| # |
| # 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 unittest |
| |
| from pyspark.sql.functions import udf |
| from pyspark.sql.tests.test_udf import BaseUDFTestsMixin |
| from pyspark.testing.sqlutils import ( |
| have_pandas, |
| have_pyarrow, |
| pandas_requirement_message, |
| pyarrow_requirement_message, |
| ReusedSQLTestCase, |
| ) |
| |
| |
| @unittest.skipIf( |
| not have_pandas or not have_pyarrow, pandas_requirement_message or pyarrow_requirement_message |
| ) |
| class PythonUDFArrowTests(BaseUDFTestsMixin, ReusedSQLTestCase): |
| @classmethod |
| def setUpClass(cls): |
| super(PythonUDFArrowTests, cls).setUpClass() |
| cls.spark.conf.set("spark.sql.execution.pythonUDF.arrow.enabled", "true") |
| |
| @unittest.skip("Unrelated test, and it fails when it runs duplicatedly.") |
| def test_broadcast_in_udf(self): |
| super(PythonUDFArrowTests, self).test_broadcast_in_udf() |
| |
| @unittest.skip("Unrelated test, and it fails when it runs duplicatedly.") |
| def test_register_java_function(self): |
| super(PythonUDFArrowTests, self).test_register_java_function() |
| |
| @unittest.skip("Unrelated test, and it fails when it runs duplicatedly.") |
| def test_register_java_udaf(self): |
| super(PythonUDFArrowTests, self).test_register_java_udaf() |
| |
| @unittest.skip("Struct input types are not supported with Arrow optimization") |
| def test_udf_input_serialization_valuecompare_disabled(self): |
| super(PythonUDFArrowTests, self).test_udf_input_serialization_valuecompare_disabled() |
| |
| def test_nested_input_error(self): |
| with self.assertRaisesRegexp( |
| Exception, "NotImplementedError: Struct input type are not supported" |
| ): |
| self.spark.range(1).selectExpr("struct(1, 2) as struct").select( |
| udf(lambda x: x)("struct") |
| ).collect() |
| |
| def test_complex_input_types(self): |
| row = ( |
| self.spark.range(1) |
| .selectExpr("array(1, 2, 3) as array", "map('a', 'b') as map") |
| .select( |
| udf(lambda x: str(x))("array"), |
| udf(lambda x: str(x))("map"), |
| ) |
| .first() |
| ) |
| |
| # The input is NumPy array when the optimization is on. |
| self.assertEquals(row[0], "[1 2 3]") |
| self.assertEquals(row[1], "{'a': 'b'}") |
| |
| |
| if __name__ == "__main__": |
| from pyspark.sql.tests.test_arrow_python_udf import * # noqa: F401 |
| |
| try: |
| import xmlrunner |
| |
| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) |
| except ImportError: |
| testRunner = None |
| unittest.main(testRunner=testRunner, verbosity=2) |