d80tb7 commented on a change in pull request #24981: [SPARK-27463][PYTHON] Support Dataframe Cogroup via Pandas UDFs URL: https://github.com/apache/spark/pull/24981#discussion_r315754866
########## File path: python/pyspark/sql/tests/test_pandas_udf_cogrouped_map.py ########## @@ -0,0 +1,285 @@ +# +# 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 datetime +import unittest +import sys + +from collections import OrderedDict +from decimal import Decimal + +from pyspark.sql import Row +from pyspark.sql.functions import array, explode, col, lit, udf, sum, pandas_udf, PandasUDFType +from pyspark.sql.types import * +from pyspark.testing.sqlutils import ReusedSQLTestCase, have_pandas, have_pyarrow, \ + pandas_requirement_message, pyarrow_requirement_message +from pyspark.testing.utils import QuietTest + +if have_pandas: + import pandas as pd + from pandas.util.testing import assert_frame_equal, assert_series_equal + +if have_pyarrow: + import pyarrow as pa + + +""" +Tests below use pd.DataFrame.assign that will infer mixed types (unicode/str) for column names +from kwargs w/ Python 2, so need to set check_column_type=False and avoid this check +""" +if sys.version < '3': + _check_column_type = False +else: + _check_column_type = True + + +@unittest.skipIf( + not have_pandas or not have_pyarrow, + pandas_requirement_message or pyarrow_requirement_message) +class CoGroupedMapPandasUDFTests(ReusedSQLTestCase): + + @property + def data1(self): + return self.spark.range(10).toDF('id') \ + .withColumn("ks", array([lit(i) for i in range(20, 30)])) \ + .withColumn("k", explode(col('ks')))\ + .withColumn("v", col('k') * 10)\ + .drop('ks') + + @property + def data2(self): + return self.spark.range(10).toDF('id') \ + .withColumn("ks", array([lit(i) for i in range(20, 30)])) \ + .withColumn("k", explode(col('ks'))) \ + .withColumn("v2", col('k') * 100) \ + .drop('ks') + + def test_simple(self): + self._test_merge(self.data1, self.data2) + + def test_left_group_empty(self): + left = self.data1.where(col("id") % 2 == 0) + self._test_merge(left, self.data2) + + def test_right_group_empty(self): + right = self.data2.where(col("id") % 2 == 0) + self._test_merge(self.data1, right) + + def test_different_schemas(self): + right = self.data2.withColumn('v3', lit('a')) + self._test_merge(self.data1, right, 'id long, k int, v int, v2 int, v3 string') + + def test_complex_group_by(self): + left = pd.DataFrame.from_dict({ + 'id': [1, 2, 3], + 'k': [5, 6, 7], + 'v': [9, 10, 11] + }) + + right = pd.DataFrame.from_dict({ + 'id': [11, 12, 13], + 'k': [5, 6, 7], + 'v2': [90, 100, 110] + }) + + left_df = self.spark\ Review comment: yes- that's better- done. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
