本文整理汇总了Python中pyspark.SparkContext.__name__方法的典型用法代码示例。如果您正苦于以下问题：Python SparkContext.__name__方法的具体用法？Python SparkContext.__name__怎么用？Python SparkContext.__name__使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyspark.SparkContext的用法示例。
在下文中一共展示了SparkContext.__name__方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: SparkContext
# 需要导入模块: from pyspark import SparkContext [as 别名]
# 或者: from pyspark.SparkContext import __name__ [as 别名]
# 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 sys
from random import random
from operator import add
from pyspark import SparkContext
sc= SparkContext(appName="PythonPi")
sc.__name__="PythonPi"
if __name__ == "__main__":
"""
Usage: pi [partitions]
"""
#sc = SparkContext(appName="PythonPi")
partitions = int(sys.argv[1]) if len(sys.argv) > 1 else 2
n = 100000 * partitions
def f(_):
x = random() * 2 - 1
y = random() * 2 - 1
return 1 if x ** 2 + y ** 2 < 1 else 0
count = sc.parallelize(range(1, n + 1), partitions).map(f).reduce(add)
print("Pi is roughly %f" % (4.0 * count / n))