--- layout: docu redirect_from: - /docs/guides/python/export_arrow title: Export to Apache Arrow --- All results of a query can be exported to an [Apache Arrow Table](https://arrow.apache.org/docs/python/generated/pyarrow.Table.html) using the `fetch_arrow_table` function. Alternatively, results can be returned as a [RecordBatchReader](https://arrow.apache.org/docs/python/generated/pyarrow.ipc.RecordBatchStreamReader.html) using the `arrow` function and results can be read one batch at a time. In addition, relations built using DuckDB's [Relational API]({% link docs/stable/guides/python/relational_api_pandas.md %}) can also be exported. ## Export to an Arrow Table ```python import duckdb import pyarrow as pa my_arrow_table = pa.Table.from_pydict({'i': [1, 2, 3, 4], 'j': ["one", "two", "three", "four"]}) # query the Apache Arrow Table "my_arrow_table" and return as an Arrow Table results = duckdb.sql("SELECT * FROM my_arrow_table").fetch_arrow_table() ``` ## Export as a RecordBatchReader ```python import duckdb import pyarrow as pa my_arrow_table = pa.Table.from_pydict({'i': [1, 2, 3, 4], 'j': ["one", "two", "three", "four"]}) # query the Apache Arrow Table "my_arrow_table" and return as an Arrow RecordBatchReader chunk_size = 1_000_000 result = duckdb.sql("SELECT * FROM my_arrow_table").arrow(chunk_size) # Loop through the results. A StopIteration exception is thrown when the RecordBatchReader is empty while (batch := result.read_next_batch()): # Process a single chunk here print(batch.to_pandas()) ``` ## Export from Relational API Arrow objects can also be exported from the Relational API. A relation can be converted to an Arrow table using either the `DuckDBPyRelation.fetch_arrow_table` or `DuckDBPyRelation.to_arrow_table` function, and to an Arrow record batch reader using either the `DuckDBPyRelation.arrow` or `DuckDBPyRelation.fetch_arrow_reader` function. ```python import duckdb # connect to an in-memory database con = duckdb.connect() con.execute('CREATE TABLE integers (i integer)') con.execute('INSERT INTO integers VALUES (0), (1), (2), (3), (4), (5), (6), (7), (8), (9), (NULL)') # Create a relation from the table and export the entire relation as Arrow rel = con.table("integers") relation_as_arrow = rel.to_arrow_table() # or .fetch_arrow_table() # Calculate a result using that relation and export that result to Arrow res = rel.aggregate("sum(i)").execute() arrow_table = res.to_arrow_table() # or .fetch_arrow_table() # You can also create an Arrow record batch reader from a relation arrow_batch_reader = res.arrow() # or .fetch_arrow_reader() while (batch := arrow_batch_reader.read_next_batch()): # Process a single chunk here print(batch.to_pandas()) ```