HarryZhu harryprince

https://kafka.apache.org/quickstart

wget http://apache.claz.org/kafka/2.1.0/kafka_2.12-2.1.0.tgz
tar -xzf kafka_2.12-2.1.0.tgz

bin/zookeeper-server-start.sh config/zookeeper.properties
bin/kafka-server-start.sh config/server.properties

bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test

Building Arrow R Bindings in Windows

This doc captures results from investigating how to build the Arrow R bindings in Windows. The following options were explored:

Building Arrow in MSys and bindings in RTools.
Building Arrow and bindings in RTools.

The most promising long-term solution is to write a CMake generator that can be run from RTools; short term, we can continue making progress compiling Arrow from MSys.

This document explains other approaches considered and provides additional details.

A script to demonstrate using TensorFlow in Spark with Amazon EMR and sparklyr.

Create an EMR cluster for sparklyr, connect to EMR and install required tools:

install.packages(tensorflow)
devtools::install_github("rstudio/tfdeploy")

Connect to Spark using sparklyr, copy some data and the mtcars TensorFlow model:

Installing ubuntu snappy core on raspberry pi 2

Translated to os x from https://developer.ubuntu.com/en/snappy/start/#snappy-raspi2

Download the image

http://people.canonical.com/~platform/snappy/raspberrypi2/

Locate your sd card

Moved to https://github.com/yihui/shiny-apps/tree/master/voice

	#plotly box or lasso select linked to
	# DT data table
	# using Wage data
	# the out group: is sex:Male, region:Middle Atlantic +


	library(ggplot2)
	library(plotly)
	library(dplyr)
	library(ISLR)

	############################################################################################
	############################################################################################
	# Plotting networks in R - an example how to plot a network and
	# customize its appearance in Cytoscape directly from R using
	# the RCy3 package
	############################################################################################
	############################################################################################
	# Clear workspace
	# rm(list = ls())
	############################################################################################

	## Purpose: illustrate use of magick, gganimate, and purrr
	## Inspiration:
	## https://rud.is/b/2016/07/27/u-s-drought-animations-with-the-witchs-brew-purrr-broom-magick/
	## and subsequent discussion on magick vs gganimate:
	## https://twitter.com/hrbrmstr/status/758304420224466944
	library(purrr)
	library(ggplot2)
	library(gganimate)
	library(animation)
	library(magick)

	#!/usr/bin/r

	library(inline)
	library(rbenchmark)

	## openMPCode example from Rcpp/examples/OpenMP/ by Dirk E.

	openMPCode <- '
	// assign to C++ vector
	std::vector<double> x = Rcpp::as<std::vector< double > >(xs);

	This Shiny application is designed to help analysing trading strategies. It is an ongoing project that I improve when time allows. Feel free to get in touch should you have any suggestion.

	*How to use the App as it is?
	The App uses as input several csv files (one for each strategy). Each file has two columns: date and daily return. There is an example of such a file in the Github repository. The code is essentially made of 3 files.
	-ui.R: controls the layout and appearance of the app
	-server.R: contains the instructions needed to build the app. You can load as much strategies as you want as long as the corresponding csv file has the right format (see below).
	-shinyStrategyGeneral.R: loads the required packages and launches the app
	put ui.R and server.R file in a separate directory

	In the server.R file change the inputPath, inputFile and keepColumns parameters to match your setting. The first two are self explanatory the third one is a list of column names within the csv file. Keep only date and daily return