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#!/bin/bash

list=/etc/openvpn/server/ipp.txt

ip_mask=255.255.255.0

# IFS=, is used for "read", as comma is the seperator in ipp

OLDIFS=$IFS
IFS=,

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{"err":["Välkommen","Välkommen till Växla upp 2 !"]}

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[user]
name = Sunny
email = Sunny

[diff]
tool = vimdiff

[difftool]
prompt = true

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Spark - High availability

Components in play

As a reminder, here are the components in play to run an application:

• The cluster:
  • Spark Master: coordinates the resources
  • Spark Workers: offer resources to run the applications
• The application:

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# I was having problems to create docker images for spark-on-k8s using docker-image-tool.sh in spark (it always gives spark-r).
# Thus here is the docker file to creat for running pyspark.
# The image is available on sunnybingome/spark8s:pyspark240py368 with spark 2.4.0
# For clie-mode (interactive mode), please use pipenv to ensure py version. The image is in using py 3.6(.8).

# Sunny modified from spark-2.4.0-bin-hadoop2.7/kubernetes/dockerfiles/spark/Dockerfile

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with

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This is a gist of collection of simple spark tests for Jupyter and spark-submit.

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import socket
print([l for l in ([ip for ip in socket.gethostbyname_ex(socket.gethostname())[2] 
if not ip.startswith("127.")][:1], [[(s.connect(('8.8.8.8', 53)), 
s.getsockname()[0], s.close()) for s in [socket.socket(socket.AF_INET, 
socket.SOCK_DGRAM)]][0][1]]) if l][0][0])

# limit: only one IP, not getting multi-NIC IPs

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# Import module from previous step
Import-Module -Name posh-git

function Test-Administrator {
    $user = [Security.Principal.WindowsIdentity]::GetCurrent();
    (New-Object Security.Principal.WindowsPrincipal $user).IsInRole([Security.Principal.WindowsBuiltinRole]::Administrator)
}

function mklink { cmd /c mklink $args }

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# pip2
absl-py==0.2.2
adium-theme-ubuntu==0.3.4
astor==0.6.2
backports.functools-lru-cache==1.5
backports.shutil-get-terminal-size==1.0.0
backports.weakref==1.0.post1
bleach==1.5.0
certifi==2018.4.16
chardet==3.0.4

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apt-get purge cuda && \
apt-get purge libcudnn6 && \
apt-get purge libcudnn6-dev && \
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.0.176-1_amd64.deb && \
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libcudnn7_7.0.5.15-1+cuda9.0_amd64.deb && \
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libcudnn7-dev_7.0.5.15-1+cuda9.0_amd64.deb && \
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libnccl2_2.1.4-1+cuda9.0_amd64.deb && \
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libnccl-dev_2.1.4-1+cuda9.0_amd64.deb && \
dpkg -i cuda-repo-ubuntu1604_9.0.176-1_amd64.deb && \
dpkg -i libcudnn7_7.0.5.15-1+cuda9.0_amd64.deb && \