MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

tmyymmt

// see https://gist.github.com/2382341

// scalaz for only solution3
import scalaz._
import Scalaz._

object SolutionForMultiNestedMatchforMyStudy {

  def f(num: Int): Option[Int] = {
    num match {

ngocdaothanh

package recfun

import scala.collection.mutable.ListBuffer
import common._

/** https://class.coursera.org/progfun-2012-001/assignment/view?assignment_id=4 */
object Main {
  def main(args: Array[String]) {
    println("Pascal's Triangle")
    for (row <- 0 to 10) {

mheadd

#!/bin/bash
UP=$(pgrep mysql | wc -l);
if [ "$UP" -ne 1 ];
then
        echo "MySQL is down.";
        sudo service mysql start

else
        echo "All is well.";
fi

rxaviers

People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

kevin-smets

Default

Powerlevel10k

lalyos

Ambari uses a local postgres db by default.This page describes how to use ambari-server with remote postgres server.

Install

Ambari is installed on centos 6.4 with the following command:

curl -so /etc/yum.repos.d/ambari.repo http://public-repo-1.hortonworks.com/ambari/centos6/1.x/GA/ambari.repo
yum repolist
yum -y install ambari-server

crosbymichael

#!/bin/bash

set -e 

apt-get install -y curl python-setuptools python-pip python-dev python-protobuf

# zookeeper
apt-get install -y zookeeperd
echo 1 | dd of=/var/lib/zookeeper/myid

welbornprod

#!/bin/bash

# Here are some embedded Python examples using Python3.
# They are put into functions for separation and clarity.


# Simple usage, only using python to print the date.
# This is not really a good example, because the `date`
# command works just as well.
function date_time {

jkbradley

/*
This example uses Scala.  Please see the MLlib documentation for a Java example.

Try running this code in the Spark shell.  It may produce different topics each time (since LDA includes some randomization), but it should give topics similar to those listed above.

This example is paired with a blog post on LDA in Spark: http://databricks.com/blog
Spark: http://spark.apache.org/
*/

import scala.collection.mutable