21 plug-ins to make the most of Eclipse

21 plug-ins to pump up Eclipse
eclipse plug ins intro

Image by Thinkstock/Eclipse

Eclipse continues to be one of the most popular developer IDEs, thanks in large part to the broad ecosystem of plug-ins the platform supports. It may have begun as a tool for Java, but more and more people use it for other languages and frameworks, from Scala and Kotlin to JavaScript and Node.js. 

To read this article in full, please click here

Source: New feed

Beta JetBrains IDE moves Kotlin apps out of the JVM

JetBrains has made available the Kotlin/Native technology, which creates native binaries for Kotlin code so they can run without a Java virtual machine. A beta version of the CLion IDE allows Kotlin programs to be compiled directly to an executable machine-code format.

Kotlin is a statically typed Java language alternative that began on the JVM. But many platforms can’t run JVMs, restricting the use of Kotlin to JVM-friendly platforms like Android. The Kotlin/Native preview’s supported target platforms include MacOS, iOS, Ubuntu Linux, and Raspberry Pi.

To read this article in full, please click here

Source: New feed

Java 101: Datastructures and algorithms in Java, Part 2

An array is a fundamental datastructure category, and a building block for more complex datastructures. In this second part of my Java 101 introduction to datastructures and algorithms, you will learn how arrays are understood and used in Java programming. I introduce the concept of an array and how arrays are represented in the Java language. Then you’ll learn about one-dimensional arrays and the three ways that you can introduce them to your Java programs. Finally, we’ll explore five algorithms used to search and sort one-dimensional arrays.

Note that this article builds on Datastructures and algorithms, Part 1, which introduces the theoretical side of datastructures and the algorithms associated with them. That article includes an in-depth discussion of algorithms and how to use space and time complexity factors to evaluate and select the most efficient algorithm for your Java program. This article will be much more hands-on, and assumes you have already read and digested Part 1.

To read this article in full, please click here

Source: New feed

ZGC large-heap Java garbage collector may go open source

An Oracle-developed, low-latency Java garbage collector geared to large heaps could move to the open source community, if a proposal to do so gets community approval. Votes are due by November 8.

Called the Z Garbage Collector (ZGC), the project is designed to support multiterabyte heaps, have pause times not exceeding 10 milliseconds, and offer no more than a 15 percent application reduction throughput compared to the G1 garbage collector.

But ZGC’s developers don’t see these goals as “hard requirements” for every workload, according to a proposal floated on an OpenJDK mailing list by Per Liden, a member of the HotSpot virtual machine team at Oracle. Liden’s proposal calls for creation of a ZGC project that he would lead, with the HotSpot group as sponsor. 

To read this article in full, please click here

Source: New feed

Machine learning for Java developers

Self-driving cars, face detection software, and voice controlled speakers all are built on machine learning technologies and frameworks–and these are just the first wave. Over the next decade, a new generation of products will transform our world, initiating new approaches to software development and the applications and products that we create and use.

As a Java developer, you want to get ahead of this curve now–when tech companies are beginning to seriously invest in machine learning. What you learn today, you can build on over the next five years, but you have to start somewhere.

This article will get you started. You will begin with a first impression of how machine learning works, followed by a short guide to implementing and training a machine learning algorithm. After studying the internals of the learning algorithm and features that you can use to train, score, and select the best-fitting prediction function, you’ll get an overview of using a JVM framework, Weka, to build machine learning solutions. This article focuses on supervised machine learning, which is the most common approach to developing intelligent applications.

To read this article in full, please click here

Source: New feed

Serverless computing with AWS Lambda

Serverless computing may be the hottest thing in cloud computing today, but what, exactly, is it? In this two-part article you’ll get started with serverless computing–from what it is, to why it’s considered disruptive to traditional cloud computing, and how you might find yourself using it in Java-based programming. Following the overview, you’ll get a tutorial introduction to AWS Lambda, which is considered by many the premiere Java-based solution for serverless computing today. In Part 1, you’ll use AWS Lambda to build your first serverless function in Java. In Part 2, you’ll integrate your Lambda functions with DynamoDB, then use the AWS SDK to invoke Lambda functions in a Java application.

To read this article in full, please click here

Source: New feed

21 rules for faster SQL queries

Everyone wants faster database queries, and both SQL developers and DBAs can turn to many time-tested methods to achieve that goal. Unfortunately, no single method is foolproof or ironclad. But even if there is no right answer to tuning every query, there are plenty of proven do’s and don’ts to help light the way. While some are RDBMS-specific, most of these tips apply to any relational database.

Whether you’re coding on SQL Server, Oracle, DB2, Sybase, MySQL, or some other relational platform, your goal is the same: You want the database to support as many concurrent users as practical while processing queries as quickly as it can. That means you need to minimize locking, I/O, and network traffic, while optimizing space and resource management. 

To read this article in full, please click here

(Insider Story)
Source: New feed