Principle:Eventual Inc Daft Arrow Export
| Knowledge Sources | |
|---|---|
| Domains | Data_Engineering, Interoperability |
| Last Updated | 2026-02-08 00:00 GMT |
Overview
Technique for converting a Daft DataFrame to an Apache Arrow Table for zero-copy interoperability.
Description
Arrow export materializes a Daft DataFrame and converts it to a PyArrow Table, enabling efficient interop with Arrow-based libraries (DuckDB, Polars, etc.) without serialization overhead. Since Daft uses Apache Arrow as its internal columnar representation, this conversion can often avoid unnecessary data copies, making it the most efficient export path.
Usage
Use Arrow export when you need to pass data to Arrow-native libraries or perform zero-copy data exchange. Ideal for integration with DuckDB, Polars, or any system that natively consumes Arrow data.
Theoretical Basis
Direct columnar memory layout sharing through the Apache Arrow standard:
Daft DataFrame
-> to_arrow_iter(results_buffer_size=None)
-> Stream Arrow RecordBatches from all partitions
-> pyarrow.Table.from_batches(batches, schema)
-> pyarrow.Table
The Arrow columnar format provides a standardized in-memory layout that enables zero-copy data sharing between systems. Since Daft's internal representation is Arrow-compatible, the export avoids serialization/deserialization overhead.