spark-instrumented-optimizer/python/pyspark/sql/tests/test_appsubmit.py

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[SPARK-26032][PYTHON] Break large sql/tests.py files into smaller files ## What changes were proposed in this pull request? This is the official first attempt to break huge single `tests.py` file - I did it locally before few times and gave up for some reasons. Now, currently it really makes the unittests super hard to read and difficult to check. To me, it even bothers me to to scroll down the big file. It's one single 7000 lines file! This is not only readability issue. Since one big test takes most of tests time, the tests don't run in parallel fully - although it will costs to start and stop the context. We could pick up one example and follow. Given my investigation, the current style looks closer to NumPy structure and looks easier to follow. Please see https://github.com/numpy/numpy/tree/master/numpy. Basically this PR proposes to break down `pyspark/sql/tests.py` into ...: ```bash pyspark ... ├── sql ... │   ├── tests # Includes all tests broken down from 'pyspark/sql/tests.py' │ │  │ # Each matchs to module in 'pyspark/sql'. Additionally, some logical group can │ │  │ # be added. For instance, 'test_arrow.py', 'test_datasources.py' ... │   │   ├── __init__.py │   │   ├── test_appsubmit.py │   │   ├── test_arrow.py │   │   ├── test_catalog.py │   │   ├── test_column.py │   │   ├── test_conf.py │   │   ├── test_context.py │   │   ├── test_dataframe.py │   │   ├── test_datasources.py │   │   ├── test_functions.py │   │   ├── test_group.py │   │   ├── test_pandas_udf.py │   │   ├── test_pandas_udf_grouped_agg.py │   │   ├── test_pandas_udf_grouped_map.py │   │   ├── test_pandas_udf_scalar.py │   │   ├── test_pandas_udf_window.py │   │   ├── test_readwriter.py │   │   ├── test_serde.py │   │   ├── test_session.py │   │   ├── test_streaming.py │   │   ├── test_types.py │   │   ├── test_udf.py │   │   └── test_utils.py ... ├── testing # Includes testing utils that can be used in unittests. │   ├── __init__.py │   └── sqlutils.py ... ``` ## How was this patch tested? Existing tests should cover. `cd python` and `./run-tests-with-coverage`. Manually checked they are actually being ran. Each test (not officially) can be ran via: ``` SPARK_TESTING=1 ./bin/pyspark pyspark.sql.tests.test_pandas_udf_scalar ``` Note that if you're using Mac and Python 3, you might have to `OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES`. Closes #23021 from HyukjinKwon/SPARK-25344. Authored-by: hyukjinkwon <gurwls223@apache.org> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-11-14 01:51:11 -05:00
#
# 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 os
import subprocess
import tempfile
import py4j
from pyspark import SparkContext
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from pyspark.tests.test_appsubmit import SparkSubmitTests
[SPARK-26032][PYTHON] Break large sql/tests.py files into smaller files ## What changes were proposed in this pull request? This is the official first attempt to break huge single `tests.py` file - I did it locally before few times and gave up for some reasons. Now, currently it really makes the unittests super hard to read and difficult to check. To me, it even bothers me to to scroll down the big file. It's one single 7000 lines file! This is not only readability issue. Since one big test takes most of tests time, the tests don't run in parallel fully - although it will costs to start and stop the context. We could pick up one example and follow. Given my investigation, the current style looks closer to NumPy structure and looks easier to follow. Please see https://github.com/numpy/numpy/tree/master/numpy. Basically this PR proposes to break down `pyspark/sql/tests.py` into ...: ```bash pyspark ... ├── sql ... │   ├── tests # Includes all tests broken down from 'pyspark/sql/tests.py' │ │  │ # Each matchs to module in 'pyspark/sql'. Additionally, some logical group can │ │  │ # be added. For instance, 'test_arrow.py', 'test_datasources.py' ... │   │   ├── __init__.py │   │   ├── test_appsubmit.py │   │   ├── test_arrow.py │   │   ├── test_catalog.py │   │   ├── test_column.py │   │   ├── test_conf.py │   │   ├── test_context.py │   │   ├── test_dataframe.py │   │   ├── test_datasources.py │   │   ├── test_functions.py │   │   ├── test_group.py │   │   ├── test_pandas_udf.py │   │   ├── test_pandas_udf_grouped_agg.py │   │   ├── test_pandas_udf_grouped_map.py │   │   ├── test_pandas_udf_scalar.py │   │   ├── test_pandas_udf_window.py │   │   ├── test_readwriter.py │   │   ├── test_serde.py │   │   ├── test_session.py │   │   ├── test_streaming.py │   │   ├── test_types.py │   │   ├── test_udf.py │   │   └── test_utils.py ... ├── testing # Includes testing utils that can be used in unittests. │   ├── __init__.py │   └── sqlutils.py ... ``` ## How was this patch tested? Existing tests should cover. `cd python` and `./run-tests-with-coverage`. Manually checked they are actually being ran. Each test (not officially) can be ran via: ``` SPARK_TESTING=1 ./bin/pyspark pyspark.sql.tests.test_pandas_udf_scalar ``` Note that if you're using Mac and Python 3, you might have to `OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES`. Closes #23021 from HyukjinKwon/SPARK-25344. Authored-by: hyukjinkwon <gurwls223@apache.org> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
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class HiveSparkSubmitTests(SparkSubmitTests):
@classmethod
def setUpClass(cls):
# get a SparkContext to check for availability of Hive
sc = SparkContext('local[4]', cls.__name__)
cls.hive_available = True
try:
sc._jvm.org.apache.hadoop.hive.conf.HiveConf()
except py4j.protocol.Py4JError:
cls.hive_available = False
except TypeError:
cls.hive_available = False
finally:
# we don't need this SparkContext for the test
sc.stop()
def setUp(self):
super(HiveSparkSubmitTests, self).setUp()
if not self.hive_available:
self.skipTest("Hive is not available.")
def test_hivecontext(self):
# This test checks that HiveContext is using Hive metastore (SPARK-16224).
# It sets a metastore url and checks if there is a derby dir created by
# Hive metastore. If this derby dir exists, HiveContext is using
# Hive metastore.
metastore_path = os.path.join(tempfile.mkdtemp(), "spark16224_metastore_db")
metastore_URL = "jdbc:derby:;databaseName=" + metastore_path + ";create=true"
hive_site_dir = os.path.join(self.programDir, "conf")
hive_site_file = self.createTempFile("hive-site.xml", ("""
|<configuration>
| <property>
| <name>javax.jdo.option.ConnectionURL</name>
| <value>%s</value>
| </property>
|</configuration>
""" % metastore_URL).lstrip(), "conf")
script = self.createTempFile("test.py", """
|import os
|
|from pyspark.conf import SparkConf
|from pyspark.context import SparkContext
|from pyspark.sql import HiveContext
|
|conf = SparkConf()
|sc = SparkContext(conf=conf)
|hive_context = HiveContext(sc)
|print(hive_context.sql("show databases").collect())
""")
proc = subprocess.Popen(
self.sparkSubmit + ["--master", "local-cluster[1,1,1024]",
"--driver-class-path", hive_site_dir, script],
stdout=subprocess.PIPE)
out, err = proc.communicate()
self.assertEqual(0, proc.returncode)
self.assertIn("default", out.decode('utf-8'))
self.assertTrue(os.path.exists(metastore_path))
if __name__ == "__main__":
import unittest
from pyspark.sql.tests.test_appsubmit import *
try:
import xmlrunner
[SPARK-28130][PYTHON] Print pretty messages for skipped tests when xmlrunner is available in PySpark ## What changes were proposed in this pull request? Currently, pretty skipped message added by https://github.com/apache/spark/commit/f7435bec6a9348cfbbe26b13c230c08545d16067 mechanism seems not working when xmlrunner is installed apparently. This PR fixes two things: 1. When `xmlrunner` is installed, seems `xmlrunner` does not respect `vervosity` level in unittests (default is level 1). So the output looks as below ``` Running tests... ---------------------------------------------------------------------- SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS ---------------------------------------------------------------------- ``` So it is not caught by our message detection mechanism. 2. If we manually set the `vervocity` level to `xmlrunner`, it prints messages as below: ``` test_mixed_udf (pyspark.sql.tests.test_pandas_udf_scalar.ScalarPandasUDFTests) ... SKIP (0.000s) test_mixed_udf_and_sql (pyspark.sql.tests.test_pandas_udf_scalar.ScalarPandasUDFTests) ... SKIP (0.000s) ... ``` This is different in our Jenkins machine: ``` test_createDataFrame_column_name_encoding (pyspark.sql.tests.test_arrow.ArrowTests) ... skipped 'Pandas >= 0.23.2 must be installed; however, it was not found.' test_createDataFrame_does_not_modify_input (pyspark.sql.tests.test_arrow.ArrowTests) ... skipped 'Pandas >= 0.23.2 must be installed; however, it was not found.' ... ``` Note that last `SKIP` is different. This PR fixes the regular expression to catch `SKIP` case as well. ## How was this patch tested? Manually tested. **Before:** ``` Starting test(python2.7): pyspark.... Finished test(python2.7): pyspark.... (0s) ... Tests passed in 562 seconds ======================================================================== ... ``` **After:** ``` Starting test(python2.7): pyspark.... Finished test(python2.7): pyspark.... (48s) ... 93 tests were skipped ... Tests passed in 560 seconds Skipped tests pyspark.... with python2.7: pyspark...(...) ... SKIP (0.000s) ... ======================================================================== ... ``` Closes #24927 from HyukjinKwon/SPARK-28130. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
[SPARK-26032][PYTHON] Break large sql/tests.py files into smaller files ## What changes were proposed in this pull request? This is the official first attempt to break huge single `tests.py` file - I did it locally before few times and gave up for some reasons. Now, currently it really makes the unittests super hard to read and difficult to check. To me, it even bothers me to to scroll down the big file. It's one single 7000 lines file! This is not only readability issue. Since one big test takes most of tests time, the tests don't run in parallel fully - although it will costs to start and stop the context. We could pick up one example and follow. Given my investigation, the current style looks closer to NumPy structure and looks easier to follow. Please see https://github.com/numpy/numpy/tree/master/numpy. Basically this PR proposes to break down `pyspark/sql/tests.py` into ...: ```bash pyspark ... ├── sql ... │   ├── tests # Includes all tests broken down from 'pyspark/sql/tests.py' │ │  │ # Each matchs to module in 'pyspark/sql'. Additionally, some logical group can │ │  │ # be added. For instance, 'test_arrow.py', 'test_datasources.py' ... │   │   ├── __init__.py │   │   ├── test_appsubmit.py │   │   ├── test_arrow.py │   │   ├── test_catalog.py │   │   ├── test_column.py │   │   ├── test_conf.py │   │   ├── test_context.py │   │   ├── test_dataframe.py │   │   ├── test_datasources.py │   │   ├── test_functions.py │   │   ├── test_group.py │   │   ├── test_pandas_udf.py │   │   ├── test_pandas_udf_grouped_agg.py │   │   ├── test_pandas_udf_grouped_map.py │   │   ├── test_pandas_udf_scalar.py │   │   ├── test_pandas_udf_window.py │   │   ├── test_readwriter.py │   │   ├── test_serde.py │   │   ├── test_session.py │   │   ├── test_streaming.py │   │   ├── test_types.py │   │   ├── test_udf.py │   │   └── test_utils.py ... ├── testing # Includes testing utils that can be used in unittests. │   ├── __init__.py │   └── sqlutils.py ... ``` ## How was this patch tested? Existing tests should cover. `cd python` and `./run-tests-with-coverage`. Manually checked they are actually being ran. Each test (not officially) can be ran via: ``` SPARK_TESTING=1 ./bin/pyspark pyspark.sql.tests.test_pandas_udf_scalar ``` Note that if you're using Mac and Python 3, you might have to `OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES`. Closes #23021 from HyukjinKwon/SPARK-25344. Authored-by: hyukjinkwon <gurwls223@apache.org> Signed-off-by: hyukjinkwon <gurwls223@apache.org>
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except ImportError:
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testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)