4ad9bfd53b
### What changes were proposed in this pull request? This PR aims to drop Python 2.7, 3.4 and 3.5. Roughly speaking, it removes all the widely known Python 2 compatibility workarounds such as `sys.version` comparison, `__future__`. Also, it removes the Python 2 dedicated codes such as `ArrayConstructor` in Spark. ### Why are the changes needed? 1. Unsupport EOL Python versions 2. Reduce maintenance overhead and remove a bit of legacy codes and hacks for Python 2. 3. PyPy2 has a critical bug that causes a flaky test, SPARK-28358 given my testing and investigation. 4. Users can use Python type hints with Pandas UDFs without thinking about Python version 5. Users can leverage one latest cloudpickle, https://github.com/apache/spark/pull/28950. With Python 3.8+ it can also leverage C pickle. ### Does this PR introduce _any_ user-facing change? Yes, users cannot use Python 2.7, 3.4 and 3.5 in the upcoming Spark version. ### How was this patch tested? Manually tested and also tested in Jenkins. Closes #28957 from HyukjinKwon/SPARK-32138. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
122 lines
3.9 KiB
Python
122 lines
3.9 KiB
Python
# -*- coding: utf-8 -*-
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import re
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import sys
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import traceback
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__all__ = []
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def print_exec(stream):
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ei = sys.exc_info()
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traceback.print_exception(ei[0], ei[1], ei[2], None, stream)
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class VersionUtils(object):
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"""
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Provides utility method to determine Spark versions with given input string.
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"""
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@staticmethod
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def majorMinorVersion(sparkVersion):
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"""
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Given a Spark version string, return the (major version number, minor version number).
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E.g., for 2.0.1-SNAPSHOT, return (2, 0).
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>>> sparkVersion = "2.4.0"
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>>> VersionUtils.majorMinorVersion(sparkVersion)
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(2, 4)
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>>> sparkVersion = "2.3.0-SNAPSHOT"
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>>> VersionUtils.majorMinorVersion(sparkVersion)
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(2, 3)
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"""
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m = re.search(r'^(\d+)\.(\d+)(\..*)?$', sparkVersion)
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if m is not None:
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return (int(m.group(1)), int(m.group(2)))
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else:
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raise ValueError("Spark tried to parse '%s' as a Spark" % sparkVersion +
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" version string, but it could not find the major and minor" +
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" version numbers.")
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def fail_on_stopiteration(f):
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"""
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Wraps the input function to fail on 'StopIteration' by raising a 'RuntimeError'
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prevents silent loss of data when 'f' is used in a for loop in Spark code
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"""
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def wrapper(*args, **kwargs):
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try:
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return f(*args, **kwargs)
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except StopIteration as exc:
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raise RuntimeError(
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"Caught StopIteration thrown from user's code; failing the task",
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exc
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)
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return wrapper
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def _print_missing_jar(lib_name, pkg_name, jar_name, spark_version):
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print("""
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________________________________________________________________________________________________
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Spark %(lib_name)s libraries not found in class path. Try one of the following.
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1. Include the %(lib_name)s library and its dependencies with in the
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spark-submit command as
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$ bin/spark-submit --packages org.apache.spark:spark-%(pkg_name)s:%(spark_version)s ...
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2. Download the JAR of the artifact from Maven Central http://search.maven.org/,
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Group Id = org.apache.spark, Artifact Id = spark-%(jar_name)s, Version = %(spark_version)s.
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Then, include the jar in the spark-submit command as
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$ bin/spark-submit --jars <spark-%(jar_name)s.jar> ...
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________________________________________________________________________________________________
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""" % {
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"lib_name": lib_name,
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"pkg_name": pkg_name,
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"jar_name": jar_name,
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"spark_version": spark_version
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})
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def _parse_memory(s):
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"""
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Parse a memory string in the format supported by Java (e.g. 1g, 200m) and
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return the value in MiB
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>>> _parse_memory("256m")
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256
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>>> _parse_memory("2g")
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2048
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"""
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units = {'g': 1024, 'm': 1, 't': 1 << 20, 'k': 1.0 / 1024}
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if s[-1].lower() not in units:
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raise ValueError("invalid format: " + s)
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return int(float(s[:-1]) * units[s[-1].lower()])
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if __name__ == "__main__":
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import doctest
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(failure_count, test_count) = doctest.testmod()
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if failure_count:
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sys.exit(-1)
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