hrbrmstr

This thread http://mail-archives.apache.org/mod_mbox/drill-user/201707.mbox/%3cCAHfzKEoYeE08GXtF3pJsCfExTJgJPj7nx9bjTnW3a=hgMJAxhQ@mail.gmail.com%3e from the Drill mailing list has a good discussion abt that as well as this (open) JIRA https://issues.apache.org/jira/browse/DRILL-3534.

You can kinda do this with Spark http://aseigneurin.github.io/2017/03/14/incrementally-loaded-parquet-files.html but I actually like the filesystem-based manual partitions better (but that's just me).

What I tend to do is have data-source and date-based partitions for parquet files. So, say for one of our Sonar internet studies (I'll use our 3 SMTP scans for this example) I do something like:

• /data/sonar/smtp/port25/yyyy/mm/dd/port25.parquet
• /data/sonar/smtp/port465/yyyy/mm/dd/port465.parquet
• /data/sonar/smtp/port587/yyyy/mm/dd/port587.parquet

sjewo

library(tmap)
library(sp)
library(rgeos)
library(maptools)


# Cartogram 
# algorithm from  Dougenik, Chrisman, Niemeyer (1985): An Algorithm To Construct Continuous Area Cartograms. In: Professional Geographer, 37(1), 75-81.
cartogram <- function(shp, weight, itermax=15, maxSizeError=1.0001) {

xiaodaigh

#install.packages(c("devtools","svSockets")) # if not already installed
#devtools::install_github("gosocket","analytixware") # if not already installed
#devtools::install_github("shinysky","analytixware") # if not already installed

library(shiny)
library(shinysky)
library(gosocket)

# Define server logic required to generate and plot a random distribution
shinyServer(function(input, output,session) {

spartanroc

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dsparks

SmoothCoefficientPlot <- function(models, modelnames = "", removeintercept = FALSE){
  # models must be a list()

  Alphas <- seq(1, 99, 2) / 100

  Multiplier <- qnorm(1 - Alphas / 2)
  zzTransparency <<- 1/(length(Multiplier)/4)
  CoefficientTables <- lapply(models, function(x){summary(x)$coef})
  TableRows <- unlist(lapply(CoefficientTables, nrow))

dsparks

CoefficientPlot <- function(models, alpha = 0.05, modelnames = ""){
  # models must be a list()

  Multiplier <- qnorm(1 - alpha / 2)
  CoefficientTables <- lapply(models, function(x){summary(x)$coef})
  TableRows <- unlist(lapply(CoefficientTables, nrow))

  if(modelnames[1] == ""){
    ModelNameLabels <- rep(paste("Model", 1:length(TableRows)), TableRows)
    } else {