mitliagkas

#!/bin/sh

export IPYTHON_OPTS="notebook --profile=yannis_spark"

unset SPARK_JAVA_OPTS

export SPARK_DAEMON_JAVA_OPTS="\
-Dspark.default.parallelism=128   \
-Dspark.cores.max=32              \
-Dspark.worker.timeout=500        \

mitliagkas

import rlcompleter, readline
readline.parse_and_bind('tab: complete')

mitliagkas

#ifdef _MSC_VER
# include <intrin.h>
# define CAS(ptr, oldval, newval) \
    _InterlockedCompareExchange(ptr, newval, oldval)
#elif __GNUC__
# if __GNUC__ < 4 || (__GNUC__ == 4 && __GNUC_MINOR__ < 1)
#  error "requires GCC 4.1 or greater"
# endif
# define CAS(ptr, oldval, newval) \
    __sync_val_compare_and_swap(ptr, oldval, newval)

mitliagkas

#include <time.h>

clock_t start, end;
double elapsed;

start = clock();
... /* Do the work. */
end = clock();
elapsed = ((double) (end - start)) / CLOCKS_PER_SEC;

mitliagkas

\begin{algorithm}[tb]
   \caption{Bubble Sort}
   \label{alg:example}
\begin{algorithmic}
   \STATE {\bfseries Input:} data $x_i$, size $m$
   \REPEAT
   \STATE Initialize $noChange = true$.
   \FOR{$i=1$ {\bfseries to} $m-1$}
   \IF{$x_i > x_{i+1}$} 
   \STATE Swap $x_i$ and $x_{i+1}$

mitliagkas

\begin{table}[t]
\caption{Classification accuracies for naive Bayes and flexible 
Bayes on various data sets.}
\label{sample-table}
\vskip 0.15in
\begin{center}
\begin{small}
\begin{sc}
\begin{tabular}{lcccr}
\hline