spark-instrumented-optimizer/python/pyspark/conf.py
Davies Liu 04e44b37cc [SPARK-4897] [PySpark] Python 3 support
This PR update PySpark to support Python 3 (tested with 3.4).

Known issue: unpickle array from Pyrolite is broken in Python 3, those tests are skipped.

TODO: ec2/spark-ec2.py is not fully tested with python3.

Author: Davies Liu <davies@databricks.com>
Author: twneale <twneale@gmail.com>
Author: Josh Rosen <joshrosen@databricks.com>

Closes #5173 from davies/python3 and squashes the following commits:

d7d6323 [Davies Liu] fix tests
6c52a98 [Davies Liu] fix mllib test
99e334f [Davies Liu] update timeout
b716610 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
cafd5ec [Davies Liu] adddress comments from @mengxr
bf225d7 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
179fc8d [Davies Liu] tuning flaky tests
8c8b957 [Davies Liu] fix ResourceWarning in Python 3
5c57c95 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
4006829 [Davies Liu] fix test
2fc0066 [Davies Liu] add python3 path
71535e9 [Davies Liu] fix xrange and divide
5a55ab4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
125f12c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ed498c8 [Davies Liu] fix compatibility with python 3
820e649 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
e8ce8c9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ad7c374 [Davies Liu] fix mllib test and warning
ef1fc2f [Davies Liu] fix tests
4eee14a [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
20112ff [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
59bb492 [Davies Liu] fix tests
1da268c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ca0fdd3 [Davies Liu] fix code style
9563a15 [Davies Liu] add imap back for python 2
0b1ec04 [Davies Liu] make python examples work with Python 3
d2fd566 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
a716d34 [Davies Liu] test with python 3.4
f1700e8 [Davies Liu] fix test in python3
671b1db [Davies Liu] fix test in python3
692ff47 [Davies Liu] fix flaky test
7b9699f [Davies Liu] invalidate import cache for Python 3.3+
9c58497 [Davies Liu] fix kill worker
309bfbf [Davies Liu] keep compatibility
5707476 [Davies Liu] cleanup, fix hash of string in 3.3+
8662d5b [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
f53e1f0 [Davies Liu] fix tests
70b6b73 [Davies Liu] compile ec2/spark_ec2.py in python 3
a39167e [Davies Liu] support customize class in __main__
814c77b [Davies Liu] run unittests with python 3
7f4476e [Davies Liu] mllib tests passed
d737924 [Davies Liu] pass ml tests
375ea17 [Davies Liu] SQL tests pass
6cc42a9 [Davies Liu] rename
431a8de [Davies Liu] streaming tests pass
78901a7 [Davies Liu] fix hash of serializer in Python 3
24b2f2e [Davies Liu] pass all RDD tests
35f48fe [Davies Liu] run future again
1eebac2 [Davies Liu] fix conflict in ec2/spark_ec2.py
6e3c21d [Davies Liu] make cloudpickle work with Python3
2fb2db3 [Josh Rosen] Guard more changes behind sys.version; still doesn't run
1aa5e8f [twneale] Turned out `pickle.DictionaryType is dict` == True, so swapped it out
7354371 [twneale] buffer --> memoryview  I'm not super sure if this a valid change, but the 2.7 docs recommend using memoryview over buffer where possible, so hoping it'll work.
b69ccdf [twneale] Uses the pure python pickle._Pickler instead of c-extension _pickle.Pickler. It appears pyspark 2.7 uses the pure python pickler as well, so this shouldn't degrade pickling performance (?).
f40d925 [twneale] xrange --> range
e104215 [twneale] Replaces 2.7 types.InstsanceType with 3.4 `object`....could be horribly wrong depending on how types.InstanceType is used elsewhere in the package--see http://bugs.python.org/issue8206
79de9d0 [twneale] Replaces python2.7 `file` with 3.4 _io.TextIOWrapper
2adb42d [Josh Rosen] Fix up some import differences between Python 2 and 3
854be27 [Josh Rosen] Run `futurize` on Python code:
7c5b4ce [Josh Rosen] Remove Python 3 check in shell.py.
2015-04-16 16:20:57 -07:00

192 lines
6.2 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 pyspark.conf import SparkConf
>>> from pyspark.context import SparkContext
>>> conf = SparkConf()
>>> conf.setMaster("local").setAppName("My app")
<pyspark.conf.SparkConf object at ...>
>>> conf.get("spark.master")
u'local'
>>> conf.get("spark.app.name")
u'My app'
>>> sc = SparkContext(conf=conf)
>>> sc.master
u'local'
>>> sc.appName
u'My app'
>>> sc.sparkHome is None
True
>>> conf = SparkConf(loadDefaults=False)
>>> conf.setSparkHome("/path")
<pyspark.conf.SparkConf object at ...>
>>> conf.get("spark.home")
u'/path'
>>> conf.setExecutorEnv("VAR1", "value1")
<pyspark.conf.SparkConf object at ...>
>>> conf.setExecutorEnv(pairs = [("VAR3", "value3"), ("VAR4", "value4")])
<pyspark.conf.SparkConf object at ...>
>>> conf.get("spark.executorEnv.VAR1")
u'value1'
>>> print(conf.toDebugString())
spark.executorEnv.VAR1=value1
spark.executorEnv.VAR3=value3
spark.executorEnv.VAR4=value4
spark.home=/path
>>> sorted(conf.getAll(), key=lambda p: p[0])
[(u'spark.executorEnv.VAR1', u'value1'), (u'spark.executorEnv.VAR3', u'value3'), \
(u'spark.executorEnv.VAR4', u'value4'), (u'spark.home', u'/path')]
"""
__all__ = ['SparkConf']
import sys
import re
if sys.version > '3':
unicode = str
__doc__ = re.sub(r"(\W|^)[uU](['])", r'\1\2', __doc__)
class SparkConf(object):
"""
Configuration for a Spark application. Used to set various Spark
parameters as key-value pairs.
Most of the time, you would create a SparkConf object with
C{SparkConf()}, which will load values from C{spark.*} Java system
properties as well. In this case, any parameters you set directly on
the C{SparkConf} object take priority over system properties.
For unit tests, you can also call C{SparkConf(false)} to skip
loading external settings and get the same configuration no matter
what the system properties are.
All setter methods in this class support chaining. For example,
you can write C{conf.setMaster("local").setAppName("My app")}.
Note that once a SparkConf object is passed to Spark, it is cloned
and can no longer be modified by the user.
"""
def __init__(self, loadDefaults=True, _jvm=None, _jconf=None):
"""
Create a new Spark configuration.
:param loadDefaults: whether to load values from Java system
properties (True by default)
:param _jvm: internal parameter used to pass a handle to the
Java VM; does not need to be set by users
:param _jconf: Optionally pass in an existing SparkConf handle
to use its parameters
"""
if _jconf:
self._jconf = _jconf
else:
from pyspark.context import SparkContext
SparkContext._ensure_initialized()
_jvm = _jvm or SparkContext._jvm
self._jconf = _jvm.SparkConf(loadDefaults)
def set(self, key, value):
"""Set a configuration property."""
self._jconf.set(key, unicode(value))
return self
def setIfMissing(self, key, value):
"""Set a configuration property, if not already set."""
if self.get(key) is None:
self.set(key, value)
return self
def setMaster(self, value):
"""Set master URL to connect to."""
self._jconf.setMaster(value)
return self
def setAppName(self, value):
"""Set application name."""
self._jconf.setAppName(value)
return self
def setSparkHome(self, value):
"""Set path where Spark is installed on worker nodes."""
self._jconf.setSparkHome(value)
return self
def setExecutorEnv(self, key=None, value=None, pairs=None):
"""Set an environment variable to be passed to executors."""
if (key is not None and pairs is not None) or (key is None and pairs is None):
raise Exception("Either pass one key-value pair or a list of pairs")
elif key is not None:
self._jconf.setExecutorEnv(key, value)
elif pairs is not None:
for (k, v) in pairs:
self._jconf.setExecutorEnv(k, v)
return self
def setAll(self, pairs):
"""
Set multiple parameters, passed as a list of key-value pairs.
:param pairs: list of key-value pairs to set
"""
for (k, v) in pairs:
self._jconf.set(k, v)
return self
def get(self, key, defaultValue=None):
"""Get the configured value for some key, or return a default otherwise."""
if defaultValue is None: # Py4J doesn't call the right get() if we pass None
if not self._jconf.contains(key):
return None
return self._jconf.get(key)
else:
return self._jconf.get(key, defaultValue)
def getAll(self):
"""Get all values as a list of key-value pairs."""
pairs = []
for elem in self._jconf.getAll():
pairs.append((elem._1(), elem._2()))
return pairs
def contains(self, key):
"""Does this configuration contain a given key?"""
return self._jconf.contains(key)
def toDebugString(self):
"""
Returns a printable version of the configuration, as a list of
key=value pairs, one per line.
"""
return self._jconf.toDebugString()
def _test():
import doctest
(failure_count, test_count) = doctest.testmod(optionflags=doctest.ELLIPSIS)
if failure_count:
exit(-1)
if __name__ == "__main__":
_test()