There are several ways to improve your product. One such way is to carefully track what your users are experiencing and improve based on that.
I'm not even certain that I could help them with some of the Python technology required to extend scipy. But, I'm sure I cannot actually do anything of value under the circumstances that (a) they have not really tried the established algorithms and (b) they're already sure that the established algorithms can't work based on religious-wars arguments.
TL;DR: The realities of modern corporate networks make the move to distributed database architectures inevitable. How do you leverage the stability and security of traditional relational database designs while making the transition to distributed environments? One key consideration is to ensure your cloud databases are scalable enough to deliver the technology's cost and performance benefits.
I had an interesting conversation today about the cost of using string concatenation in log statements.
Java Performance: The Definitive Guide is the best Java book I read this year.
NetBeans 8.0 introduces several new Java hints.
When thinking about performance, AppDynamics and New Relic are the main modern tools that come to mind. Both spawned from the same company, Wily Technology, who also dealt with performance monitoring and was acquired by CA back in 2006 - making way to new technology.
I was recently asked to compare the performance of Kafka with Chronicle Queue. No two products are exactly alike, and performing a fair comparison is not easy. We can try to run similar tests and see what results we get.
Flash storage is slowly becoming more affordable and infiltrating the mainstream enterprise.
Cyclomatic complexity is a software metric used to measure the complexity of a program. This metric measures independent paths through the program's source code.
In a post published in July, I mentioned the so-called Goldilocks principle, in the context of kernel density estimation, and bandwidth selection. The bandwidth should not be too small (the variance would be too large) and it should not be too large (the bias would be too large).
Handling state is a common programming problem. This article shows how the state monad implemented in Java 8 may help solving this kind of problem. It first describes how it may be applied to memoizing a recursive function. Then, it shows how the state monad may simplify the implementation of a state machine.
Every week here and in our newsletter, we feature a new developer/blogger from the DZone community to catch up and find out what he or she is working on now and what's coming next. This week we're talking to Vladimir Šor, co-founder and CTO of Plumbr.
This post is asking you to help us in building a better product. What we are after is your current experience in Java performance tuning
There is a migration process that deals with event sourcing system. So we have 10,000,000 commits with 5 – 50 events per commit. Each event result in a property update to an entity.
In this article we will explore some of the well-established options available for thread pooling/sharing in the JVM. Also, with the availability of multicore processors new issues have crept up.
There are some instances when you want to store your passwords in files to be used by programs or scripts. But storing your passwords in plain text is not a good idea. Use the SecurePasswordVault to encrypt your passwords before storing and get it decrypted when you want to use it.
Even though there is plenty of HTTP clients in Java world, I created a new one, which is fluent, immutable, extendable and simple
One of the basic needs in fluent interface is connecting to user types. What field, method or operation does this fluent interface try to refer? JaQue project provides an elegant solution.
I’ve listed out those origins of conditionals that I could think of. Is this a fool’s errand? Possibly, but let’s give it a try anyway.
The latest Packt Publishing Java EE 7 books are all around performance and tuning.
Memoization is a technique used to speed up functions. Memoization may be done manually. It may also be done automatically. We can find many examples of automatic memoization on Internet. In this article, I will show how Java 8 makes it very easy to memoize functions.
Load-testing is not trivial. It’s often not just about downloading JMeter or Gatling, recording some scenarios and then running them. It’s good to be reminded of some things that can potentially waste time.
By ensuring that all objects participating in a transaction are mapped to the same logical partition, we can remove the whole "prepare" phase from the distributed commit protocol, thus converting the standard 2-Phase-Commit into very light weight 1-Phase-Commit transactions.
There have been a couple of articles on null, NPE's and how to avoid them. They make some point, but could stress the easy, safe, beautiful aspects of Java 8's Optional. This article shows some way of dealing with optional values, without additional utility code.