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@article{floratou2014sql, | |
title={SQL-on-Hadoop: full circle back to shared-nothing database architectures}, | |
author={Floratou, Avrilia and Minhas, Umar Farooq and {\"O}zcan, Fatma}, | |
journal={Proceedings of the VLDB Endowment}, | |
volume={7}, | |
number={12}, | |
pages={1295--1306}, | |
year={2014}, | |
publisher={VLDB Endowment} | |
} |
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date | category | task | complete | notes | |
---|---|---|---|---|---|
2018-10-15 | support | type and share meeting notes from Friday with Duncan | 0 | ||
2018-10-15 | revise | rewrite software alchemy example for clarity following Duncan's feedback | 0 |
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clark@campus-108-089 ~/dev/Rtesseract (master) | |
$ ./configure | |
checking for pkg-config... /usr/local/bin/pkg-config | |
Package tesseract was not found in the pkg-config search path. | |
Perhaps you should add the directory containing `tesseract.pc' | |
to the PKG_CONFIG_PATH environment variable | |
No package 'tesseract' found | |
Package tesseract was not found in the pkg-config search path. | |
Perhaps you should add the directory containing `tesseract.pc' | |
to the PKG_CONFIG_PATH environment variable |
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#!/usr/bin/env Rscript | |
# 2018-06-04 11:26:12 | |
# Automatically generated from R by autoparallel version 0.0.1 | |
library(parallel) | |
nworkers = 2 | |
timeout = 600 |
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# Given observations of linear functions f and g at points a and b this | |
# calculates the integral of f * g from a to b. | |
# | |
# Looks like it will already work as a vectorized function. Sweet! | |
inner_one_piece = function(a, b, fa, fb, ga, gb) | |
{ | |
# Roughly following my notes | |
fslope = (fb - fa) / (b - a) | |
gslope = (gb - ga) / (b - a) |
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# Following: | |
# https://cran.r-project.org/web/packages/rslurm/vignettes/rslurm.html | |
library(rslurm) | |
test_func <- function(par_mu, par_sd) { | |
samp <- rnorm(10^6, par_mu, par_sd) | |
c(s_mu = mean(samp), s_sd = sd(samp)) | |
} |
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#' Split And Append Results To CSV File | |
#' | |
#' x will be split by f and each group will be appended to a directory of | |
#' csv files named according to f | |
#' | |
#' @param x data frame to split | |
#' @param f factor defining splits | |
#' @param ... further arguments to split | |
#' @param dirname character directory, will be created if doesn't exist | |
#' @return NULL |
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# Mon Aug 28 16:33:46 PDT 2017 | |
# | |
# sweep() used to implement scale() is inefficient. Profiling shows that | |
# only 2% of the time is spent in colMeans. The only other thing to do is | |
# subtract the mean, which should be fast, but isn't because memory | |
# layout requires a transpose to use recycling (broadcasting). | |
# | |
# But I don't know how to do any better short of writing in C | |
library(microbenchmark) |
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cov_chunked = function(x, nchunks = 2L) | |
{ | |
p = ncol(x) | |
indices = parallel::splitIndices(p, nchunks) | |
diagonal_blocks = lapply(indices, function(idx) cov(x[, idx, drop = FALSE])) | |
upper_right_indices = combn(indices, 2, simplify = FALSE) |
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# From wlandau | |
# https://github.com/duncantl/CodeDepends/issues/19 | |
library(CodeDepends) | |
#' Recursively Find Global Variables | |
#' | |
#' TODO: Modify this to work without requiring that the code be evaluated | |
#' Probably means we can't use codetools::findGlobals |
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