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Arun Manivannan10/05/12
0 replies

Architexa - a Fine Code Reading Tool

I love reading code for two reasons : If the code is bad, it is an awesome ego boost PLUS you get to foul mouth someone who has a good reputation for designing amazing things.

Hubert Klein Ikkink10/05/12
0 replies

Groovy Goodness: Boolean Implications

Since Groovy 1.8.3 we can use the implies() method on Boolean types. The implies() method implements a logical implication. This means that if we have two Boolean variables A and B, that if A is true, then B is true

Ayende Rahien10/05/12
0 replies

Lucene is Beautiful

So after I finished telling you how much I don’t like the Lucene.net codebase, what's this post about? The ideas behind Lucene are actually amazingly powerful in their simplicity.

Yaron Naveh10/05/12
0 replies

MongoDB and Redis Go Head-to-Head with Node.js Social Analytics

Here are some of the amazing geo-social visualizations you get when you compare two projects:

Brian Gracely10/05/12
0 replies

Who's Your Puppet Master: The Cloudcast - Eps.59

Aaron and Nick Weaver talk with Luke Kanies (@puppetmasterd), Founder / CEO @ Puppet Labs, about the evolution of DevOps, the growth of the Puppet community and shifts in how IT operations are being managed.

Claus Ibsen10/05/12
0 replies

Apache Camel and Akka

See how well Camel and Akka work together, showcasing demos with code that's less than a page, but still does powerful stuff, integrating mail, jms, file, akka, twitter, aws and whatnot.

Nick Jordan10/05/12
0 replies

Our Search for the Perfect Project Management Tool

We’ve tried Co-Human (now MindJet), Redmine, Trello, OmniPlan, Pivotal Tracker, heck even Microsoft has given a shot at the PM tool marketplace. Each PM tool has a set of features that set it apart from the other; time tracking, estimates, client delivery, to do lists, budgets, assignments, etc.

John Cook10/04/12
0 replies

Your Software Flow is More Like a Whirlpool than a Pipeline

Most software looks more like a whirlpool than a pipeline. Data swirls around in loops before going down the drain.

Duncan Brown10/04/12
2 replies

Spring Data Neo4j, @MapResult, Cypher, Casing and You!

If you're using the @MapResult way in your Neo4j repositories, be careful of what you use in the corresponding @ResultColumn annotations.

Nikita Salnikov...10/04/12
0 replies

Measuring Memory Overhead in Java

I have spent a lot of time recently measuring Plumbr’s overhead and figuring out some ways of reducing it.

Esen Sagynov10/04/12
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Commercial and Open Source Big Data Platforms Comparison

Lee Kyu Jae takes an in-depth look at how to effectively analyze data from a platform perspective, and how that data can help us face future problems.

Roger Hughes10/04/12
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Spring 3.1: Caching and EhCache

If you look around the web for examples of using Spring 3.1’s built in caching then you’ll usually bump into Spring’s SimpleCacheManager, which the Guys at Spring say is “Useful for testing or simple caching declarations”.

Eric Berg10/04/12
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Defining the Enterprise Cloud Service: Endless 9s Reliability

Availability of a cloud service is important. People I know get quite agitated when Facebook or Twitter is unavailable, but imagine the repercussions when a big enterprise such as Genomic Health can’t access a critical application, such as CRM.

Mark Needham10/04/12
11 replies

Java: Parsing CSV files

As I mentioned in a previous post I recently moved a bunch of neo4j data loading code from Ruby to Java and as part of that process I needed to parse some CSV files.

Mark Needham10/04/12
0 replies

Data Science: Making Sense of the Data

The data we’re working with was initially stored in a SQL Server database, so the quickest way to get moving was to export it as CSV files and then work with those.