python/pyspark/testing/sqlutils.py - spark - Git at Google

 #
 # 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 glob
 import math
 import os
 import shutil
 import tempfile
 from contextlib import contextmanager

 from pyspark.find_spark_home import _find_spark_home
 from pyspark.sql import SparkSession
 from pyspark.sql.types import Row
 from pyspark.testing.utils import (
     PySparkErrorTestUtils,
     ReusedPySparkTestCase,
 )

 SPARK_HOME = _find_spark_home()


 def search_jar(project_relative_path, sbt_jar_name_prefix, mvn_jar_name_prefix, return_first=False):
     # Note that 'sbt_jar_name_prefix' and 'mvn_jar_name_prefix' are used since the prefix can
     # vary for SBT or Maven specifically. See also SPARK-26856
     project_full_path = os.path.join(SPARK_HOME, project_relative_path)

     # We should ignore the following jars
     ignored_jar_suffixes = ("javadoc.jar", "sources.jar", "test-sources.jar", "tests.jar")

     # Search jar in the project dir using the jar name_prefix for both sbt build and maven
     # build because the artifact jars are in different directories.
     sbt_build = glob.glob(
         os.path.join(project_full_path, "target/scala-*/%s*.jar" % sbt_jar_name_prefix)
     )
     maven_build = glob.glob(os.path.join(project_full_path, "target/%s*.jar" % mvn_jar_name_prefix))
     jar_paths = sbt_build + maven_build
     jars = [jar for jar in jar_paths if not jar.endswith(ignored_jar_suffixes)]

     if not jars:
         return None
     elif len(jars) > 1 and not return_first:
         raise RuntimeError("Found multiple JARs: %s; please remove all but one" % (", ".join(jars)))
     else:
         return jars[0]


 def get_sbt_runtime_classpath(project_relative_path, project_name_map):
     """
     Get the runtime classpath for a project using SBT.
     This is used as a fallback when classpath.txt doesn't exist (SBT builds).
     Args:
         project_relative_path: Relative path from SPARK_HOME to the project directory
         project_name_map: Dict mapping project paths to SBT project names
                          (e.g., {"connector/kafka-0-10-sql": "sql-kafka-0-10"})
     Returns:
         Comma-separated string of JAR paths, or None if SBT command fails
     """
     import re
     import subprocess

     sbt_project = project_name_map.get(project_relative_path)
     if not sbt_project:
         return None

     try:
         # Run SBT command to get runtime classpath
         sbt_cmd = os.path.join(SPARK_HOME, "build", "sbt")
         result = subprocess.run(
             [sbt_cmd, f"show {sbt_project}/Runtime/dependencyClasspath"],
             cwd=SPARK_HOME,
             capture_output=True,
             text=True,
             encoding="utf-8",
             timeout=180,
         )

         if result.returncode != 0:
             return None

         # Parse the output to extract JAR paths.
         # SBT's `show dependencyClasspath` emits lines like:
         #   [info] * Attributed(/path/to/file.jar)
         # The Attributed(...) format is part of SBT's core attributed path API and has
         # been stable across all SBT versions used by Spark. If SBT changes this format,
         # update the regex below to match the new output.
         jar_paths = []
         for line in result.stdout.splitlines():
             match = re.search(r"Attributed\(([^)]+\.jar)\)", line)
             if match:
                 jar_paths.append(match.group(1))

         if jar_paths:
             return ",".join(jar_paths)

         return None
     except Exception:
         return None


 def read_classpath(project_relative_path, project_name_map=None):
     """
     Read the classpath file for a project and return it as a comma-separated string.

     The classpath file is typically generated by Maven and contains colon-separated paths.
     For SBT builds (when classpath.txt doesn't exist), this function will query SBT
     for the runtime classpath.

     Args:
         project_relative_path: Relative path from SPARK_HOME to the project directory
         project_name_map: Optional dict mapping project paths to SBT project names.
                          Required if classpath.txt doesn't exist and SBT query is needed.

     Returns:
         Comma-separated string of JAR paths

     Raises:
         RuntimeError: If the classpath cannot be determined

     Example:
         >>> classpath = read_classpath("connector/kafka-0-10-sql")
         >>> # Returns: "/path/to/jar1.jar,/path/to/jar2.jar,..."
     """
     project_full_path = os.path.join(SPARK_HOME, project_relative_path)
     classpath_file = os.path.join(project_full_path, "target", "classpath.txt")

     # First try to read classpath.txt (Maven builds)
     if os.path.exists(classpath_file):
         with open(classpath_file, "r", encoding="utf-8") as f:
             classpath = f.read().strip()
         # Replace colon with comma for spark-submit --jars format
         return classpath.replace(":", ",")

     # Fall back to querying SBT for runtime classpath (SBT builds)
     if project_name_map is not None:
         sbt_classpath = get_sbt_runtime_classpath(project_relative_path, project_name_map)
         if sbt_classpath:
             return sbt_classpath

     # If both methods fail, raise an error
     raise RuntimeError(
         f"Classpath file not found at {classpath_file} and could not query SBT. "
         f"Please build the project with Maven: "
         f"'build/mvn -pl {project_relative_path} dependency:build-classpath "
         f"-Dmdep.outputFile=target/classpath.txt' "
         f"or with SBT: 'build/sbt Test/package'"
     )


 test_not_compiled_message = ""
 try:
     from pyspark.sql.utils import require_test_compiled

     require_test_compiled()
 except Exception as e:
     test_not_compiled_message = str(e)

 test_compiled = not test_not_compiled_message


 class SQLTestUtils:
     """
     This util assumes the instance of this to have 'spark' attribute, having a spark session.
     It is usually used with 'ReusedSQLTestCase' class but can be used if you feel sure the
     the implementation of this class has 'spark' attribute.
     """

     @contextmanager
     def sql_conf(self, pairs):
         """
         A convenient context manager to test some configuration specific logic. This sets
         `value` to the configuration `key` and then restores it back when it exits.
         """
         assert isinstance(pairs, dict), "pairs should be a dictionary."
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         keys = pairs.keys()
         new_values = pairs.values()
         old_values = [self.spark.conf.get(key, None) for key in keys]
         for key, new_value in zip(keys, new_values):
             self.spark.conf.set(key, new_value)
         try:
             yield
         finally:
             for key, old_value in zip(keys, old_values):
                 if old_value is None:
                     self.spark.conf.unset(key)
                 else:
                     self.spark.conf.set(key, old_value)

     @contextmanager
     def database(self, *databases):
         """
         A convenient context manager to test with some specific databases. This drops the given
         databases if it exists and sets current database to "default" when it exits.
         """
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         try:
             yield
         finally:
             for db in databases:
                 self.spark.sql("DROP DATABASE IF EXISTS %s CASCADE" % db)
             self.spark.catalog.setCurrentDatabase("default")

     @contextmanager
     def table(self, *tables):
         """
         A convenient context manager to test with some specific tables. This drops the given tables
         if it exists.
         """
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         try:
             yield
         finally:
             for t in tables:
                 self.spark.sql("DROP TABLE IF EXISTS %s" % t)

     @contextmanager
     def view(self, *views):
         """
         A convenient context manager for persistent (catalog) views. On exit, runs
         ``DROP VIEW IF EXISTS`` for each name. For temporary views, use :meth:`temp_view`.
         """
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         try:
             yield
         finally:
             for v in views:
                 self.spark.sql("DROP VIEW IF EXISTS %s" % v)

     @contextmanager
     def temp_view(self, *views):
         """
         A convenient context manager to test with some specific views. This drops the given views
         if it exists.
         """
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         try:
             yield
         finally:
             for v in views:
                 self.spark.catalog.dropTempView(v)

     @contextmanager
     def temp_func(self, *functions):
         """
         A convenient context manager to test with some specific temporary functions.
         This drops the temporary functions if it exists.
         """
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         try:
             yield
         finally:
             for f in functions:
                 self.spark.sql("DROP TEMPORARY FUNCTION IF EXISTS %s" % f)

     @contextmanager
     def function(self, *functions):
         """
         A convenient context manager to test with some specific functions. This drops the given
         functions if it exists.
         """
         assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

         try:
             yield
         finally:
             for f in functions:
                 self.spark.sql("DROP FUNCTION IF EXISTS %s" % f)

     @contextmanager
     def temp_env(self, pairs):
         assert isinstance(pairs, dict), "pairs should be a dictionary."

         keys = pairs.keys()
         new_values = pairs.values()
         old_values = [os.environ.get(key, None) for key in keys]
         for key, new_value in zip(keys, new_values):
             if new_value is None:
                 if key in os.environ:
                     del os.environ[key]
             else:
                 os.environ[key] = new_value
         try:
             yield
         finally:
             for key, old_value in zip(keys, old_values):
                 if old_value is None:
                     if key in os.environ:
                         del os.environ[key]
                 else:
                     os.environ[key] = old_value

     @staticmethod
     def assert_close(a, b):
         c = [j[0] for j in b]
         diff = [abs(v - c[k]) < 1e-6 if math.isfinite(v) else v == c[k] for k, v in enumerate(a)]
         assert sum(diff) == len(a), f"sum: {sum(diff)}, len: {len(a)}"


 class ReusedSQLTestCase(ReusedPySparkTestCase, SQLTestUtils, PySparkErrorTestUtils):
     @classmethod
     def setUpClass(cls):
         super().setUpClass()

         cls._legacy_sc = cls.sc
         cls.spark = SparkSession(cls.sc)
         cls.tempdir = tempfile.NamedTemporaryFile(delete=False)
         os.unlink(cls.tempdir.name)
         cls.testData = [Row(key=i, value=str(i)) for i in range(100)]
         cls.df = cls.spark.createDataFrame(cls.testData)

     @classmethod
     def tearDownClass(cls):
         try:
             cls.spark.stop()
             shutil.rmtree(cls.tempdir.name, ignore_errors=True)
         finally:
             super().tearDownClass()

     def tearDown(self):
         try:
             self.spark._jsparkSession.cleanupPythonWorkerLogs()
         finally:
             super().tearDown()
	#
	# 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 glob
	import math
	import os
	import shutil
	import tempfile
	from contextlib import contextmanager

	from pyspark.find_spark_home import _find_spark_home
	from pyspark.sql import SparkSession
	from pyspark.sql.types import Row
	from pyspark.testing.utils import (
	PySparkErrorTestUtils,
	ReusedPySparkTestCase,
	)

	SPARK_HOME = _find_spark_home()


	def search_jar(project_relative_path, sbt_jar_name_prefix, mvn_jar_name_prefix, return_first=False):
	# Note that 'sbt_jar_name_prefix' and 'mvn_jar_name_prefix' are used since the prefix can
	# vary for SBT or Maven specifically. See also SPARK-26856
	project_full_path = os.path.join(SPARK_HOME, project_relative_path)

	# We should ignore the following jars
	ignored_jar_suffixes = ("javadoc.jar", "sources.jar", "test-sources.jar", "tests.jar")

	# Search jar in the project dir using the jar name_prefix for both sbt build and maven
	# build because the artifact jars are in different directories.
	sbt_build = glob.glob(
	os.path.join(project_full_path, "target/scala-/%s.jar" % sbt_jar_name_prefix)
	)
	maven_build = glob.glob(os.path.join(project_full_path, "target/%s*.jar" % mvn_jar_name_prefix))
	jar_paths = sbt_build + maven_build
	jars = [jar for jar in jar_paths if not jar.endswith(ignored_jar_suffixes)]

	if not jars:
	return None
	elif len(jars) > 1 and not return_first:
	raise RuntimeError("Found multiple JARs: %s; please remove all but one" % (", ".join(jars)))
	else:
	return jars[0]


	def get_sbt_runtime_classpath(project_relative_path, project_name_map):
	"""
	Get the runtime classpath for a project using SBT.
	This is used as a fallback when classpath.txt doesn't exist (SBT builds).
	Args:
	project_relative_path: Relative path from SPARK_HOME to the project directory
	project_name_map: Dict mapping project paths to SBT project names
	(e.g., {"connector/kafka-0-10-sql": "sql-kafka-0-10"})
	Returns:
	Comma-separated string of JAR paths, or None if SBT command fails
	"""
	import re
	import subprocess

	sbt_project = project_name_map.get(project_relative_path)
	if not sbt_project:
	return None

	try:
	# Run SBT command to get runtime classpath
	sbt_cmd = os.path.join(SPARK_HOME, "build", "sbt")
	result = subprocess.run(
	[sbt_cmd, f"show {sbt_project}/Runtime/dependencyClasspath"],
	cwd=SPARK_HOME,
	capture_output=True,
	text=True,
	encoding="utf-8",
	timeout=180,
	)

	if result.returncode != 0:
	return None

	# Parse the output to extract JAR paths.
	# SBT's `show dependencyClasspath` emits lines like:
	# [info] * Attributed(/path/to/file.jar)
	# The Attributed(...) format is part of SBT's core attributed path API and has
	# been stable across all SBT versions used by Spark. If SBT changes this format,
	# update the regex below to match the new output.
	jar_paths = []
	for line in result.stdout.splitlines():
	match = re.search(r"Attributed\(([^)]+\.jar)\)", line)
	if match:
	jar_paths.append(match.group(1))

	if jar_paths:
	return ",".join(jar_paths)

	return None
	except Exception:
	return None


	def read_classpath(project_relative_path, project_name_map=None):
	"""
	Read the classpath file for a project and return it as a comma-separated string.

	The classpath file is typically generated by Maven and contains colon-separated paths.
	For SBT builds (when classpath.txt doesn't exist), this function will query SBT
	for the runtime classpath.

	Args:
	project_relative_path: Relative path from SPARK_HOME to the project directory
	project_name_map: Optional dict mapping project paths to SBT project names.
	Required if classpath.txt doesn't exist and SBT query is needed.

	Returns:
	Comma-separated string of JAR paths

	Raises:
	RuntimeError: If the classpath cannot be determined

	Example:
	>>> classpath = read_classpath("connector/kafka-0-10-sql")
	>>> # Returns: "/path/to/jar1.jar,/path/to/jar2.jar,..."
	"""
	project_full_path = os.path.join(SPARK_HOME, project_relative_path)
	classpath_file = os.path.join(project_full_path, "target", "classpath.txt")

	# First try to read classpath.txt (Maven builds)
	if os.path.exists(classpath_file):
	with open(classpath_file, "r", encoding="utf-8") as f:
	classpath = f.read().strip()
	# Replace colon with comma for spark-submit --jars format
	return classpath.replace(":", ",")

	# Fall back to querying SBT for runtime classpath (SBT builds)
	if project_name_map is not None:
	sbt_classpath = get_sbt_runtime_classpath(project_relative_path, project_name_map)
	if sbt_classpath:
	return sbt_classpath

	# If both methods fail, raise an error
	raise RuntimeError(
	f"Classpath file not found at {classpath_file} and could not query SBT. "
	f"Please build the project with Maven: "
	f"'build/mvn -pl {project_relative_path} dependency:build-classpath "
	f"-Dmdep.outputFile=target/classpath.txt' "
	f"or with SBT: 'build/sbt Test/package'"
	)


	test_not_compiled_message = ""
	try:
	from pyspark.sql.utils import require_test_compiled

	require_test_compiled()
	except Exception as e:
	test_not_compiled_message = str(e)

	test_compiled = not test_not_compiled_message


	class SQLTestUtils:
	"""
	This util assumes the instance of this to have 'spark' attribute, having a spark session.
	It is usually used with 'ReusedSQLTestCase' class but can be used if you feel sure the
	the implementation of this class has 'spark' attribute.
	"""

	@contextmanager
	def sql_conf(self, pairs):
	"""
	A convenient context manager to test some configuration specific logic. This sets
	`value` to the configuration `key` and then restores it back when it exits.
	"""
	assert isinstance(pairs, dict), "pairs should be a dictionary."
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	keys = pairs.keys()
	new_values = pairs.values()
	old_values = [self.spark.conf.get(key, None) for key in keys]
	for key, new_value in zip(keys, new_values):
	self.spark.conf.set(key, new_value)
	try:
	yield
	finally:
	for key, old_value in zip(keys, old_values):
	if old_value is None:
	self.spark.conf.unset(key)
	else:
	self.spark.conf.set(key, old_value)

	@contextmanager
	def database(self, *databases):
	"""
	A convenient context manager to test with some specific databases. This drops the given
	databases if it exists and sets current database to "default" when it exits.
	"""
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	try:
	yield
	finally:
	for db in databases:
	self.spark.sql("DROP DATABASE IF EXISTS %s CASCADE" % db)
	self.spark.catalog.setCurrentDatabase("default")

	@contextmanager
	def table(self, *tables):
	"""
	A convenient context manager to test with some specific tables. This drops the given tables
	if it exists.
	"""
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	try:
	yield
	finally:
	for t in tables:
	self.spark.sql("DROP TABLE IF EXISTS %s" % t)

	@contextmanager
	def view(self, *views):
	"""
	A convenient context manager for persistent (catalog) views. On exit, runs
	``DROP VIEW IF EXISTS`` for each name. For temporary views, use :meth:`temp_view`.
	"""
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	try:
	yield
	finally:
	for v in views:
	self.spark.sql("DROP VIEW IF EXISTS %s" % v)

	@contextmanager
	def temp_view(self, *views):
	"""
	A convenient context manager to test with some specific views. This drops the given views
	if it exists.
	"""
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	try:
	yield
	finally:
	for v in views:
	self.spark.catalog.dropTempView(v)

	@contextmanager
	def temp_func(self, *functions):
	"""
	A convenient context manager to test with some specific temporary functions.
	This drops the temporary functions if it exists.
	"""
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	try:
	yield
	finally:
	for f in functions:
	self.spark.sql("DROP TEMPORARY FUNCTION IF EXISTS %s" % f)

	@contextmanager
	def function(self, *functions):
	"""
	A convenient context manager to test with some specific functions. This drops the given
	functions if it exists.
	"""
	assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."

	try:
	yield
	finally:
	for f in functions:
	self.spark.sql("DROP FUNCTION IF EXISTS %s" % f)

	@contextmanager
	def temp_env(self, pairs):
	assert isinstance(pairs, dict), "pairs should be a dictionary."

	keys = pairs.keys()
	new_values = pairs.values()
	old_values = [os.environ.get(key, None) for key in keys]
	for key, new_value in zip(keys, new_values):
	if new_value is None:
	if key in os.environ:
	del os.environ[key]
	else:
	os.environ[key] = new_value
	try:
	yield
	finally:
	for key, old_value in zip(keys, old_values):
	if old_value is None:
	if key in os.environ:
	del os.environ[key]
	else:
	os.environ[key] = old_value

	@staticmethod
	def assert_close(a, b):
	c = [j[0] for j in b]
	diff = [abs(v - c[k]) < 1e-6 if math.isfinite(v) else v == c[k] for k, v in enumerate(a)]
	assert sum(diff) == len(a), f"sum: {sum(diff)}, len: {len(a)}"


	class ReusedSQLTestCase(ReusedPySparkTestCase, SQLTestUtils, PySparkErrorTestUtils):
	@classmethod
	def setUpClass(cls):
	super().setUpClass()

	cls._legacy_sc = cls.sc
	cls.spark = SparkSession(cls.sc)
	cls.tempdir = tempfile.NamedTemporaryFile(delete=False)
	os.unlink(cls.tempdir.name)
	cls.testData = [Row(key=i, value=str(i)) for i in range(100)]
	cls.df = cls.spark.createDataFrame(cls.testData)

	@classmethod
	def tearDownClass(cls):
	try:
	cls.spark.stop()
	shutil.rmtree(cls.tempdir.name, ignore_errors=True)
	finally:
	super().tearDownClass()

	def tearDown(self):
	try:
	self.spark._jsparkSession.cleanupPythonWorkerLogs()
	finally:
	super().tearDown()