| # |
| # 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.testing.connectutils import ReusedConnectTestCase |
| from pyspark.testing.utils import have_graphviz, graphviz_requirement_message |
| |
| |
| class SparkConnectDataFrameDebug(ReusedConnectTestCase): |
| def test_df_debug_basics(self): |
| df = self.spark.range(100).repartition(10).groupBy("id").count() |
| x = df.collect() # noqa: F841 |
| ei = df.executionInfo |
| |
| root, graph = ei.metrics.extract_graph() |
| self.assertIn(root, graph, "The root must be rooted in the graph") |
| |
| def test_df_quey_execution_empty_before_execution(self): |
| df = self.spark.range(100).repartition(10).groupBy("id").count() |
| ei = df.executionInfo |
| self.assertIsNone(ei, "The query execution must be None before the action is executed") |
| |
| def test_df_query_execution_with_writes(self): |
| df = self.spark.range(100).repartition(10).groupBy("id").count() |
| df.write.save("/tmp/test_df_query_execution_with_writes", format="json", mode="overwrite") |
| ei = df.executionInfo |
| self.assertIsNotNone( |
| ei, "The query execution must be None after the write action is executed" |
| ) |
| |
| def test_query_execution_text_format(self): |
| df = self.spark.range(100).repartition(10).groupBy("id").count() |
| df.collect() |
| self.assertIn("HashAggregate", df.executionInfo.metrics.toText()) |
| |
| # Different execution mode. |
| df = self.spark.range(100).repartition(10).groupBy("id").count() |
| df.toPandas() |
| self.assertIn("HashAggregate", df.executionInfo.metrics.toText()) |
| |
| @unittest.skipIf(not have_graphviz, graphviz_requirement_message) |
| def test_df_query_execution_metrics_to_dot(self): |
| df = self.spark.range(100).repartition(10).groupBy("id").count() |
| x = df.collect() # noqa: F841 |
| ei = df.executionInfo |
| |
| dot = ei.metrics.toDot() |
| source = dot.source |
| self.assertIsNotNone(dot, "The dot representation must not be None") |
| self.assertGreater(len(source), 0, "The dot representation must not be empty") |
| self.assertIn("digraph", source, "The dot representation must contain the digraph keyword") |
| self.assertIn("Metrics", source, "The dot representation must contain the Metrics keyword") |
| |
| |
| if __name__ == "__main__": |
| from pyspark.sql.tests.connect.test_df_debug import * # noqa: F401 |
| |
| try: |
| import xmlrunner # type: ignore |
| |
| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) |
| except ImportError: |
| testRunner = None |
| unittest.main(testRunner=testRunner, verbosity=2) |