Hello Community! 👋
Welcome to the second part of the IRIS IO Utility series. This extension represents my submission for the InterSystems "Bringing Ideas to Reality" Contest 2025 and offers you an intuitive and powerful interface for importing and exporting data directly inside VS Code.

Apache Airflow is the leading open-source platform to programmatically author, schedule, and monitor data pipelines and workflows using Python. Workflows are defined as code (DAGs), making them version-controlled, testable, and reusable. With a rich UI, 100+ built-in operators, dynamic task generation, and native support for cloud providers, Airflow powers ETL/ELT, ML pipelines, and batch jobs at companies like Airbnb, Netflix, and Spotify.

Airflow Application Layout

I'm pleased to announce the publication of gj :: dataLoader, a new VS Code extension that simplifies the task of loading data from local CSV files into SQL tables on your InterSystems IRIS servers.

Here's an introductory video:

https://www.youtube.com/embed/XohVoW5rSy4
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The previous article introduced IrisOASTestGen, a tool designed to generate REST API test code for InterSystems IRIS based on OpenAPI 2.0 specifications. It demonstrated how to scaffold test cases using the default templates bundled with OpenAPI Generator.

This follow-up focuses on the next natural step: customizing the generated test code.
By extending the code generation logic with Mustache templates, it becomes possible to express richer semantics, implement CRUD-aware tests, and create more meaningful test suites.

Modern SQL engines are enormously complex pieces of software. Even when they appear stable and mature, subtle bugs can hide in their optimizers, type systems, predicate evaluation, or execution layers. These bugs rarely announce themselves loudly. Instead, they quietly produce incorrect results, behave inconsistently, or fail abruptly under specific combinations of SQL constructs.

This is precisely why tools like SQLancer exist. SQLancer automatically generates SQL queries and uses logical “oracles” to detect when a database behaves incorrectly. It has revealed hundreds of real bugs in widely used systems such as MySQL, PostgreSQL, SQLite, and DuckDB.

With this in mind, I attempted to bring SQLancer to InterSystems IRIS, starting with the NOREC oracle — a powerful method for detecting optimizer correctness issues. The journey, however, uncovered not just potential SQL correctness problems, but also a surprising number of driver-level and server-level failures that prevented SQLancer from running at full strength.

This article summarizes why SQLancer is important, how the NOREC oracle works, and what unexpected findings appeared while testing IRIS.

One of the newest features of .Net core 10 with C# 14 is the file-based apps. This feature allows you to execute C# code in a simple .cs file without the need to create a solution, a project, or any of the related structure.

For example you can create a script.cs file using the notepad with the content:

Console.WriteLine(“This is a script in c#.”);

Then in the command line or the terminal you execute the command:

FastJsonSchema: High-Performance JSON Validation in IRIS

Validating JSON data against JSON Schema is a common requirement for modern applications. FastJsonSchema brings this capability natively to InterSystems IRIS, combining speed, simplicity, and full schema compliance.

Unlike traditional validation approaches, FastJsonSchema generates native ObjectScript code from your JSON Schemas and compiles it directly to iris object code, enabling idiomatic performance without relying on external libraries or runtimes.

Project Overview / Introduction

Developing and testing REST APIs in InterSystems IRIS often requires a significant amount of boilerplate code. While ObjectScript provides powerful tools for building APIs, writing consistent and repeatable tests can be time‑consuming. This is where IrisOASTestGen comes in.

There's a pattern I've encountered several times where I need to use a temp file/folder and have it cleaned up at some point later.

The natural thing to do here is to follow the patterns from "Robust Error Handling and Cleanup in ObjectScript" with a try/catch/pseudo-finally or a registered object to manage cleanup in the destructor. %Stream.File* also has a "RemoveOnClose" property that you can set - but use with care, as you could accidentally remove an important file, and this flag gets reset by calls to %Save() so you'll need to set it back to 1 after doing that.

There's one tricky case, though - suppose you need the temp file to survive in an enclosing stack level. e.g.:

In this final part of our introduction to Window Functions, we will explore the remaining functions that have not been covered yet. You will also discover performance tips and a practical guide to help you decide when (and when not) to use window functions effectively.

1. Offset and Positional Value Functions

Overview

These functions reference values are calculated from other rows relative to the current row, or they are extracted from the first, last, or nth values within a window.

The Load Data utility it is an excellent tool to load data from CSV/TXT files into an IRIS SQL Table, but it is required send the target file to the IRIS server and write the Load Data sentence to ingest the file content. Now it is possible select a file in VSCode, set the table destination and submit the request. The vscode-load-data utility will send the file to the IRIS server and run the Load Data command to you! Very simple:

The InterSystems IRIS data platform underlies all InterSystems applications, as well as thousands of customer and partner applications across Healthcare, Financial Services, Supply Chain, and other ecosystems. It is a converged platform, providing transactional-analytical data management, integrated interoperability, and data integration, as well as integrated analytics and AI. It supports the InterSystems Smart Data Fabric approach to managing diverse and distributed data.

One objective of vectorization is to render unstructured text more machine-usable. Vector embeddings accomplish this by encoding the semantics of text as high-dimensional numeric vectors, which can be employed by advanced search algorithms (normally an approximate nearest neighbor algorithm like Hierarchical Navigable Small World). This not only improves our ability to interact with unstructured text programmatically but makes it searchable by context and by meaning beyond what is captured literally by keyword.

Introduction and Motivation

A unit of ObjectScript code (a ClassMethod, say) may produce a variety of unexpected side effects by interacting with parts of the system outside of its own scope and not properly cleaning up. As a non-exhaustive list, these include: