antirez

Meltdown fix impact on Redis performances in virtualized environments

UPDATE: apparently kernel difference may have a serious impact, so I'll redo the test from scratch.

Test performed with AOF enabled, fsync policy 1 second, allowing the rewrites to be triggered.

Command lines used:

djspiewak

Thread Pools

Thread pools on the JVM should usually be divided into the following three categories:

1. CPU-bound
2. Blocking IO
3. Non-blocking IO polling

Each of these categories has a different optimal configuration and usage pattern.

antirez

# LVDB - LLOOGG Memory DB
# Copyriht (C) 2009 Salvatore Sanfilippo <antirez@gmail.com>
# All Rights Reserved

# TODO
# - cron with cleanup of timedout clients, automatic dump
# - the dump should use array startsearch to write it line by line
#   and may just use gets to read element by element and load the whole state.
# - 'help','stopserver','saveandstopserver','save','load','reset','keys' commands.
# - ttl with milliseconds resolution 'ttl a 1000'. Check ttl in dump!

aweiteka

#!/bin/bash

#
# for hacking on cockpit registry web UI
# using a container with bindmounted local js source
#

# on host, one time commands:
# cp containers/kubernetes/registry-dashboard-override.json pkg/kubernetes/override.json
# cp pkg/kubernetes/registry.html pkg/kubernetes/index.html

jaceklaskowski

Requirements

• no upfront installation/agents on remote/slave machines - ssh should be enough
• application components should use third-party software, e.g. HDFS, Spark's cluster, deployed separately
• configuration templating
• environment requires/asserts, i.e. we need a JVM in a given version before doing deployment
• deployment process run from Jenkins

Solution

sergeyf

import numpy as np
from matplotlib import pylab as plt
#from mpltools import style # uncomment for prettier plots
#style.use(['ggplot'])

# generate all bernoulli rewards ahead of time
def generate_bernoulli_bandit_data(num_samples,K):
    CTRs_that_generated_data = np.tile(np.random.rand(K),(num_samples,1))
    true_rewards = np.random.rand(num_samples,K) < CTRs_that_generated_data
    return true_rewards,CTRs_that_generated_data

lelandbatey

Description

This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.

The script is here:

#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"

Results

pascalpoitras

Mouse

---

enable

---

toolmantim

# A simple Makefile alternative to using Grunt for your static asset compilation
#
## Usage
#
#   $ npm install
#
# And then you can run various commands:
#
#   $ make            # compile files that need compiling
#   $ make clean all  # remove target files and recompile from scratch

dergachev

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application: