Use Cast Object to get the specialisation

The Mendix platform queries the entire hierarchy when retrieving the specialisation from the database, in order to guarantee a consistent data structure. When retrieving the generalisation it will also retrieve the entire hierarchy. Thus, developers should never retrieve a specialisation from database if the generalisation is already available. Use Cast Object with an inheritance split to get the specialised members of the object. This is much faster.

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Scheduled events might not work the way you would expect

Scheduled Events (SE) allow you to execute microflows at a specific time. These events can be repeated based on an interval (e.g. every day). The Mendix platform calculates when the next iteration of an event should occur based on fixed intervals. These intervals are configured by the developer but the execution of these intervals might not meet expectations. For example, an event scheduled at monthly interval will run every 31 days instead of every month.

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Fast manipulation of large tables

Mendix applications can accumulate large sets of data originating from various sources and created for various reasons. In order to work efficiently with large datasets extra attention to performance is needed. This post will provide recommendations for speed and performance when modelling manipulations of large datasets.

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Using Google Tag Manager with Mendix

Analytics are essential in monitoring and reacting to traffic and usage of your application. The widget for Google Analytics in the Mendix appstore lets you track events, pages and transactions, but can be time-consuming to configure. With Google Tag Manager you can launch new tags with a few clicks. Instead of adding new events in Mendix, the Google Tag Manager allows marketers to add new tags without the need for changes to the model and deployments of Mendix. This post is a description of my first-time setup of Google Tag Manager and Mendix, and it worked!

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The developers guide to performance

End-users expect fast and engaging web experiences. Yet the application landscape is becoming more complex. Your Mendix application can meet these rising expectations and impress users on both desktop and mobile devices. Learn how to locate and analyse performance issues, improve application performance and gain insight in how design decisions impact your application. This post is a comprehensive reference guide for developers to optimize their applications.

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Semantics of XPath expressions part 2 – analysing the SQL

In the previous post (semantics of XPath expressions), the semantics of different XPath notations were discussed. Part 2 will be an in-depth analyses of the SQL queries generated by Mendix for each of the XPath expressions. Furthermore it will shed some light on why these XPath expressions return a different data set.

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Semantics of XPath expressions

XPath expressions can be added to any XPath query in Mendix to constrain the queried Mendix object. The XPath expression can be a combination of variables, operations, functions, keywords and system variables. This post will focus on the semantics of certain XPath expressions with the AND-operator. A seemingly small change in the notation of an XPath expression using this comparison operator can have a huge impact on the retrieved data.

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