#Object Data Model

Hi folks,

I've created a datatype class whoch extends from %Library.String with a REGEX parameter and the validation of the value against the regular expression. The class does not support Populate using the regular expression as a template for data population.

In my previous article, we reviewed possible use-cases for macros, so let’s now proceed to a more comprehensive example of macros usability. In this article we will design and build a logging system.

Logging system

Logging system is a useful tool for monitoring the work of an application that saves a lot of time during debugging and monitoring. Our system would consist of two parts:

• Storage class (for log records)
• Set of macros that automatically add a new record to the log

Before we start talking about databases and different data models that exist, first we'd better talk about what a database is and how to use it.

A database is an organized collection of data stored and accessed electronically. It is used to store and retrieve structured, semi-structured, or raw data which is often related to a theme or activity.

At the heart of every database lies at least one model used to describe its data. And depending on the model it is based on, a database may have slightly different characteristics and store different types of data.

To write, retrieve, modify, sort, transform or print the information from the database, a software called Database Management System (DBMS) is used.

The size, capacity, and performance of databases and their respective DBMS have increased by several orders of magnitude. It has been made possible by technological advances in various areas, such as processors, computer memory, computer storage, and computer networks. In general, the development of database technology can be divided into four generations based on the data models or structure: navigational, relational, object and post-relational.

XDATA is used for a whole host of ISC libraries to store things like Zen pages, BPL logic and DTL transformations.

XDATA is the equivalent of XML config files of the JAVA world and JSON config files of the JavaScript / NPM world.

Whilst Atelier looks to shift source code to the disk, XDATA will remain a key component to source control our projects config / meta data.

What if you could serialize/deserialize objects in whatever format: JSON, XML, CSV,...; attending different criteria: export/import some properties and not others, transform values in this or that way before exporting/importing,...; and all of this without having to change the class definition? Wouldn't that be great??

Well, perhaps it's a goal too ambitious to reach 100% but, exploring this idea, I've developed a bunch of classes that I thought it was good to share. If you want to test, change, modify or improve the code, or just take a look at it, you can do it here. There you'll find a more detailed explanation (see Readme.md)

This is the first article of a series diving into visualization tools and analysis of time series data. Obviously we are most interested in looking at performance related data we can gather from the Caché family of products. However, as we'll see down the road, we are absolutely not limited to that. For now we are exploring python and the libraries/tools available within that ecosystem.

Here's a code snippet to calculate the length of a class or a package in lines of code:

In part I of this series we have introduced MapReduce as a generic concept, and in part II we started to approach Caché ObjectScript implementation via introducing abstract interfaces. Now we will try to provide more concrete examples of applications using MapReduce.

Among the outputs of our Yuzinji tool are two code metrics that it can be interesting to track over time as a development project proceeds. These are Size and XS. The first is fairly straightforward. As you write more code the size of your codebase increases. The XS metric (pronounced "excess") aims to quantify excessive structural complexity.

Here you have an easy way to write and execute COS code from your unix scripts. This way one does not need to write routines or even open Studio or Atelier. It can be an option for simple and small actions for instance things like installation tasks or compiling.

See sample bash script (compile.sh) to compile classes:

As a developer, you have probably spent at least some time writing repetetive code. You may have even found yourself wishing you could generate the code programmatically. If this sounds familiar, this article is for you!

We'll start with an example. Note: the following examples use the %DynamicObject interface, which requires Caché 2016.2 or later. If you are unfamiliar with this class, check out the documentation here: Using JSON in Caché. It's really cool!

What do you do if you want to have the ID field have a meaningful name for your application?

Sometimes it comes to pass that when you're making a new table that you want to have the unique row identifier (a.k.a. IDKEY) to be a field that has a name that is meaningful for your data. Moreover, sometimes you want to set this value directly. Caché fully supports this functionality and it works Suppose you have a class Test.Kyle. The data will be stored like so:

^Test.Kyle(IDKEY)=$LB("",Field1,Field2,...,Fieldn)

This article was written as an attempt to share the experience of installing the InterSystems Caché DBMS for production environment.
We all know that the development configuration of a DBMS is very different from real-life conditions.
As a rule, development is carried out in “hothouse conditions” with a bare minimum of security measures, but when we publish our project online, we must ensure its reliable and uninterrupted operation in a very aggressive environment.