any worker.
✦ Why It Matters
Implement paging in your data retrieval processes to manage large datasets without hitting API limits.
Key Takeaways
- Use file_row_number for faster paging through large Parquet files.
- Check the number of row groups in your Parquet file before optimizing.
- Avoid using OFFSET without ORDER BY to prevent data integrity issues.
- Consider streaming responses to bypass API size limits.
How It Works
DuckDB's file_row_number option allows users to specify a range of physical row positions, enabling the database to skip entire row groups when retrieving data. This method leverages the structure of Parquet files, which are organized into row groups, allowing for efficient access without decompressing unnecessary data.