spark-instrumented-optimizer/python/pyspark/testing/utils.py

#
# 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 os
import struct
import sys
import unittest
from time import time, sleep

from pyspark import SparkContext, SparkConf


have_scipy = False
have_numpy = False
try:
    import scipy.sparse  # noqa: F401
    have_scipy = True
except:
    # No SciPy, but that's okay, we'll skip those tests
    pass
try:
    import numpy as np  # noqa: F401
    have_numpy = True
except:
    # No NumPy, but that's okay, we'll skip those tests
    pass


SPARK_HOME = os.environ["SPARK_HOME"]


def read_int(b):
    return struct.unpack("!i", b)[0]


def write_int(i):
    return struct.pack("!i", i)


def eventually(condition, timeout=30.0, catch_assertions=False):
    """
    Wait a given amount of time for a condition to pass, else fail with an error.
    This is a helper utility for PySpark tests.

    :param condition: Function that checks for termination conditions.
                      condition() can return:
                       - True: Conditions met. Return without error.
                       - other value: Conditions not met yet. Continue. Upon timeout,
                                      include last such value in error message.
                      Note that this method may be called at any time during
                      streaming execution (e.g., even before any results
                      have been created).
    :param timeout: Number of seconds to wait.  Default 30 seconds.
    :param catch_assertions: If False (default), do not catch AssertionErrors.
                             If True, catch AssertionErrors; continue, but save
                             error to throw upon timeout.
    """
    start_time = time()
    lastValue = None
    while time() - start_time < timeout:
        if catch_assertions:
            try:
                lastValue = condition()
            except AssertionError as e:
                lastValue = e
        else:
            lastValue = condition()
        if lastValue is True:
            return
        sleep(0.01)
    if isinstance(lastValue, AssertionError):
        raise lastValue
    else:
        raise AssertionError(
            "Test failed due to timeout after %g sec, with last condition returning: %s"
            % (timeout, lastValue))


class QuietTest(object):
    def __init__(self, sc):
        self.log4j = sc._jvm.org.apache.log4j

    def __enter__(self):
        self.old_level = self.log4j.LogManager.getRootLogger().getLevel()
        self.log4j.LogManager.getRootLogger().setLevel(self.log4j.Level.FATAL)

    def __exit__(self, exc_type, exc_val, exc_tb):
        self.log4j.LogManager.getRootLogger().setLevel(self.old_level)


class PySparkTestCase(unittest.TestCase):

    def setUp(self):
        self._old_sys_path = list(sys.path)
        class_name = self.__class__.__name__
        self.sc = SparkContext('local[4]', class_name)

    def tearDown(self):
        self.sc.stop()
        sys.path = self._old_sys_path


class ReusedPySparkTestCase(unittest.TestCase):

    @classmethod
    def conf(cls):
        """
        Override this in subclasses to supply a more specific conf
        """
        return SparkConf()

    @classmethod
    def setUpClass(cls):
        cls.sc = SparkContext('local[4]', cls.__name__, conf=cls.conf())

    @classmethod
    def tearDownClass(cls):
        cls.sc.stop()


class ByteArrayOutput(object):
    def __init__(self):
        self.buffer = bytearray()

    def write(self, b):
        self.buffer += b

    def close(self):
        pass


def search_jar(project_relative_path, sbt_jar_name_prefix, mvn_jar_name_prefix):
    # 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(
        os.environ["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:
        raise Exception("Found multiple JARs: %s; please remove all but one" % (", ".join(jars)))
    else:
        return jars[0]