spark-instrumented-optimizer/python/pyspark/resultiterable.py
HyukjinKwon 4ad9bfd53b [SPARK-32138] Drop Python 2.7, 3.4 and 3.5
### 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>
2020-07-14 11:22:44 +09:00

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1.2 KiB
Python

#
# 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.
#
from collections.abc import Iterable
__all__ = ["ResultIterable"]
class ResultIterable(Iterable):
"""
A special result iterable. This is used because the standard
iterator can not be pickled
"""
def __init__(self, data):
self.data = data
self.index = 0
self.maxindex = len(data)
def __iter__(self):
return iter(self.data)
def __len__(self):
return len(self.data)