Re: how to debug this distributed program?

[meInvent bbird]

i follow documentation and add keyfile to indicate the path of private key
but still no response from program,

what is the correct way to do?

cluster = dispy.JobCluster(compute, 
nodes=['ec2-35-162-137-237.us-west-2.compute.amazonaws.com'], 
callback=job_callback, 
keyfile=r"C:\Users\martlee2\Downloads\datacenterusekey.ppk")



On Tuesday, November 1, 2016 at 3:58:24 PM UTC+8, Steve D'Aprano wrote:
> On Tue, 1 Nov 2016 06:40 pm, meInvent bbird wrote:
> 
> > how to debug this distributed program?
> 
> 
> The same way you would debug any other program.
> 
> http://sscce.org/
> 
> 
> 
> 
> 
> -- 
> Steve
> “Cheer up,” they said, “things could be worse.” So I cheered up, and sure
> enough, things got worse.

-- 
https://mail.python.org/mailman/listinfo/python-list

Re: how to debug this distributed program?

[Steve D'Aprano]

On Tue, 1 Nov 2016 06:40 pm, meInvent bbird wrote:

> how to debug this distributed program?


The same way you would debug any other program.

http://sscce.org/





-- 
Steve
“Cheer up,” they said, “things could be worse.” So I cheered up, and sure
enough, things got worse.

-- 
https://mail.python.org/mailman/listinfo/python-list

how to debug this distributed program?

[meInvent bbird]

https://drive.google.com/open?id=0Bxs_ao6uuBDUSEc5S3U3Nko5ZjA


A. i am not sure whether parameter start from 0 or 1
n[0] or n[1] in compute function

B. it run a very long time and nothing to see in amazon linux instance
there is no python program in top command

C. in distributed programming web site, there is no authentication method
using private key in python program,  how do distributed program access
the nodes in amazon cloud when run python program below in window locally?

import random, dispy

def compute(n): # executed on nodes
import random, time, socket
name = socket.gethostname()
cur_best = 1
for ii in range(n[0],n[0]):
for jj in range(n[1],n[1]):
for kk in range(n[2],n[3],100): 
dispy_provisional_result((name, r))
cur_best = r
time.sleep(0.1)
# final result
return (name, cur_best)

def job_callback(job): # executed at the client
if job.status == dispy.DispyJob.ProvisionalResult:
#if job.result[1] < 0.005:
# acceptable result; terminate jobs
print('%s computed: %s %s %s %s' % (job.result[0], job.result[1], 
job.result[2], job.result[3], job.result[4]))
# 'jobs' and 'cluster' are created in '__main__' below
for j in jobs:
if j.status in [dispy.DispyJob.Created, dispy.DispyJob.Running,
dispy.DispyJob.ProvisionalResult]:
cluster.cancel(j)

if __name__ == '__main__':
#cluster = dispy.JobCluster(compute, callback=job_callback)
cluster = dispy.JobCluster(compute, 
nodes=['ec2-100-162-137-237.us-west-2.compute.amazonaws.com'], 
callback=job_callback)
jobs = []
prevk = 1
count = 0
for ii in range(1,2):
for jj in range(1,2000):
for kk in range(1,2000,100):
if ii < jj and jj < kk:
job = cluster.submit([ii,jj,prevk,kk])
prevk = kk
if job is None:
print('creating job %s failed!' % n)
continue
job.id = count
count = count + 1
jobs.append(job)
cluster.wait()
cluster.print_status()
cluster.close()
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