# # 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") >>> 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") >>> conf.get("spark.home") u'/path' >>> conf.setExecutorEnv("VAR1", "value1") >>> conf.setExecutorEnv(pairs = [("VAR3", "value3"), ("VAR4", "value4")]) >>> 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()