kanekv

#!/bin/bash

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kanekv

# -*- ksh -*-
#
# If you use the GNU debugger gdb to debug the Python C runtime, you
# might find some of the following commands useful.  Copy this to your
# ~/.gdbinit file and it'll get loaded into gdb automatically when you
# start it up.  Then, at the gdb prompt you can do things like:
#
#    (gdb) pyo apyobjectptr
#    <module 'foobar' (built-in)>
#    refcounts: 1

kanekv

# bash/zsh completion support for core Git.
#
# Copyright (C) 2006,2007 Shawn O. Pearce <[email protected]>
# Conceptually based on gitcompletion (http://gitweb.hawaga.org.uk/).
# Distributed under the GNU General Public License, version 2.0.
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# The contained completion routines provide support for completing:
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#    *) local and remote branch names
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kanekv

http://jeffreystedfast.blogspot.com/2013/08/why-decoding-rfc2047-encoded-headers-is.html
http://jeffreystedfast.blogspot.com/2013/09/time-for-rant-on-mime-parsers.html
https://www.youtube.com/watch?v=JENdgiAPD6c&authuser=1

kanekv

 tc qdisc add dev eth0 root netem delay 1000ms
 tc qdisc del dev eth0 root
 tc qdisc add dev eth0 root netem loss 25%
 tc qdisc add dev eth0 root netem duplicate 50%
 tc qdisc show

kanekv

My initial configuration is: 
    conf.set("spark.cores.max", "16") // 16 map workers, that is 2 workers per machine (see my cluster config below) 
    conf.set("spark.akka.frameSize", "100000") 
    conf.set("spark.executor.memory", "120g") 
    conf.set("spark.reducer.maxMbInFlight", "100000") 
    conf.set("spark.storage.memoryFraction", "0.9") 
    conf.set("spark.shuffle.file.buffer.kb", "1000") 
    conf.set("spark.broadcast.factory", "org.apache.spark.broadcast.HttpBroadcastFactory")   
    conf.set("spark.driver.maxResultSize", "120g") 
    val sc = new SparkContext(conf) 

kanekv

dstat -tdD total,sda,sdb 60