| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| from __future__ import annotations |
| |
| import pyarrow as pa |
| from datafusion import SessionContext, col, udaf |
| from datafusion_ffi_example import MySumUDF |
| |
| |
| def setup_context_with_table(): |
| ctx = SessionContext() |
| |
| # Pick numbers here so we get the same value in both groups |
| # since we cannot be certain of the output order of batches |
| batch = pa.RecordBatch.from_arrays( |
| [ |
| pa.array([1, 2, 3, None], type=pa.int64()), |
| pa.array([1, 1, 2, 2], type=pa.int64()), |
| ], |
| names=["a", "b"], |
| ) |
| ctx.register_record_batches("test_table", [[batch]]) |
| return ctx |
| |
| |
| def test_ffi_aggregate_register(): |
| ctx = setup_context_with_table() |
| my_udaf = udaf(MySumUDF()) |
| ctx.register_udaf(my_udaf) |
| |
| result = ctx.sql("select my_custom_sum(a) from test_table group by b").collect() |
| |
| assert len(result) == 2 |
| assert result[0].num_columns == 1 |
| |
| result = [r.column(0) for r in result] |
| expected = [ |
| pa.array([3], type=pa.int64()), |
| pa.array([3], type=pa.int64()), |
| ] |
| |
| assert result == expected |
| |
| |
| def test_ffi_aggregate_call_directly(): |
| ctx = setup_context_with_table() |
| my_udaf = udaf(MySumUDF()) |
| |
| result = ( |
| ctx.table("test_table").aggregate([col("b")], [my_udaf(col("a"))]).collect() |
| ) |
| |
| assert len(result) == 2 |
| assert result[0].num_columns == 2 |
| |
| result = [r.column(1) for r in result] |
| expected = [ |
| pa.array([3], type=pa.int64()), |
| pa.array([3], type=pa.int64()), |
| ] |
| |
| assert result == expected |