Just found my address in Moscow in high resolution on google maps - far out! It was by Moscow State University.

http://maps.google.com/maps?q=moscow+state+university&oe=utf-8&client=firefox-a&ie=UTF8&split=0&gl=us&ei=6LH3SebmENSEtwfZkOCoDw&t=h&ll=55.691671,37.492465&spn=0.004233,0.013947&z=17&iwloc=A

Moscow - Ramenki - Google Maps

Why would Oracle, which makes most of its money from databases and business software, buy a hardware firm? A big part of the reason is the outsized appetite of Larry Ellison, Oracle’s flamboyant chief executive. His firm has spent around $30 billion buying 50 firms since 2005, among them software heavyweights such as PeopleSoft, Siebel and BEA. Buying Sun should help Mr Ellison achieve his goal of getting Oracle’s revenues above $30 billion by the end of this year.

Oracle's surprising takeover of Sun | Mr Ellison helps himself | The Economist

We also announced a partnership with Amazon, through which we've made OpenSolaris, alongside MySQL and Glassfish, available with commercial support on Amazon's elastic computing cloud. From where I sit, this is a profound change in the industry - the world's most popular database is now available, and commercially supported, as a cloud service. As is the fastest growing Java container, and a redefined OpenSolaris for the modern world.

Jonathan Schwartz's Blog: OpenSolaris, Amazon, MySQL and Glassfish... Clouds Parting

Cloudera's Basic Hadoop Training

Cloudera's Basic Hadoop Training is available online, free of charge. If you have questions about the content, please feel free to direct them to community support.

Really good videos make a great introduction to Hadoop.

Cloudera's Basic Hadoop Training | Cloudera

This is a guest post by Russell Jurney, a technologist and serial entrepreneur. His new startup, Cloud Stenography, will launch later this year. The article is an extension of a simple question on Twitter asking the importance of Map Reduce. Some subjects take much more than 140 characters.

The Technical Situation in Brief

The advent of the personal computer and the Visicalc spreadsheet were the foundation for a revolution in computing, business and life whereby normal people could carry out sophisticated accounting, analysis and forecasting to inform their decisions to arrive at more positive outcomes. As Moore’s law has progressed and processors have become faster, and computers inter-networked, large volumes of highly granular data have been collected. Analysis of terabyte datasets on the same level as a spreadsheet has been limited by the disparity of acceleration between processor speed and computer I/O (input/output) operations. Intel has produced ever faster processor clock speeds without accompanying disk, RAM or bus speeds. Put simply: We have cheap and numerous computing resources and abundant data, but bringing those resources to bear on that data to generate real value from it has proven exceedingly difficult.

I did they guest post on Lance Weatherby's blog to explain mapreduce to the people.

The hacker news thread is: http://news.ycombinator.com/item?id=554327

Map Reduce for the People: Force of Good: a blog by Lance Weatherby

Michael Osinski:

Here's one thing that's definitely true: The software proved to be more sophisticated than the people who used it, and that has caused the whole world a lot of problems.

I was wondering why I was making more than anyone in my family, maybe as much as all my siblings combined. Hey, I had higher SAT scores. I could do all the arithmetic in my head. I was very good at programming a computer. And that computer, with my software, touched billions of dollars of the firm's money. Every week. That justified it. When you're close to the money, you get the first cut. Oyster farmers eat lots of oysters, don't they?

From January:

When I started in the business in risk management a veteran trader drew me a picture of the money river to tell me how everyone got paid.

He drew the river and then in a prime spot, a dam. That's where management was. Then you had sales and trading rank and file down the river a bit, but on the bank dipping their pans in the river. Middle office was behind the river bank dipping in the occasional spill over.

My Manhattan Project

Hadoop feat. Lzo - save disk space and speed up your programs
The whole point of Hadoop is to process very large datasets. This implies that you will be using a lot of disk space, all those big files replicated a couple of times add up. Let's look at how we can compress text files, saving disk space without losing performance.

braindump: Hadoop feat. Lzo - save disk space and speed up your programs

Xobni's Outlook add-in saves you time finding email, conversations, contact info & attachments.null

Xobni's Outlook Add in - Learn more

Enron Email Dataset
This dataset was collected and prepared by the CALO Project (A Cognitive Assistant that Learns and Organizes). It contains data from about 150 users, mostly senior management of Enron, organized into folders. The corpus contains a total of about 0.5M messages. This data was originally made public, and posted to the web, by the Federal Energy Regulatory Commission during its investigation.

The email dataset was later purchased by Leslie Kaelbling at MIT, and turned out to have a number of integrity problems. A number of folks at SRI, notably Melinda Gervasio, worked hard to correct these problems, and it is thanks to them (not me) that the dataset is available. The dataset here does not include attachments, and some messages have been deleted "as part of a redaction effort due to requests from affected employees". Invalid email addresses were converted to something of the form user@enron.com whenever possible (i.e., recipient is specified in some parse-able format like "Doe, John" or "Mary K. Smith") and to no_address@enron.com when no recipient was specified.

I get a number of questions about this corpus each week, which I am unable to answer, mostly because they deal with preparation issues and such that I just don't know about. If you ask me a question and I don't answer, please don't feel slighted.

I am distributing this dataset as a resource for researchers who are interested in improving current email tools, or understanding how email is currently used. This data is valuable; to my knowledge it is the only substantial collection of "real" email that is public. The reason other datasets are not public is because of privacy concerns. In using this dataset, please be sensitive to the privacy of the people involved (and remember that many of these people were certainly not involved in any of the actions which precipitated the investigation.)

Enron Email Dataset

Introduction

PostgreSQL is the most advanced and flexible Open Source SQL database today. With this power and flexibility comes a problem. How do the PostgreSQL developers tune the default configuration for everyone? Unfortunately the answer is they can't.

Really good, comprehensive introduction to tuning Postgres.

Performance Tuning PostgreSQL