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Posted to user@spark.apache.org by FeigenB aum <Fe...@mail.com> on 2020/05/18 03:25:52 UTC
FeigenBaumConstant
from pyspark import SparkContext, SparkConf
import random
conf = SparkConf().\
setMaster("spark://192.168.0.39:7077").setAppName("Job Name: Calculate Pi")
sc = SparkContext(conf=conf)
FeigenBaumConstant = 4.6692016
TheFour = 4
# calculate the value of π using Mandelbrot set Randomiser
def inside(p) :
x,y = random.random(),random.random()
return x*x + y*y < 1
num_samples=10**9
print("show me the big number = ", num_samples)
count = sc.parallelize(\
range(0,num_samples))\
.filter(inside)\
.count()
pi = TheFour * count / num_samples
print(" ≈ π is equal to {:0.3f}".format(pi))
sc.stop()
(base) zahid@kub20:~/spark-2.4.5-bin-hadoop2.7/sparkpi$ cd
/home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi ; env
/home/zahid/anaconda3/bin/python /home/zahid/.vscode/extensions/ms-
python.python-2020.5.78807/pythonFiles/lib/python/debugpy/wheels/debugpy/launcher
44527 -- /home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi/.vscode/CalculatePi.py
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
num of samples = 10000000
pi = 3.260
(base) zahid@kub20:~/spark-2.4.5-bin-hadoop2.7/sparkpi$ cd
/home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi ; env
/home/zahid/anaconda3/bin/python /home/zahid/.vscode/extensions/ms-
python.python-2020.5.78807/pythonFiles/lib/python/debugpy/wheels/debugpy/launcher
45337 -- /home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi/.vscode/CalculatePi.py
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
num of samples = 100000000
pi = 3.261
(base) zahid@kub20:~/spark-2.4.5-bin-hadoop2.7/sparkpi$ cd
/home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi ; env
/home/zahid/anaconda3/bin/python /home/zahid/.vscode/extensions/ms-
python.python-2020.5.78807/pythonFiles/lib/python/debugpy/wheels/debugpy/launcher
40507 -- /home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi/.vscode/CalculatePi.py
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
num of samples = 100000000
pi = 3.253
(base) zahid@kub20:~/spark-2.4.5-bin-hadoop2.7/sparkpi$ cd
/home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi ; env
/home/zahid/anaconda3/bin/python /home/zahid/.vscode/extensions/ms-
python.python-2020.5.78807/pythonFiles/lib/python/debugpy/wheels/debugpy/launcher
42593 -- /home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi/.vscode/CalculatePi.py
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
num of samples = 10000000000
[Stage 0:> (0 + 2) /
2](base) zahid@kub20:~/spark-2.4.5-bin-hadoop2.7/sparkpi$ cd
/home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi ; env
/home/zahid/anaconda3/bin/python /home/zahid/.vscode/extensions/ms-
python.python-2020.5.78807/pythonFiles/lib/python/debugpy/wheels/debugpy/launcher
40545 -- /home/zahid/spark-2.4.5-bin-hadoop2.7/sparkpi/.vscode/CalculatePi.py
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
num of samples = 1000000000
pi = 3.142
(base) zahid@kub20:~/spark-2.4.5-bin-hadoop2.7/sparkpi$
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