The utility returns the desired values from the text and display the multiple values if exists based on starting and ending string.

Class Test.Utility.FunctionSet Extends %RegisteredObject
{

Git link: https://github.com/ecelg/InterSystems-IRIS-as-a-Spotify-REST-client

Recently, I come up an idea in my mind that how can I put my playlist on IRIS.🧐

At the same time, I was told to pay for my Spotify subscription💸💸... ooo.. how about to get some data from the Spotify API... so I started to do study about it.

Hi developers!

How do you debug implementation code in .impl classes of REST.API in InterSystems IRIS?

Especially if you don't have access to globals, so no things like:

Set ^AAA="here we are"

not possible in this case.

Suppose I have the following signature of the REST.API method called as POST and containing JSON. :

A benefit of using Doxygenerate is that Doxygen does more than just HTML output. Tweak the Doxyfile that tells Doxygen what to do and you can easily create a PDF. Our example MARINA application yielded a 524-page PDF. Here's what page 94 looks like:

You can browse the whole file here.

Hi Team,

I am converting xml message into HL7 message but the input XML message contains pdf which is converting into base 64 and getting mapped to OBX:5.5 in HL7 message and sending it to downstream

In Downstream service i am using normal HL7 TCP class EnsLib.HL7.Service.TCPService but the message looks like below i am not sure why stream is taking as another segment in HL7 message,

Any thoughts on this?

Thanks,

Smythee

Is there a way to delete suspended messages rather than using the WebMgmt gui?

We have over three million in one namespace, and using the gui I can only do 2000 at a time.

I was thinking of using delete in sql like Ens.MessageHeader where Status = 'Suspended'

But I don't know if that is a clean way to do it.

The rise of Big Data projects, real-time self-service analytics, online query services, and social networks, among others, have enabled scenarios for massive and high-performance data queries. In response to this challenge, MPP (massively parallel processing database) technology was created, and it quickly established itself. Among the open-source MPP options, Presto (https://prestodb.io/) is the best-known option. It originated in Facebook and was utilized for data analytics, but later became open-sourced.

InterSystems Announces General Availability of InterSystems IRIS, InterSystems IRIS for Health, and HealthShare Health Connect 2025.1

An extension “extends” or enhances a FHIR resource or a data element in a custom way. The extension can be added to the root of a resource, such as “Patient.ethnicity” in US Core profile, and they can be added to individual elements such as HumanName, Address or Identifier.

Did you know that you can also add an extension to a primitive data type?

Primitives usually store a single item and are the most basic element in FHIR. For example: "Keren", false, 1234, 12/08/2024 etc.

For example, the patient resources might look like this:

I've just stumbled across this post. I am an aspiring developer and one of my first few projects is a HL7 v2 message generator. It takes in a message template and then you can edit and create bulk messages from it.

BroadSea - Core OHDSI Walkthrough with InterSystems OMOP

My usecase is sorting and removing duplicates and getting count from a file that has json messages as a individual rows.

I am currently planning to use pandas for this purpose as its really fast. Below are the steps i am following

1) call a python function (called function) from IRIS classmethod(calling function)

2) the call python function will read the json file in a dataframe

3) perform sorting, dup removal, count in the dataframe

4) convert the dataframe into iris stream

5) return back the stream to iris calling function class method

Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ FHIR Object Model Classes in VS Code

https://www.youtube.com/embed/e7kHwsmRY7U
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Introduction

Database performance has become a critical success factor in a modern application environment. Therefore identifying and optimizing the most resource-intensive SQL queries is essential for guaranteeing a smooth user experience and maintaining application stability.

This article will explore a quick approach to analyzing SQL query execution statistics on an InterSystems IRIS instance to identify areas for optimization within a macro-application.

Rather than focusing on real-time monitoring, we will set up a system that collects and analyzes statistics pre-calculated by IRIS once an hour. This approach, while not enabling instantaneous monitoring, offers an excellent compromise between the wealth of data available and the simplicity of implementation.

We will use Grafana for data visualization and analysis, InfluxDB for time series storage, and Telegraf for metrics collection. These tools, recognized for their power and flexibility, will allow us to obtain a clear and exploitable view.

More specifically, we will detail the configuration of Telegraf to retrieve statistics. We will also set up the integration with InfluxDB for data storage and analysis, and create customized dashboards in Grafana. This will help us quickly identify queries requiring special attention.

To facilitate the orchestration and deployment of these various components, we will employ Docker.