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James Gosling is probably best known for creating the Java programming language while working at Sun Microsystems. Currently, he is the chief software architect at Liquid Robotics. Among other projects, Liquid Robotics makes the Wave Glider, an autonomous, environmentally powered marine robot. James has agreed to take a little time from the oceangoing robots and answer any questions you have. As usual, ask as many as you'd like, but please, one question per post.

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Abstract
This paper presents Polybase, a feature of SQL Server PDW V2 that allows users to manage and query data stored in a Hadoop
cluster using the standard SQL query language. Unlike other database systems that provide only a relational view over HDFSresident data through the use of an external table mechanism, Polybase employs a split query processing paradigm in which
SQL operators on HDFS-resident data are translated into MapReduce jobs by the PDW query optimizer and then executed on the Hadoop cluster. The paper describes the design and implementation of Polybase along with a thorough performance evaluation that explores the benefits of employing a split query processing paradigm for executing queries that involve both structured data in a relational DBMS and unstructured data in Hadoop. Our results demonstrate that while the use of a splitbased query execution paradigm can improve the performance of some queries by as much as 10X, one must employ a cost-based query optimizer that considers a broad set of factors when deciding whether or not it is advantageous to push a SQL operator to Hadoop. These factors include the selectivity factor of the predicate, the relative sizes of the two clusters, and whether or not their nodes are co-located. In addition, differences in the semantics of the Java and SQL languages must be carefully considered in order to avoid altering the expected results of a query.

Link to the paper

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This is a guest post written by Claude Johnson, a Lead Site Reliability Engineer at salesforce.com.

The following is an architectural overview of salesforce.com’s core platform and applications. Other systems such as Heroku's Dyno architecture or the subsystems of other products such as work.com and do.com are specifically not covered by this material, although database.com is. The idea is to share with the technology community some insight about how salesforce.com does what it does. Any mistakes or omissions are mine.

This is by no means comprehensive but if there is interest, the author would be happy to tackle other areas of how salesforce.com works. Salesforce.com is interested in being more open with the technology communities that we have not previously interacted with. Here’s to the start of “Opening the Kimono” about how we work.

Since 1999, salesforce.com has been singularly focused on building technologies for business that are delivered over the Internet, displacing traditional enterprise software. Our customers pay via monthly subscription to access our services anywhere, anytime through a web browser. We hope this exploration of the core salesforce.com architecture will be the first of many contributions to the community.

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Starting with templates, Android features can be added quickly with a single line of DSL code.

In the first installment of this two-part series on developing Android Apps with Scala and Scaloid, I explained how Scaloid simplifies and reduces the required Android code as much as possible while leveraging type safety. In this article, I explain how to utilize asynchronous task processing, the execution of methods from system services, and specific Scaloid classes and traits.

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Original author: 
Stack Exchange

Stack Exchange

This Q&A is part of a weekly series of posts highlighting common questions encountered by technophiles and answered by users at Stack Exchange, a free, community-powered network of 100+ Q&A sites.

Java developer Stijn Geukens is working with 10 developers, and nearly every dev has his own style. That's about to change, as the company may soon impose a standard code format upon all developers. They'll be using Eclipse to help facilitate the change. But is forcing consistency upon the team more trouble than it's worth? See the original question here.

How professional

ZeroOne answers (39 votes):

Read 13 remaining paragraphs | Comments

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Original author: 
Jon Brodkin

Niall Kennedy

Todd Kuehnl has been a developer for nearly 20 years and says he's tried "pretty much every language under the sun."

But it was only recently that Kuehnl discovered Go, a programming language unveiled by Google almost four years ago. Go is still a new kid on the block, but for Kuehnl, the conversion was quick. Now he says "Go is definitely by far my favorite programming language to work in." Kuehnl admitted he is "kind of a fanboy."

I'm no expert in programming, but I talked to Kuehnl because I was curious what might draw experienced coders to switch from proven languages to a brand new one (albeit one co-invented by the famous Ken Thompson, creator of Unix and the B programming language). Google itself runs some of its back-end systems on Go, no surprise for a company that designs its own servers and much of the software (right down to the operating systems) that its employees use. But why would non-Google engineers go with Go?

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Original author: 
Peter Bright

Aurich Lawson / Thinkstock

In a bid to make JavaScript run ever faster, Mozilla has developed asm.js. It's a limited, stripped down subset of JavaScript that the company claims will offer performance that's within a factor of two of native—good enough to use the browser for almost any application. Can JavaScript really start to rival native code performance? We've been taking a closer look.

The quest for faster JavaScript

JavaScript performance became a big deal in 2008. Prior to this, the JavaScript engines found in common Web browsers tended to be pretty slow. These were good enough for the basic scripting that the Web used at the time, but it was largely inadequate for those wanting to use the Web as a rich application platform.

In 2008, however, Google released Chrome with its V8 JavaScript engine. Around the same time, Apple brought out Safari 4 with its Nitro (née Squirrelfish Extreme) engine. These engines brought something new to the world of JavaScript: high performance achieved through just-in-time (JIT) compilation. V8 and Nitro would convert JavaScript into pieces of executable code that the CPU could run directly, improving performance by a factor of three or more.

Read 94 remaining paragraphs | Comments

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Original author: 
Todd Hoff

What data structure is more sacred than the link list? If we get rid of it what silly interview questions would we use instead? But not using linked-lists is exactly what Aater Suleman recommends in Should you ever use Linked-Lists?

In The Secret To 10 Million Concurrent Connections one of the important strategies is not scribbling data all over memory via pointers because following pointers increases cache misses which reduces performance. And there’s nothing more iconic of pointers than the link list.

Here are Aeter's reasons to be anti-linked-list:

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