This blog article is part of a “series of blog articles” about common pitfalls using JPA and ways to avoid them. In this article, we describe the difference between a set or list relationship.
Continue readingPlayground
JPA Pitfalls (1): Serialized Collection
This blog article is part of a “series of blog articles” about common pitfalls using JPA and ways to avoid them. In this article, we describe, how easily a relation mapped as collection ends up as a blob.
Continue readingJPA Pitfalls – a Series of Serious JPA Obstacles
Most of our Java-based web-applications store their data in a relational database such as Oracle, PostgreSQL, MySQL, MariaDB or MS SQLServer. The standard way to access and modify the data is using an object-relational mapping as specified by the Java Persistence API (JPA). Over the years JPA has become a mature specification and there are a couple of JPA implementations with strong support such as Hibernate, EclipseLink, OpenJPA and DataNucleus. However, day-to-day project experience demonstrates there are number of pitfalls you might run into when using JPA.
To avoid stumbling into the same pitfall again and again, we collected them with their solutions and presented these pairs of problems and solutions. This is a start of a series of blog articles each describing a pitfall and a way to circumvent it.
Unbounded Functional Loops in Kotlin
This article is a follow-up to this previous article about bounded loops. Bounded loops are cool because they always terminate and usually it is pretty easy to estimate the computational time. But as every computer scientist, who had to understand the halting problem, knows, there is a big class of algorithms which are harder. These are known as the class of μ-recursive functions. Here, unbounded loops exists which can run forever. I will introduce how IMHO unbounded loops can be implemented in Kotlin in a functional way. And, of course, I could not resist and did some measurements…
Continue readingBounded Functional Loops in Kotlin
Loops are a basic paradigm in imperative programming languages. In functional languages you also need to loop, but you do it differently. Here, I present how I prefer to implement loops in a functional style using Kotlin. To check, if this is a good idea at all, I do some benchmarks against imperative variants and good old Haskell.
Continue readingGUI Transactions with the FRP Framework Sodium
Sodium is an implementation of Functional Reactive programming (FRP) with some nice features. One of these is the support of transactions in the GUI layer. I had quite some discussions with my colleagues on what this actually means and if such a transaction concept is useful or not. In this article I sum up my current insights and opinions about transactions in Sodium.
Continue reading
Jacoco and Sonar with Kotlin
When we began a new project recently the team thought about using Kotlin over Java to implement the backend. The project lead had issues with this because there was no clear information on how Kotlin would be supported by tools like Sonar and Jacoco. Since these tools deliver important information about code quality and potential issues we decided to spend some time on evaluating how these tools would collaborate with Kotlin.
Functional Reactive Programming with Angular and Sodium
Functional reactive programming (FRP) is a variant of reactive programming for the development of user interfaces based on the functional paradigm and a strict set of basic operators. In contrast to reactive frameworks, such as RxJs, using FRP enables a developer to define a pure area in her code in which some error classes, typical for event-based architectures, do not occur. Sodium is an FRP-framework, which is independent of a specific GUI-framwork and supports several different programming languages. Here, we describe how to use Sodium together with Angular.
Continue reading
How to deploy a dockerized app to Microsoft Azure Web App for Containers
Deploying a Docker container on Azure ‘Web App for Containers’ can be done fairly easy. In this blog post, I will provide a step by step guide to get you started. Some basic knowledge of Azure and Docker definitely helps. But why should you care in the first place? You will get:
- a managed runtime (for a single image)
- scaling to multiple instances
- HTTPS
- a simple deployment model
- easy integration with App Insights (Azure’s Monitoring system for Web Apps)
- use any Azure SaaS like CosmosDB, MSSQL, …
