Page not found
All Microsoft Global Microsoft 365 Teams Copilot Windows Surface Xbox Deals Small Business Support Software Windows Apps AI Outlook OneDrive Microsoft Teams OneNote Microsoft Edge Skype PCs & Devices Computers Shop Xbox Accessories VR & mixed reality Certified Refurbished Trade-in for cash Entertainment Xbox Game Pass Ultimate PC Game Pass Xbox games PC and Windows games Movies & TV Business Micro
How to Make a Heatmap – a Quick and Easy Solution
A heatmap is a literal way of visualizing a table of numbers, where you substitute the numbers with colored cells. This is a quick way to make one in R. A heatmap is basically a table that has colors in place of numbers. Colors correspond to the level of the measurement. Each column can be a different metric like above, or it can be all the same like this one. It’s useful for finding highs and low
SparkR by amplab-extras
R frontend for Spark Project maintained by amplab-extras Hosted on GitHub Pages — Theme by mattgraham R on Spark SparkR is an R package that provides a light-weight frontend to use Apache Spark from R. SparkR exposes the Spark API through the RDD class and allows users to interactively run jobs from the R shell on a cluster. NOTE: As of April 2015, SparkR has been officially merged into Apache Spa
Beginner’s guide to R: Introduction
R is hot. Whether measured by more than 10,000 add-on packages, the 95,000+ members of LinkedIn’s R group or the more than 400 R Meetup groups currently in existence, there can be little doubt that interest in the R statistics language, especially for data analysis, is soaring. Why R? It’s free, open source, powerful and highly extensible. “You have a lot of prepackaged stuff that’s already avail
Rの並列化の現状について | wrong, rogue and log
RとHadoopを併用する並列化ソリューションがようやく実用レベルのとば口の一歩手前まできたカンジがある。昨日発表があった、Revolution Analytics(旧REvolution Comupting)のRとHadoopインテグレーションは、並列化処理速度を目指したというよりは、Hadoopの分散ストレージ(HDFS)をうまく使ってテラバイトサイズのデータを解析できるようにしたソリューションだそうだ。 Revolution Analytics Brings Big Data Analysis to R with R http://bit.ly/cD1Pf9 ちなみにRevolution Analyticsとしては、以前の多コア対応を謳っていた並列化ソリューションであるParallelRもサポートをつづけるけれど、主力をこちらのほうにシフトするみたいだね。 いままでも、Amazon
Parallel R
Read it now on the O’Reilly learning platform with a 10-day free trial. O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers. It’s tough to argue with R as a high-quality, cross-platform, open source statistical software product—unless you’re in the business of crunching Big Data. This concise book introduces
Parallel Computing in R
This document discusses using parallel computing in R with the snow package. It provides an overview of using snow to distribute computations across multiple CPUs. Examples are given showing how snow can be used with functions like parApply to speed up matrix multiplication by performing the operation in parallel on a cluster. The document also discusses using snow together with Rmpi and a job sch
RHadoop の紹介
10. > small.ints = to.dfs(1:10) > out = mapreduce(input = small.ints, map = function(k,v) keyval(k, k^2)) > res = from.dfs(out) > colres <- do.call('rbind', lapply(res,"[[",2)) > t(colres) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 4 9 16 25 36 49 64 81 100 > groups = to.dfs(rbinom(32, n = 50, prob = 0.4)) > out = mapreduce(input = groups, reduce = function(k,vv) keyval(k, length(vv
1
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
GitHub - kaneplusplus/cnidaria: Distributed Data Structures for R
Community Question View - Community
Build a Simple Heatmap Using R - 33 Sticks
https://amplab.cs.berkeley.edu/2014/01/26/large-scale-data-analysis-made-easier-with-sparkr/
Distributed R for Big Data
Top 3 R resources for beginners
Package `parallel'
How can R and Hadoop be used together?
http://cdn.oreillystatic.com/en/assets/1/event/61/Distributed%20Data%20Analysis%20with%20Hadoop%20and%20R%20Presentation.pdf
New ways to Hadoop with R