#InterSystems IRIS

I have written a new script for csv file export, which writes lines to a %Library.File file based on a SQL query.

The code is simplified into the following as

Say I have an ObjectScript object called Book. It has 2 properties title and author. It extends JSON.%Adaptor, so I can call book.%JSONExport() and get this output:

In my web service I want to have a search function that returns an array of Books along with the total number of responses, like this:

If you look at the values.yaml of the IKO's Helm chart you'll find:

useIrisFsGroup: false 

Let's break down what it is and in what situations you may want to set it to true.

FsGroup refers to the file system group.

Hello Team,

I got xDBC protocol is not compatible while executing python script. How to fix this error

C:\Users\ak\Desktop\lpyth\iris>C:/Users/ak/AppData/Local/Programs/Python/Python312/python.exe c:/Users/ak/Desktop/lpyth/iris/irisconn.py
An error occurred: connection failed: IRIS xDBC protocol is not compatible

py -m pip list
Package Version
------------------ ---------
intersystems-iris 3.9.2

Introduction

If you're solving complex problems in ObjectScript, you probably have a lot of code that works with %Status values. If you have interacted with persistent classes from an object perspective (%Save, %OpenId, etc.), you have almost certainly seen them. A %Status provides a wrapper around a localizable error message in InterSystems' platforms. An OK status ($$$OK) is just equal to 1, whereas a bad status ($$$ERROR(errorcode,arguments...)) is represented as a 0 followed by a space followed by a $ListBuild list with structured information about the error. $System.Status (see class reference) provides several handy APIs for working with %Status values; the class reference is helpful and I won't bother duplicating it here. There have been a few other useful articles/questions on the topic as well (see links at the end). My focus in this article will be on a few debugging tricks techniques rather than coding best practices (again, if you're looking for those, see links at the end).

I ask ChatGPT periodically to produce ObjectScript or plain MUMPS code for string manipulation, or for implementing known algorithms etc. Occasionally, it does make mistakes or uses non-existing class members but generally not that bad. Is there any tutorial on the subject of using AI for coding, ideally specifically for ObjectScript/MUMPS? Any AI productivity advice, or tricks you are using, or another AI flavor?

Thanks in advance,
Anna

Hi Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ Integrating DBT and Apache Airflow with InterSystems IRIS @ Global Summit 2024

https://www.youtube.com/embed/tFHSoqZpA88
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Hi Guys,

Background

Embeddings is a new IRIS feature empowering the latest capability in AI semantic search.
This presents as a new kind of column on a table that holds vector data.
The embedding column supports search for another existing column of the same table.
As records are added or updated to the table, the supported column is passed through an AI model and the semantic signature is returned.
This signature information is stored as the vector for future search comparison.

Migrating InterSystems IRIS and InterSystems IRIS for Health from on-premises to the cloud offers many advantages for Application Providers and Solution Providers. These advantages include simplified operations, access to flexible resources, and enhanced resilience. Companies no longer need to worry about the physical constraints and expenses associated with maintaining on-prem infrastructure, such as power and space requirements and expensive computer hardware.

One of the most compelling benefits is the ability to accelerate speed to market. By removing the burden of infrastructure maintenance, cloud environments enable faster development and deployment cycles, allowing businesses to respond quickly to market demands and opportunities. Operational costs are also lowered, because companies can scale resources up or down based on actual needs, leading to more efficient use of capital. Moreover, migrating to the cloud can contribute to a reduced carbon footprint by optimizing energy usage through shared cloud infrastructure.

Transitioning to the cloud may involve significant changes. Companies may benefit from a more operational focus, managing and optimizing cloud resources continuously. This shift may require changes to business models, reconsideration of margins, and strategies for scaling operations up or out. While requiring more investment, embracing these changes can lead to improved agility and competitive advantage in the marketplace.

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.

I'm exploring this right now: given a bunch of types defined as Pydantic models, how can I come up with an equivalent %RegisteredObject/%SerialObject and convert to/from (e.g., to support persistence and match validation as much as possible)?

People who know Python better than I do (e.g., your average undergraduate from this decade): is this a stupid idea or a cool idea? Has anyone else done this before?

Hi,

How can I query fields by passing them in variable names, eg. I would like to query columns Book & Author fields from eg. the following :

S =var1="Book", var2="Author"

Select var1,var2 from myTables.Books

I tried @var1 or %var1 and didn't work

Thanks