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In this article i’ll show how easy it is to setup Spring Java app with Kafka message brocker. We will use docker containers for kafka zookeeper/brocker apps and configure plaintext authorization for access from both local and external net.

Link to final project on github can be picked up at the end of the article.

In this digital world, people prefer to work remotely. There are numerous tasks that each of us goes through every day. If I talk about an application's usage, then it has been predicted that there will be a 25% increase in global app downloads between 2018 and 2022. 

But it can be quite challenging for organizations to maintain and create multiple passwords. Hence, a password management software can be a great choice to manage this effectively. It is like your bank locker, where one can store numerous passwords. The users only need a master password to access the software.

Do You Know? 

The Big Data Tools plugin seamlessly integrates HDFS into your IDE and provides access to different cloud storage systems (AWS S3, Minio, Linode, Digital Open Space, GS, Azure). But is this the end? Have we implemented everything and now progress has stopped? Of course not.

In this short digest, we'll take a look at 15 popular distributed file systems available on the market and try to get a sense of their individual advantages.

Almost all of these systems are free or open-source, and you can find the sources on GitHub. The sites of these projects, their documentation, and online reviews provide most of the information we’ll consider here. Other than HDFS, none of these technologies have been implemented yet in Big Data Tools. But who knows? Perhaps someday we'll see them in our plugin.

EAP 11 of the Big Data Tools plugin for IntelliJ IDEA Ultimate, PyCharm, and DataGrip is available starting today. You can install it from the JetBrains Plugin Repository or inside your IDE.

Big Data Tools is a new JetBrains plugin that allows you to connect to Hadoop and Spark clusters and monitor nodes, applications, and jobs. It also brings support for editing and running Zeppelin notebooks inside IntelliJ IDEA and DataGrip, so you can create, edit, and run Zeppelin notebooks without ever having to leave your favorite IDE. The plugin offers smart navigation, code completion, inspections, quick-fixes, and refactoring inside notebooks.

Zeppelin is a web-based notebook for data engineers that enables data-driven, interactive data analytics with Spark, Scala, and more.

The project recently reached version 0.9.0-preview2 and is being actively developed, but there are still many things to be implemented.

One such thing is an API for getting comprehensive information about what's going on inside the notebook. There is already an API that completely solves the problems of high-level notebook management, but it doesn’t help if you want to do anything more complex.

JavaCC 21 is a continuation of work on the venerable JavaCC parser generator, originally developed at Sun Microsystems in the 1990’s and released under a liberal open source license in 2003. It is currently the most advanced version of JavaCC. It has many feature enhancements (with more to come soon) and also generates much more modern, readable Java code. Also, certain key bugs have finally been fixed. (N.B. The “21” in JavaCC 21 is not a version number. It is simply part of the project name and means that this is a JavaCC for the 21st century!)

I offer a solution to one beautiful task — writing code that outputs its text is valid for interpreters and compilers of different languages and is correctly executed when reversing its sources.

Not so long ago I learned about code that can be both interpreted in PHP and compiled to Java: PhpJava.java. As it turned out, this idea is not new: code which is valid for several compilers or interpreters is called a polyglot. It is possible to write such code because of the peculiarities of processing strings and comments in different interpreters or compilers.

Several years ago we had to solve how to enqueue events with an arbitrary delay, e.g. check a status of a payment 3 hours later, or send notification to a client in 45 minutes. At that point of time, we didn't find suitable libraries to accomplish this task, which didn't require us to spend time on configuration and maintenance. After analysing possible solutions we ended up building our own small library delayed queue in Java language on top of Redis storage engine. In this article I'll explain capabilities of this library, alternatives and problems we solved during creation process.

Introduction

In my opinion transaction management is a really important topic for each backend developer. In general, people don’t pay attention to it while using Spring framework.

But I think, it is important to know how to use transactions properly. Because sometimes can happen that there was an exception thrown inside your method, but transaction was not rolled back and it is not clear why? Or some other “strange” cases.

1. Introduction

How can I easily test my MongoDB multi-document transaction code without setting up MongoDB on my device? One might argue that they have to set it up first because in order to carry out such a transaction it needs a session which requires a replica set. Thankfully, there is no need to create a 3-node replica set and we can run these transactions only against a single database instance.

Modern IDEs are very powerful tools that can help developers in all kinds of situations. Unfortunately, much of this power is often lost because many functions remain unknown to developers, hiding in the shadows.

Structural search and replace is one such pair of features. They can be extremely useful in situations where a whole variety of other functions can’t quite get the job done.

In this post, I will present some of these situations and go beyond artificial cases by demonstrating examples of real code from two projects:

1. 3D-engine for game development, jMonkeyEngine, which is an example of a big, interesting project.
2. My own pet project, plantuml-native-image, where I experiment with compiling PlantUML into native executable code using GraalVM Native Image.

In fact, it is this second project that encouraged me to write this post but I’m getting ahead of myself. First things first...

Polluting code with 'test-only' methods or access modifiers