| # 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. |
| |
| import pyarrow |
| import pyarrow.compute |
| import datafusion |
| from datafusion import udaf, Accumulator |
| from datafusion import col |
| |
| |
| class MyAccumulator(Accumulator): |
| """ |
| Interface of a user-defined accumulation. |
| """ |
| |
| def __init__(self): |
| self._sum = pyarrow.scalar(0.0) |
| |
| def update(self, values: pyarrow.Array) -> None: |
| # not nice since pyarrow scalars can't be summed yet. This breaks on `None` |
| self._sum = pyarrow.scalar( |
| self._sum.as_py() + pyarrow.compute.sum(values).as_py() |
| ) |
| |
| def merge(self, states: pyarrow.Array) -> None: |
| # not nice since pyarrow scalars can't be summed yet. This breaks on `None` |
| self._sum = pyarrow.scalar( |
| self._sum.as_py() + pyarrow.compute.sum(states).as_py() |
| ) |
| |
| def state(self) -> pyarrow.Array: |
| return pyarrow.array([self._sum.as_py()]) |
| |
| def evaluate(self) -> pyarrow.Scalar: |
| return self._sum |
| |
| |
| # create a context |
| ctx = datafusion.SessionContext() |
| |
| # create a RecordBatch and a new DataFrame from it |
| batch = pyarrow.RecordBatch.from_arrays( |
| [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])], |
| names=["a", "b"], |
| ) |
| df = ctx.create_dataframe([[batch]]) |
| |
| my_udaf = udaf( |
| MyAccumulator, |
| pyarrow.float64(), |
| pyarrow.float64(), |
| [pyarrow.float64()], |
| "stable", |
| ) |
| |
| df = df.aggregate([], [my_udaf(col("a"))]) |
| |
| result = df.collect()[0] |
| |
| assert result.column(0) == pyarrow.array([6.0]) |