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OIO ‘s Developer Blog
This is the publication playground for these guys from OIO, the Trivadis Group`s Java experts.
Tag cloud
Agile Methods and development Atlassian Tools Build, config and deploy Did you know? Eclipse Universe Groovy and Grails Java and Quality Java Basics Java EE Java modularization Java Persistence Java Runtimes - VM, Appserver & Cloud Java Web Frameworks MDSD Open Source BI Other languages for the Java VM Politics Security SOA / Webservices Spring Universe Web as a Platform XML Universe
Category Archives: Java Runtimes – VM, Appserver & Cloud
Was ist der Unterschied zwischen RDD, DataFrame und Dataset in Apache Spark?
Apache Spark wurde entwickelt, um eine höhere Leistung im Hadoop-Ökosystem erreichen zu können. Im Vergleich zu Hadoop soll Spark dank In-Memory-Berechnungen und weiterer Optimierungen bei der Datenverarbeitung wesentlich schneller sein. In diesem Blog will ich erklären, welche Datenstrukturen Spark mitbringt und … Continue reading
Posted in Java Runtimes - VM, Appserver & Cloud
Tagged Apache Spark, DataFrame, DataSet, RDD
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Möglichkeiten, eine Spring-Anwendung auf der Azure Cloud zu betreiben
Auf Azure gibt es unzählige Möglichkeiten, eine Java Anwendung zu betreiben. In diesem Artikel möchte ich anhand eines Beispiels vier verschiedene Methoden zeigen, wie man eine Spring Boot Applikation auf Microsoft Azure deployen kann.
How to run a containerized Java application in the cloud on Microsoft Azure
This post is not meant for any Docker/Microsoft Azure expert. But for people like me, who already wrote some Java code and may have peeked a little bit into the Docker topic. Who have never touched “the cloud”, but are … Continue reading
High performance at low cost – choose the best JVM and the best Garbage Collector for your needs
The Garbage Collector (GC) is an integral part of every Java Virtual Machine (JVM) – running in the Cloud, on a dedicated server or on your desktop/laptop. Are you aware of what impact a GC has on an application – … Continue reading
Posted in Java Runtimes - VM, Appserver & Cloud
Tagged garbage collector, GraalVM, HotSpot VM, jvm, OpenJ9, Substrate VM, Zing
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Map Reduce in Hadoop Example
Hadoop MapReduce is a software framework used for distributed processing of large data sets on compute clusters. According to The Apache Software Foundation, the objective of Map/Reduce is to split the input data set into independent chunks that are processed … Continue reading
What is Docker Compose? How to use it?
When you use Docker and you have to handle many different containers, their management is complicated. You need to manage the configuration and the functioning of each container separately. When you need to use your containers in a specific environment, … Continue reading
Docker Best Practices: Keine “FAT JARs” mehr!
Dieser Beitrag unserer Blog-Serie beleuchtet, warum die so häufig genutzten “Fat” oder “Uber” Jars und auch WAR-Dateien schlecht für die Bereitstellung mit Docker sind und welche sinnvollen Alternativen existieren.
