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Case Study: Startershypotheek bij de Rabobank

Disclaimer: this post is in Dutch. If you would like to obtain a translation of this article, feel free to ask me.

Home for sale.
Home for sale.

Het zijn gunstige tijden voor huizenkopers, de huizenprijzen zijn laag. Het grote probleem voor starters is dat banken niet veel risico durven te nemen en daardoor relatief lage hypotheken verstrekken. In dit artikel probeer ik het huidige hypotheeksysteem (augustus 2016) van de Rabobank te doorgronden. Is het systeem wel eerlijk? (more…)

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CERN (deel 4) – De laatste weken

Disclaimer: This post is in Dutch. If you would like to read it in English, please ask me.

A touristic view of Geneva.
Een toeristische foto van het mooie Genève.

Dat was het dan bijna, morgen (19-8-2016) zit mijn CERN avontuur er op en dit is dan ook de laatste Nederlandstalige post over mijn zomerstage bij CERN. De laatste weken is er ontzettend veel gebeurd: ik heb bezoek uit Nederland gehad, het project is in een stroomversnelling terecht gekomen en afgerond en ik heb afscheid genomen van mijn collega’s op CERN.

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Apache Flink: The Next Distributed Data Processing Revolution?

Disclaimer: The results are valid only in the case when network attached storage is used in the computing cluster.

The logo of Apache Flink.
The logo of Apache Flink.

The amount of data is growing significantly over the past few years. It is not feasible for only one machine to process large amounts of data. Therefore, the need of distributed data processing frameworks is growing. It all started back in 2011 when the first version of Apache Hadoop was released (version 1.0.0). The Hadoop framework is capable of storing a large amount of data on a cluster. This is known as the Hadoop FileSystem (HDFS) and it is used at almost every company which has the burden to store Terabytes of data every day. Then the next problem arose: how can companies process all the stored data? Here is where Distributed Data Processing frameworks come into play. In 2014, Apache Spark was released and it now has a large community. Almost every IT section has implemented at least some lines of Apache Spark code. Companies gathered more and more data and the demand for faster data processing frameworks is growing. Apache Flink (released in March 2016) is a new face in the field of distributed data processing and is one answer to the demand for faster data processing frameworks.

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