Windows Subsystem for Linux (WSL) is a feature of Windows that allows you to run a Linux environment on your Windows machine, without the need for a separate virtual machine or dual booting. 

WSL is designed to provide a seamless and productive experience for developers who want to use both Windows and Linux at the same time**.

WSL 2 is the default distro type when installing a Linux distribution. WSL 2 uses virtualization technology to run a Linux kernel inside of a lightweight utility virtual machine (VM). Linux distributions run as isolated containers inside of the WSL 2 managed VM.

InterSystems IRIS offers various ways how to profile your code, in most cases it produces enough information to find the places where the most time is spent or where the most global sets. But sometimes it's difficult to understand the execution flow and how it ended at that point. 

To solve this, I've decided to implement a way to build a report in a way, so, it's possible to dive by stack down

Slowness of the 'Source' and 'Target' parameters in the (portal) Message Viewer is caused by the Bitmap indices of Ens.MessageHeader.

Running the 'bitmap index clean up' routine for Ens.MessageHeader will fix the issue.

I checked with WRC and they advised:

“Yes it is safe to run this tool on a live system. It will eat up 1 CPU and load a lot of data from disk into global buffers so I would suggest running it at a slower time of day.”

To compress the Bitmap indices of Ens.MessageHeader use the terminal to call OneClass():

zn "PRODUCTION"

do ##class(%SYS.Maint.Bitmap).OneClass("Ens.

Since the introduction of Embedded Python there has always been doubt about its performance compared to ObjectScript and on more than one occasion I have discussed this with @Guillaume Rongier , well, taking advantage of the fact that I was making a small application to capture data from public competitions in Spain and to be able to perform searches using the capabilities of VectorSearch I saw the opportunity to carry out a small test.

Here is a snippet that I learned yesterday

You can define an index on a collection property but when I tried to use it, I failed. I was using

     Select ….. where …. :xx %INLIST collproperty

But this will not use an index, but the equivalent syntax

     SELECT .. WHERE ... FOR SOME %ELEMENT(collproperty) (%VALUE=:xx)

will use the index 

Check out

     http://docs.intersystems.com/latest/csp/docbook/DocBook.UI.Page.cls?KEY…

Dave

This article describes a significant enhancement of how InterSystems IRIS deals with table statistics, a crucial element for IRIS SQL processing, in the 2025.2 release. We'll start with a brief refresher on what table statistics are, how they are used, and why we needed this enhancement. Then, we'll dive into the details of the new infrastructure for collecting and saving table statistics, after which we'll zoom in onto what the change means in practice for your applications. We'll end with a few additional notes on patterns enabled by the new model, and look forward to the follow-on phases of this initial delivery.

One of my colleagues had developed an interface in Health Connect (HealthShare 2019.1) to add large amounts of data to an external SQL Server database. The data comes from many text files with delimited rows and data for one table per file. There is a business process to read a file line by line and send an Insert Request to an operation. The request contains an Insert statement like ‘Insert into TABLE columns (col1, col2, … colZ) values (val1, val2, … valZ).’ The Health Connect operation utilizes Outbound SQL Adapter to insert one row into a table per request.

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.

 It's almost time to get your customers upgraded to new versions - are you worried about showing off your SQL Performance after upgrades?  If you want to upgrade without worrying, then I have just the program for you!!!  Check out this video from Global Summit 2016 featuring yours truly explaining how to upgrade a system without worrying about pesky SQL queries showing on your waistline!  

https://www.youtube.com/watch?v=GfFPYfIoR_g

Unfortunately the video started after the Frozen Musical Sing-a-long, but it's 30 minutes of the most fun you'll have while learning tools and tips for Caché

Here at InterSystems, we often deal with massive datasets of structured data. It’s not uncommon to see customers with tables spanning >100 fields and >1 billion rows, each table totaling hundred of GB of data. Now imagine joining two or three of these tables together, with a schema that wasn’t optimized for this specific use case. Just for fun, let’s say you have 10 years worth of EMR data from 20 different hospitals across your state, and you’ve been tasked with finding….

I attended Cloud Native Security Con in Seattle with full intention of crushing OTEL day, then perusing the subject of security applied to Cloud Native workloads the following days leading up to CTF as a professional excercise. This was happily upended by a new understanding of eBPF, which got my screens, career, workloads, and atitude a much needed upgrade with new approaches to solving workload problems. 

So I made it to the eBPF party and have been attending clinic after clinic on the subject ever since, here I would like to "unbox" eBPF as a technical solution, mapped directly to what we do in practice (even if its a bit off), and step through eBPF through my experimentation on supporting InterSystems IRIS Workloads, particularly on Kubernetes, but not necessarily void on standalone workloads.

eBee Steps with eBPF and InterSystems IRIS Workloads

InterSystems IRIS 2024 recently introduced the vector types. This addition empowers developers to work with vector search, enabling efficient similarity searches, clustering, and a range of other applications. In this article, we will delve into the intricacies of vector types, explore their applications, and provide practical examples to guide your implementation.

At its essence, a vector type is a structured collection of numerical values arranged in a predefined order. These values serve to represent different attributes, features, or characteristics of an object.

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. However, since Teradata has joined the Presto community, it offers support now.

Often times support and sales engineers are asked about recent benchmark results on various platforms and large scale configurations.  These will be made available here in the Developer Community in the "Documentation" section, and as an example here's a link to a recent Intel E7 v2 series processor benchmark.

https://community.intersystems.com/documentation/data-scalability-intersystems-caché-and-intel-processors-0

There are several reports available and more will be made available on an on-going basis.

It's been a long time since I didn't write an update post on IoP.

So what's new since IoP command line interface was released?

Two new big features were added to IoP:

• Rebranding: the grongier.pex module was renamed to iop to reflect the new name of the project.
• Async support: IoP now supports async functions and coroutines.

Rebranding

The grongier.pex module was renamed to iop to reflect the new name of the project.

The grongier.pex module is still available for backward compatibility, but it will be removed in the future.

So if you are following from the previous post or dropping in now, let's segway to the world of eBPF applications and take a look at Parca, which builds on our brief investigation of performance bottlenecks using eBPF, but puts a killer app on top of your cluster to monitor all your iris workloads, continually, cluster wide!  

Continous Profiling with Parca, IRIS Workloads Cluster Wide

High-Performance Message Searching in Health Connect

The Problem

Have you ever tried to do a search in Message Viewer on a busy interface and had the query time out? This can become quite a problem as the amount of data increases. For context, the instance of Health Connect I am working with does roughly 155 million Message Headers per day with 21 day message retention. To try and help with search performance, we extended the built-in SearchTable with commonly used fields in hopes that indexing these fields would result in faster query times. Despite this, we still couldn't get some of these queries to finish at all.

Optimizing Performance of Apache Web Server and Web Gateway

By Patrick Jamieson, M.D., Product Technical Manager, InterSystems IRIS for Health

When working with InterSystems IRIS or IRIS for Health, an external web server like Apache2 or NGINX is essential for managing HTTP workloads, especially for FHIR servers Starting with version 2023.3, the private Apache server was removed from the installation kit (except for Community Editions and Health Connect).

In Part 1, we explored how window functions operate. We learned the logic behind PARTITION BY, ORDER BY, and such functions as ROW_NUMBER() and RANK(). Now, in Part 2, let's delve into more window functions with practical examples.

1. Aggregate-over-Window Functions

Overview

These functions compute an aggregate (e.g., sum, average, min, max, count, etc.) over the defined window frame but don’t collapse rows.
Each row remains visible, augmented with aggregated values for its partition.

Supported functions include the following:

• AVG() — average of values in the window frame.

Introduction

MonLBL is a tool for analyzing the performance of ObjectScript code execution line by line. codemonitor.MonLBL is a wrapper based on the %Monitor.System.LineByLine package from InterSystems IRIS, designed to collect precise metrics on the execution of routines, classes, or CSP pages.

The wrapper and all examples presented in this article are available in the following GitHub repository: iris-monlbl-example

Hello!!!

Data migration often sounds like a simple "move data from A to B task" until you actually do it. In reality, it is a complex process that blends planning, validation, testing, and technical precision.

Over several projects where I handled data migration into a HIS which runs on IRIS (TrakCare), I realized that success comes from a mix of discipline and automation.

Here are a few points which I want to highlight.

1. Start with a Defined Data Format.

Before you even open your first file, make sure everyone, especially data providers, clearly understands the exact data format you expect. Defining templates early avoids unnecessary bank-and-forth and rework later. 

While Excel or CSV formats are common, I personally feel using a tab-delimited text file (.txt) for data upload is best. It's lightweight, consistent, and avoids issues with commas inside text fields. 

PatID   DOB Gender  AdmDate
10001   2000-01-02  M   2025-10-01
10002   1998-01-05  F   2025-10-05
10005   1980-08-23  M   2025-10-15

Make sure that the date formats given in the file is correct and constant throughout the file because all these files are usually converted from an Excel file and an Basic excel user might make mistakes while giving you the date formats wrong. Wrong date formats can irritate you while converting into horolog.

This article outlines the process of utilizing the renowned Jaeger solution for tracing InterSystems IRIS applications. Jaeger is an open-source product for tracking and identifying issues, especially in distributed and microservices environments. This tracing backend that emerged at Uber in 2015 was inspired by Google's Dapper and Twitter's OpenZipkin. It later joined the Cloud Native Computing Foundation (CNCF) as an incubating project in 2017, achieving graduated status in 2019. This guide will demonstrate how to operate the containerized Jaeger solution integrated with IRIS.

Hello community,

I wanted to share my experience about working on Large Data projects. Over the years, I have had the opportunity to handle massive patient data, payor data and transactional logs while working in an hospital industry. I have had the chance to build huge reports which had to be written using advanced logics fetching data across multiple tables whose indexing was not helping me write efficient code.

Here is what I have learned about managing large data efficiently.

Choosing the right data access method.

As we all here in the community are aware of, IRIS provides multiple ways to access data. Choosing the right method, depends on the requirement.

• Direct Global Access: Fastest for bulk read/write operations. For example, if i have to traverse through indexes and fetch patient data, I can loop through the globals to process millions of records. This will save a lot of time.

Set ToDate=+H
Set FromDate=+$H-1 For  Set FromDate=$O(^PatientD("Date",FromDate)) Quit:FromDate>ToDate  Do
. Set PatId="" For  Set PatId=$Order(^PatientD("Date",FromDate,PatID)) Quit:PatId=""  Do
. . Write $Get(^PatientD("Date",FromDate,PatID)),!

• Using SQL: Useful for reporting or analytical requirements, though slower for huge data sets.

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.

Embeddedpy-bridge: A Toolkit for Embedded Python

Overview

Embedded Python is a game-changer for InterSystems IRIS, offering access to the vast Python ecosystem directly within the database. However, bridging the gap between ObjectScript and Python can sometimes feel like translating between two different worlds.

To make this transition seamless using embeddedpy-bridge.

This package is a developer-centric utility kit designed to provide high-level ObjectScript wrappers, familiar syntax, and robust error handling for Embedded Python.

Looking at my database I see I have a very big ^rINDEXSQL global? Why is that? 😬

In the Management Portal SQL page, under "SQL Statements" I see a 'Clean stale' button - what does this do? 🤔

In the list of Statements some have a 'Location' value and some don't? How is that? 🤨

Technical Documentation — Quarkus IRIS Monitor System

1. Purpose and Scope

This module enables integration between Quarkus-based Java applications and InterSystems IRIS’s native performance monitoring capabilities.
It allows a developer to annotate methods with @PerfmonReport, which triggers IRIS’s ^PERFMON routines automatically around method execution, generating performance reports without manual intervention.

2. System Components

2.1 Annotation: @PerfmonReport

• Defined as a CDI InterceptorBinding.
• Can be applied to methods or classes.

The Rut

Up until early this year, I haven't been not doing much coding at all -- I had gotten sick of it.

After many years as a hands-on software engineer and data scientist, I got burned out around 2015. I switched to business development roles focused on "external innovation," then joined InterSystems in 2019 as a product manager. I missed the creative aspects of coding, but not the tedium. The endless cycle of boilerplate, debugging, and context-switching had left me creatively depleted.