Tag: source

Radoop 0.3 launched- Open Source Graphical Analytics meets Big Data

What is Radoop? Quite possibly an exciting mix of analytics and big data computing

 

http://blog.radoop.eu/?p=12

What is Radoop?

Hadoop is an excellent tool for analyzing large data sets, but it lacks an easy-to-use graphical interface. RapidMiner is an excellent tool for data analytics, but its data size is limited by the memory available, and a single machine is often not enough to run the analyses on time. In this project, we combine the strengths of both projects and provide a RapidMiner extension for editing and running ETL, data analytics and machine learning processes over Hadoop.

We have closely integrated the highly optimized data analytics capabilities of Hive and Mahout, and the user-friendly interface of RapidMiner to form a powerful and easy-to-use data analytics solution for Hadoop.

 

and what’s new

http://blog.radoop.eu/?p=198

Radoop 0.3 released – fully graphical big data analytics

Today, Radoop had a major step forward with its 0.3 release. The new version of the visual big data analytics package adds full support for all major Hadoop distributions used these days: Apache Hadoop 0.20.2, 0.20.203, 1.0 and Cloudera’s Distribution including Apache Hadoop 3 (CDH3). It also adds support for large clusters by allowing the namenode, the jobtracker and the Hive server to reside on different nodes.

As Radoop’s promise is to make big data analytics easier, the 0.3 release is also focused on improving the user interface. It has an enhanced breakpointing system which allows to investigate intermediate results, and it adds dozens of quick fixes, so common process design mistakes get much easier to solve.

There are many further improvements and fixes, so please consult the release notes for more details. Radoop is in private beta mode, but heading towards a public release in Q2 2012. If you would like to get early access, then please apply at the signup page or describe your use case in email (beta at radoop.eu).

Radoop 0.3 (15 February 2012)

  • Support for Apache Hadoop 0.20.2, 0.20.203, 1.0 and Cloudera’s Distribution Including Apache Hadoop 3 (CDH3) in a single release
  • Support for clusters with separate master nodes (namenode, jobtracker, Hive server)
  • Enhanced breakpointing to evaluate intermediate results
  • Dozens of quick fixes for the most common process design errors
  • Improved process design and error reporting
  • New welcome perspective to help in the first steps
  • Many bugfixes and performance improvements

Radoop 0.2.2 (6 December 2011)

  • More Aggregate functions and distinct option
  • Generate ID operator for convenience
  • Numerous bug fixes and improvements
  • Improved user interface

Radoop 0.2.1 (16 September 2011)

  • Set Role and Data Multiplier operators
  • Management panel for testing Hadoop connections
  • Stability improvements for Hive access
  • Further small bugfixes and improvements

Radoop 0.2 (26 July 2011)

  • Three new algoritms: Fuzzy K-Means, Canopy, and Dirichlet clustering
  • Three new data preprocessing operators: Normalize, Replace, and Replace Missing Values
  • Significant speed improvements in data transmission and interactive analytics
  • Increased stability and speedup for K-Means
  • More flexible settings for Join operations
  • More meaningful error messages
  • Other small bugfixes and improvements

Radoop 0.1 (14 June 2011)

Initial release with 26 operators for data transmission, data preprocessing, and one clustering algorithm.

Note that Rapid Miner also has a great R extension so you can use R, a graphical interface and big data analytics is now easier and more powerful than ever.


Note on Internet Privacy (Updated)and a note on DNSCrypt

I noticed the brouaha on Google’s privacy policy. I am afraid that social networks capture much more private information than search engines (even if they integrate my browser history, my social network, my emails, my search engine keywords) – I am still okay. All they are going to do is sell me better ads (maybe than just flood me with ads hoping to get a click). Of course Microsoft should take it one step forward and capture data from my desktop as well for better ads, that would really complete the curve. In any case , with the Patriot Act, most information is available to the Government anyway.

But it does make sense to have an easier to understand privacy policy, and one of my disappointments is the complete lack of visual appeal in such notices. Make things simple as possible, but no simpler, as Al-E said.

 

Privacy activists forget that ads run on models built on AGGREGATED data, and most models are scored automatically. Unless you do something really weird and fake like, chances are the data pertaining to you gets automatically collected, algorithmic-ally aggregated, then modeled and scored, and a corresponding ad to your score, or segment is shown to you. Probably no human eyes see raw data (but big G can clarify that)

 

( I also noticed Google gets a lot of free advice from bloggers. hey, if you were really good at giving advice to Google- they WILL hire you !)

on to another tool based (than legalese based approach to privacy)

I noticed tools like DNSCrypt increase internet security, so that all my integrated data goes straight to people I am okay with having it (ad sellers not governments!)

Unfortunately it is Mac Only, and I will wait for Windows or X based tools for a better review. I noticed some lag in updating these tools , so I can only guess that the boys of Baltimore have been there, so it is best used for home users alone.

 

Maybe they can find a chrome extension for DNS dummies.

http://www.opendns.com/technology/dnscrypt/

Why DNSCrypt is so significant

In the same way the SSL turns HTTP web traffic into HTTPS encrypted Web traffic, DNSCrypt turns regular DNS traffic into encrypted DNS traffic that is secure from eavesdropping and man-in-the-middle attacks.  It doesn’t require any changes to domain names or how they work, it simply provides a method for securely encrypting communication between our customers and our DNS servers in our data centers.  We know that claims alone don’t work in the security world, however, so we’ve opened up the source to our DNSCrypt code base and it’s available onGitHub.

DNSCrypt has the potential to be the most impactful advancement in Internet security since SSL, significantly improving every single Internet user’s online security and privacy.

and

http://dnscurve.org/crypto.html

The DNSCurve project adds link-level public-key protection to DNS packets. This page discusses the cryptographic tools used in DNSCurve.

Elliptic-curve cryptography

DNSCurve uses elliptic-curve cryptography, not RSA.

RSA is somewhat older than elliptic-curve cryptography: RSA was introduced in 1977, while elliptic-curve cryptography was introduced in 1985. However, RSA has shown many more weaknesses than elliptic-curve cryptography. RSA’s effective security level was dramatically reduced by the linear sieve in the late 1970s, by the quadratic sieve and ECM in the 1980s, and by the number-field sieve in the 1990s. For comparison, a few attacks have been developed against some rare elliptic curves having special algebraic structures, and the amount of computer power available to attackers has predictably increased, but typical elliptic curves require just as much computer power to break today as they required twenty years ago.

IEEE P1363 standardized elliptic-curve cryptography in the late 1990s, including a stringent list of security criteria for elliptic curves. NIST used the IEEE P1363 criteria to select fifteen specific elliptic curves at five different security levels. In 2005, NSA issued a new “Suite B” standard, recommending the NIST elliptic curves (at two specific security levels) for all public-key cryptography and withdrawing previous recommendations of RSA.

Some specific types of elliptic-curve cryptography are patented, but DNSCurve does not use any of those types of elliptic-curve cryptography.

 

Analytics for Cyber Conflict

 

The emerging use of Analytics and Knowledge Discovery in Databases for Cyber Conflict and Trade Negotiations

 

The blog post is the first in series or articles on cyber conflict and the use of analytics for targeting in both offense and defense in conflict situations.

 

It covers knowledge discovery in four kinds of databases (so chosen because of perceived importance , sensitivity, criticality and functioning of the geopolitical economic system)-

  1. Databases on Unique Identity Identifiers- including next generation biometric databases connected to Government Initiatives and Banking, and current generation databases of identifiers like government issued documents made online
  2. Databases on financial details -This includes not only traditional financial service providers but also online databases with payment details collected by retail product selling corporates like Sony’s Playstation Network, Microsoft ‘s XBox and
  3. Databases on contact details – including those by offline businesses collecting marketing databases and contact details
  4. Databases on social behavior- primarily collected by online businesses like Facebook , and other social media platforms.

It examines the role of

  1. voluntary privacy safeguards and government regulations ,

  2. weak cryptographic security of databases,

  3. weakness in balancing marketing ( maximized data ) with privacy (minimized data)

  4. and lastly the role of ownership patterns in database owning corporates

A small distinction between cyber crime and cyber conflict is that while cyber crime focusses on stealing data, intellectual property and information  to primarily maximize economic gains

cyber conflict focuses on stealing information and also disrupt effective working of database backed systems in order to gain notional competitive advantages in economics as well as geo-politics. Cyber terrorism is basically cyber conflict by non-state agents or by designated terrorist states as defined by the regulations of the “target” entity. A cyber attack is an offensive action related to cyber-infrastructure (like the Stuxnet worm that disabled uranium enrichment centrifuges of Iran). Cyber attacks and cyber terrorism are out of scope of this paper, we will concentrate on cyber conflicts involving databases.

Some examples are given here-

Types of Knowledge Discovery in –

1) Databases on Unique Identifiers- including biometric databases.

Unique Identifiers or primary keys for identifying people are critical for any intensive knowledge discovery program. The unique identifier generated must be extremely secure , and not liable to reverse engineering of the cryptographic hash function.

For biometric databases, an interesting possibility could be determining the ethnic identity from biometric information, and also mapping relatives. Current biometric information that is collected is- fingerprint data, eyes iris data, facial data. A further feature could be adding in voice data as a part of biometric databases.

This is subject to obvious privacy safeguards.

For example, Google recently unveiled facial recognition to unlock Android 4.0 mobiles, only to find out that the security feature could easily be bypassed by using a photo of the owner.

 

 

Example of Biometric Databases

In Afghanistan more than 2 million Afghans have contributed iris, fingerprint, facial data to a biometric database. In India, 121 million people have already been enrolled in the largest biometric database in the world. More than half a million customers of the Tokyo Mitsubishi Bank are are already using biometric verification at ATMs.

Examples of Breached Online Databases

In 2011, Playstation Network by Sony (PSN) lost data of 77 million customers including personal information and credit card information. Additionally data of 24 million customers were lost by Sony’s Sony Online Entertainment. The websites of open source platforms like SourceForge, WineHQ and Kernel.org were also broken into 2011. Even retailers like McDonald and Walgreen reported database breaches.

 

The role of cyber conflict arises in the following cases-

  1. Databases are online for accessing and authentication by proper users. Databases can be breached remotely by non-owners ( or “perpetrators”) non with much lesser chance of intruder identification, detection and penalization by regulators, or law enforcers (or “protectors”) than offline modes of intellectual property theft.

  2. Databases are valuable to external agents (or “sponsors”) subsidizing ( with finance, technology, information, motivation) the perpetrators for intellectual property theft. Databases contain information that can be used to disrupt the functioning of a particular economy, corporation (or “ primary targets”) or for further chain or domino effects in accessing other data (or “secondary targets”)

  3. Loss of data is more expensive than enhanced cost of security to database owners

  4. Loss of data is more disruptive to people whose data is contained within the database (or “customers”)

So the role play for different people for these kind of databases consists of-

1) Customers- who are in the database

2) Owners -who own the database. They together form the primary and secondary targets.

3) Protectors- who help customers and owners secure the databases.

and

1) Sponsors- who benefit from the theft or disruption of the database

2) Perpetrators- who execute the actual theft and disruption in the database

The use of topic models and LDA is known for making data reduction on text, and the use of data visualization including tied to GPS based location data is well known for investigative purposes, but the increasing complexity of both data generation and the sophistication of machine learning driven data processing makes this an interesting area to watch.

 

 

The next article in this series will cover-

the kind of algorithms that are currently or being proposed for cyber conflict, the role of non state agents , and what precautions can knowledge discovery in databases practitioners employ to avoid breaches of security, ethics, and regulation.

Citations-

  1. Michael A. Vatis , CYBER ATTACKS DURING THE WAR ON TERRORISM: A PREDICTIVE ANALYSIS Dartmouth College (Institute for Security Technology Studies).
  2. From Data Mining to Knowledge Discovery in Databases Usama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyt

Interview JJ Allaire Founder, RStudio

Here is an interview with JJ Allaire, founder of RStudio. RStudio is the IDE that has overtaken other IDE within the R Community in terms of ease of usage. On the eve of their latest product launch, JJ talks to DecisionStats on RStudio and more.

Ajay-  So what is new in the latest version of RStudio and how exactly is it useful for people?

JJ- The initial release of RStudio as well as the two follow-up releases we did last year were focused on the core elements of using R: editing and running code, getting help, and managing files, history, workspaces, plots, and packages. In the meantime users have also been asking for some bigger features that would improve the overall work-flow of doing analysis with R. In this release (v0.95) we focused on three of these features:

Projects. R developers tend to have several (and often dozens) of working contexts associated with different clients, analyses, data sets, etc. RStudio projects make it easy to keep these contexts well separated (with distinct R sessions, working directories, environments, command histories, and active source documents), switch quickly between project contexts, and even work with multiple projects at once (using multiple running versions of RStudio).

Version Control. The benefits of using version control for collaboration are well known, but we also believe that solo data analysis can achieve significant productivity gains by using version control (this discussion on Stack Overflow talks about why). In this release we introduced integrated support for the two most popular open-source version control systems: Git and Subversion. This includes changelist management, file diffing, and browsing of project history, all right from within RStudio.

Code Navigation. When you look at how programmers work a surprisingly large amount of time is spent simply navigating from one context to another. Modern programming environments for general purpose languages like C++ and Java solve this problem using various forms of code navigation, and in this release we’ve brought these capabilities to R. The two main features here are the ability to type the name of any file or function in your project and go immediately to it; and the ability to navigate to the definition of any function under your cursor (including the definition of functions within packages) using a keystroke (F2) or mouse gesture (Ctrl+Click).

Ajay- What’s the product road map for RStudio? When can we expect the IDE to turn into a full fledged GUI?

JJ- Linus Torvalds has said that “Linux is evolution, not intelligent design.” RStudio tries to operate on a similar principle—the world of statistical computing is too deep, diverse, and ever-changing for any one person or vendor to map out in advance what is most important. So, our internal process is to ship a new release every few months, listen to what people are doing with the product (and hope to do with it), and then start from scratch again making the improvements that are considered most important.

Right now some of the things which seem to be top of mind for users are improved support for authoring and reproducible research, various editor enhancements including code folding, and debugging tools.

What you’ll see is us do in a given release is to work on a combination of frequently requested features, smaller improvements to usability and work-flow, bug fixes, and finally architectural changes required to support current or future feature requirements.

While we do try to base what we work on as closely as possible on direct user-feedback, we also adhere to some core principles concerning the overall philosophy and direction of the product. So for example the answer to the question about the IDE turning into a full-fledged GUI is: never. We believe that textual representations of computations provide fundamental advantages in transparency, reproducibility, collaboration, and re-usability. We believe that writing code is simply the right way to do complex technical work, so we’ll always look for ways to make coding better, faster, and easier rather than try to eliminate coding altogether.

Ajay -Describe your journey in science from a high school student to your present work in R. I noticed you have been very successful in making software products that have been mostly proprietary products or sold to companies.

Why did you get into open source products with RStudio? What are your plans for monetizing RStudio further down the line?

JJ- In high school and college my principal areas of study were Political Science and Economics. I also had a very strong parallel interest in both computing and quantitative analysis. My first job out of college was as a financial analyst at a government agency. The tools I used in that job were SAS and Excel. I had a dim notion that there must be a better way to marry computation and data analysis than those tools, but of course no concept of what this would look like.

From there I went more in the direction of general purpose computing, starting a couple of companies where I worked principally on programming languages and authoring tools for the Web. These companies produced proprietary software, which at the time (between 1995 and 2005) was a workable model because it allowed us to build the revenue required to fund development and to promote and distribute the software to a wider audience.

By 2005 it was however becoming clear that proprietary software would ultimately be overtaken by open source software in nearly all domains. The cost of development had shrunken dramatically thanks to both the availability of high-quality open source languages and tools as well as the scale of global collaboration possible on open source projects. The cost of promoting and distributing software had also collapsed thanks to efficiency of both distribution and information diffusion on the Web.

When I heard about R and learned more about it, I become very excited and inspired by what the project had accomplished. A group of extremely talented and dedicated users had created the software they needed for their work and then shared the fruits of that work with everyone. R was a platform that everyone could rally around because it worked so well, was extensible in all the right ways, and most importantly was free (as in speech) so users could depend upon it as a long-term foundation for their work.

So I started RStudio with the aim of making useful contributions to the R community. We started with building an IDE because it seemed like a first-rate development environment for R that was both powerful and easy to use was an unmet need. Being aware that many other companies had built successful businesses around open-source software, we were also convinced that we could make RStudio available under a free and open-source license (the AGPLv3) while still creating a viable business. At this point RStudio is exclusively focused on creating the best IDE for R that we can. As the core product gets where it needs to be over the next couple of years we’ll then also begin to sell other products and services related to R and RStudio.

About-

http://rstudio.org/docs/about

Jjallaire

JJ Allaire

JJ Allaire is a software engineer and entrepreneur who has created a wide variety of products including ColdFusion,Windows Live Writer, Lose It!, and RStudio.

From http://en.wikipedia.org/wiki/Joseph_J._Allaire
In 1995 Joseph J. (JJ) Allaire co-founded Allaire Corporation with his brother Jeremy Allaire, creating the web development tool ColdFusion.[1] In March 2001, Allaire was sold to Macromedia where ColdFusion was integrated into the Macromedia MX product line. Macromedia was subsequently acquired by Adobe Systems, which continues to develop and market ColdFusion.
After the sale of his company, Allaire became frustrated at the difficulty of keeping track of research he was doing using Google. To address this problem, he co-founded Onfolio in 2004 with Adam Berrey, former Allaire co-founder and VP of Marketing at Macromedia.
On March 8, 2006, Onfolio was acquired by Microsoft where many of the features of the original product are being incorporated into the Windows Live Toolbar. On August 13, 2006, Microsoft released the public beta of a new desktop blogging client called Windows Live Writer that was created by Allaire’s team at Microsoft.
Starting in 2009, Allaire has been developing a web-based interface to the widely used R technical computing environment. A beta version of RStudio was publicly released on February 28, 2011.
JJ Allaire received his B.A. from Macalester College (St. Paul, MN) in 1991.
RStudio-

RStudio is an integrated development environment (IDE) for R which works with the standard version of R available from CRAN. Like R, RStudio is available under a free software license. RStudio is designed to be as straightforward and intuitive as possible to provide a friendly environment for new and experienced R users alike. RStudio is also a company, and they plan to sell services (support, training, consulting, hosting) related to the open-source software they distribute.

R Concerto- Computer Adaptive Tests

A really nice use for R is education

http://www.psychometrics.cam.ac.uk/page/300/concerto-testing-platform.htm

Concerto: R-Based Online Adaptive Testing Platform

Concerto is a web based, adaptive testing platform for creating and running rich, dynamic tests. It combines the flexibility of HTML presentation with the computing power of the R language, and the safety and performance of the MySQL database. It’s totally free for commercial and academic use, and it’s open source. If you have any questions, you feel like generously supporting the project, or you want to develop a commerical test on the platform, feel free to email Michal Kosinski.

We rely as much as possible on popular open source packages in order to maximize the safety and reliability of the system, and to ensure that its elements are kept up-to-date.

Why choose Concerto?

  • Simple to use: Check our Step-by-Step tutorial to see how to create a test in minutes.
  • Flexibility: You can use the R engine to apply virtually any IRT or CAT models.
  • Scalability: Modular design, MySQL tables, and low system requirements allow the testing of thousands for pennies.
  • Reliability: Concerto relies on popular, constantly updated, and reliable elements used by millions of users world-wide.
  • Elegant feedback and items: The flexibility of the HTML layer and the power of R allow you to use (or generate on the fly!) polished multi-media items, as well as feedback full of graphs and charts generated by R for each test taker.
  • Low costs: It’s free and open-source!

Demonstration tests:

 Concerto explained:

Get Concerto:

Before installing concerto you may prefer to test it using a demo account on our server.Email Michal Kosinski in order to get demo account.

Training in Concerto:

Next session 9th Dec 2011: book early!

Commercial tests and Concerto:

Concerto is an open-source project so anyone can use it free of charge, even for commercial purposes. However, it might be faster and less expensive to hire our experienced team to develop your test, provide support and maintenance, and take responsibility for its smooth and reliable operation. Contact us!

 

SAS Institute Financials 2011

SAS Institute has release it’s financials for 2011 at http://www.sas.com/news/preleases/2011financials.html,

Revenue surged across all solution and industry categories. Software to detect fraud saw a triple-digit jump. Revenue from on-demand solutions grew almost 50 percent. Growth from analytics and information management solutions were double digit, as were gains from customer intelligence, retail, risk and supply chain solutions

AJAY- and as a private company it is quite nice that they are willing to share so much information every year.

The graphics are nice ( and the colors much better than in 2010) , but pie-charts- seriously dude there is no way to compare how much SAS revenue is shifting across geographies or even across industries. So my two cents is – lose the pie charts, and stick to line graphs please for the share of revenue by country /industry.

In 2011, SAS grew staff 9.2 percent and reinvested 24 percent of revenue into research and development

AJAY- So that means 654 million dollars spent in Research and Development.  I wonder if SAS has considered investing in much smaller startups (than it’s traditional strategy of doing all research in-house and completely acquiring a smaller company)

Even a small investment of say 5-10 million USD in open source , or even Phd level research projects could greatly increase the ROI on that.

That means

Analyzing a private company’s financials are much more fun than a public company, and I remember the words of my finance professor ( “dig , dig”) to compare 2011 results with 2010 results.

http://www.sas.com/news/preleases/2010financials.html

The percentage invested in R and D is exactly the same (24%) and the percentages of revenue earned from each geography is exactly the same . So even though revenue growth increased from 5.2 % to 9% in 2011, both the geographic spread of revenues and share  R&D costs remained EXACTLY the same.

The Americas accounted for 46 percent of total revenue; Europe, Middle East and Africa (EMEA) 42 percent; and Asia Pacific 12 percent.

Overall, I think SAS remains a 35% market share (despite all that noise from IBM, SAS clones, open source) because they are good at providing solutions customized for industries (instead of just software products), the market for analytics is not saturated (it seems to be growing faster than 12% or is it) , and its ability to attract and retain the best analytical talent (which in a non -American tradition for a software company means no stock options, job security, and great benefits- SAS remains almost Japanese in HR practices).

In 2010, SAS grew staff by 2.4 percent, in 2011 SAS grew staff by 9 percent.

But I liked the directional statement made here-and I think that design interfaces, algorithmic and computational efficiencies should increase analytical time, time to think on business and reduce data management time further!

“What would you do with the extra time if your code ran in two minutes instead of five hours?” Goodnight challenged.

PMML Augustus

Here is a new-old system in open source for

for building and scoring statistical models designed to work with data sets that are too large to fit into memory.

http://code.google.com/p/augustus/

Augustus is an open source software toolkit for building and scoring statistical models. It is written in Python and its
most distinctive features are:
• Ability to be used on sets of big data; these are data sets that exceed either memory capacity or disk capacity, so
that existing solutions like R or SAS cannot be used. Augustus is also perfectly capable of handling problems
that can fit on one computer.
• PMML compliance and the ability to both:
– produce models with PMML-compliant formats (saved with extension .pmml).
– consume models from files with the PMML format.
Augustus has been tested and deployed on serveral operating systems. It is intended for developers who work in the
financial or insurance industry, information technology, or in the science and research communities.
Usage
Augustus produces and consumes Baseline, Cluster, Tree, and Ruleset models. Currently, it uses an event-based
approach to building Tree, Cluster and Ruleset models that is non-standard.

New to PMML ?

Read on http://code.google.com/p/augustus/wiki/PMML

The Predictive Model Markup Language or PMML is a vendor driven XML markup language for specifying statistical and data mining models. In other words, it is an XML language so that Continue reading “PMML Augustus”