When I started my journey with InterSystems IRIS, especially in Interoperability, one of the initial and common questions I had was: how can I run something on an interval or schedule? In this topic, I want to share two simple classes that address this issue. I'm surprised that some similar classes are not located somewhere in EnsLib. Or maybe I didn't search well? Anyway, this topic is not meant to be complex work, just a couple of snippets for beginners.

Window functions in InterSystems IRIS let you perform powerful analytics — like running totals, rankings, and moving averages — directly in SQL.
They operate over a "window" of rows related to the current row, without collapsing results like GROUP BY.
This means you can write cleaner, faster, and more maintainable queries — no loops, no joins, no temp tables.

In this article let's understand the mechanics of window functions by addressing some common data analisys tasks.

Table of Contents

1. Purpose of the article
2. What containers are and why they make sense with IRIS
    2.1 Containers and images in a nutshell
    2.2 Why containers are useful for developers
    2.3 Why IRIS works well with Docker
3. Prerequisites
4. Installing the InterSystems IRIS image
    4.1 Using Docker Hub
    4.2 Pulling the image
5. Running the InterSystems IRIS image
    5.1 Starting an IRIS container
    5.2 Checking container status
    5.3 Executing code in the container terminal
    5.4 Accessing the IRIS Management Portal
    5.5 Connecting the container to VS Code
    5.6 Stopping or removing the container
    5.7 Setting a specific password with a bind mount
    5.8 Using durable %SYS volumes
     5.8.1 What gets stored with durable %SYS
     5.8.2 How to enable durable %SYS
6. Using Docker Compose
    6.1 Docker Compose example
    6.2 Running Docker Compose
7. Using a Dockerfile to run custom source code
    7.1 Dockerfile example
    7.2 Docker Compose example
    7.3 Understanding layers, image tagging and build vs. run time
    7.4 Source code and init script
    7.5 Building the image with Dockerfile
    7.6 Running instructions in the containerized IRIS terminal
8. Conclusion and what’s next

The Interoperability user interface now includes modernized user experiences for the DTL Editor and Production Configuration applications that are available for opt-in in all interoperability products. You can switch between the modernized and standard views. All other Interoperability screens remain in the Standard user interface. Please note that changes are limited to these two applications and we identify below the functionality that is currently available.

InterSystems FAQ rubric

When exporting using the Export() method of the %Library.Global class, if the export format (fourth argument: OutputFormat) is set to 7, "Block format/Caché block format (%GOF)," mapped globals cannot be exported (only globals in the default global database of the namespace are exported). To export mapped globals in "Block format/Caché block format (%GOF)," specify the database directory to which you want to map them in the first parameter of %Library.Global.Export().

An example of execution is shown below.

The following regex is matching while I think it should not :

What is XML?

Hey Community!

We're happy to share the next video in the "Code to Care" series on our InterSystems Developers YouTube:

⏯ From Words to Molecules: How AI Is Transforming Medicine and Beyond

https://www.youtube.com/embed/YK___IalmYE
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InterSystems IRIS Adaptive Analytics version 2025.4.1 is now available from the InterSystems Software Distribution page. This release includes AtScale 2025.4.1 and is compatible with the existing Adaptive Analytics User-Defined Aggregate Function (UDAF) file - 2024.1. New features included in AtSCale's 2025 releases include:

Let’s shine a light on the amazing authors and contributors of our October Article Bounty! 💙
Huge thanks to everyone who joined in and shared their knowledge.

A special mention goes to those who created brand-new articles and shared their expertise — each received 5,000 points 🎉

1. @Robert Cemper >> "Sample for Beginners with Streams in IRIS"
2. @Vachan C Rannore >> "What I’ve Learned from Multiple Data Migrations"
3. @Harshitha >> "Tips on handling Large data"

And also to those who joined the challenge and helped us in the search for interesting articles (each received 30 points 🙌):

CCR users can now take advantage of an enhanced syntax for substituting pre-defined tokens with live URL links within phase-related text fields. In addition to the existing <env> token which automatically updates to reflect the Environment of the relevant CCR Record, CCR now introduces three new keywords: <smp> , <smpPrefix> , and <homepage>.

So, you checked your server and saw that IRISTEMP is growing too much. There's no need to panic. Let’s investigate the issue before your storage runs out.

Step 1: Confirm the IRISTEMP Growth Issue

Before assuming IRISTEMP is the problem, let’s check its actual size.

Check the Free Space

Run the following command in the IRIS terminal:

%SYS>do ^%FREECNT

When prompted, enter:

Introduction

My guess is that most IRIS developers create their applications using its native ObjectScript language or, if using an external language, then most likely using either Java, Python or perhaps C++.

I suspect that only a minority have considered using JavaScript as their language of choice, which, if true, is a great shame, because, In my opinion and experience, JavaScript is the closest equivalent to ObjectScript in terms of its ability to integrate with the IRIS's underlying multi-dimensional database.

Mirror Your Database Across the Galaxy with Seeding

Hello cpf fans! This distraction I used the "seed" capability in IRIS to provision an entire IrisCluster mirror, 4 maps wide with compute starting from an IRIS.DAT in a galaxy far far away. This is pretty powerful if you have had a great deal of success with a solution running on a monolithic implementation and want it to scale to the outer rim with Kubernetes and the InterSystems Kubernetes Operator. Even though my midichlorian count is admittely low, I have seen some hardcore CACHE hackers shovel around DATS, compact and shrink and update their ZROUTINES, so this same approach could also be helpful shrinking and securing your containerized workload too. If you squint and feel all living things around you, you can see a glimpse of in place (logical) mirroring in the future as a function of the operator and a migration path to a fully operational mirrored Death Star as the workload matures.