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Export to Apache Arrow

All results of a query can be exported to an Apache Arrow Table using the to_arrow_table function. Alternatively, results can be returned as a RecordBatchReader using the to_arrow_reader function and results can be read one batch at a time. In addition, relations built using DuckDB's Relational API can also be exported.

Deprecated The fetch_arrow_table, fetch_record_batch, and fetch_arrow_reader functions are deprecated. Use to_arrow_table and to_arrow_reader instead.

Export to an Arrow Table 

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").to_arrow_table()

Export as a RecordBatchReader 

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").to_arrow_reader(chunk_size)

for batch in result:
    # 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 DuckDBPyRelation.to_arrow_table, and to an Arrow record batch reader using DuckDBPyRelation.to_arrow_reader.

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()

# Calculate a result using that relation and export that result to Arrow
res = rel.aggregate("sum(i)").execute()
arrow_table = res.to_arrow_table()

# You can also create an Arrow record batch reader from a relation
arrow_batch_reader = res.to_arrow_reader()
for batch in arrow_batch_reader:
    # Process a single chunk here
    print(batch.to_pandas())
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