An experiment on how to use the LangChain framework, IRIS Vector Search, and LLMs to generate IRIS-compatible SQL from user prompts.

This article was based in this notebook. You can run it with a ready to use environment with this application in OpenExchange.

Setup

First, we need to install the necessary libraries:

There are three things most important to any SQL performance conversation: Indices, TuneTable, and Show Plan. The attached PDFs includes historical presentations on these topics that cover the basics of these 3 things in one place. Our documentation provides more detail on these and other SQL Performance topics in the links below. The eLearning options reinforces several of these topics. In addition, there are several Developer Community articles which touch on SQL performance, and those relevant links are also listed.

There is a fair amount of repetition in the information listed below. The most important aspects of SQL performance to consider are:

1. The types of indices available
2. Using one index type over another
3. The information TuneTable gathers for a table and what it means to the Optimizer
4. How to read a Show Plan to better understand if a query is good or bad

When it comes to build an iris image, we can use the cpf merge files.

Here is an cpf merge example:

[Actions]
CreateDatabase:Name=IRISAPP_DATA,Directory=/usr/irissys/mgr/IRISAPP_DATA

CreateDatabase:Name=IRISAPP_CODE,Directory=/usr/irissys/mgr/IRISAPP_CODE

CreateNamespace:Name=IRISAPP,Globals=IRISAPP_DATA,Routines=IRISAPP_CODE,Interop=1

ModifyService:Name=%Service_CallIn,Enabled=1,AutheEnabled=48

CreateApplication:Name=/frn,NameSpace=IRISAPP,DispatchClass=Formation.REST.Dispatch,AutheEnabled=48

ModifyUser:Name=SuperUser,PasswordHash=a31d24aecc0bfe560a7e45bd913ad27c667dc25a75cbfd358c451bb595b6bd52bd25c82cafaa23ca1dd30b3b4947d12d3bb0ffb2a717df29912b743a281f97c1,0a4c463a2fa1e7542b61aa48800091ab688eb0a14bebf536638f411f5454c9343b9aa6402b4694f0a89b624407a5f43f0a38fc35216bb18aab7dc41ef9f056b1,10000,SHA512

How to create an ODBC connection on your native Windows laptop to IRIS running on a Windows VM on the same computer, test the connection, and pull data from IRIS into Excel.

Some of our applications provide SOAP services that use “DSTIME”-based SQL queries that return records that have recently been added or changed. Since the records don’t change often, these queries usually return a small number of records and therefore take little time.

When using InterSystems IRIS as an interoperability engine, we all know and love how easy it is to use the Message Viewer to review message traces and see exactly what's going on in your production. When a system is handling millions of messages per day, you may not know exactly where to begin your investigation though.

Over my years supporting IRIS productions, I often find myself investigating things like...

A customer recently asked if IRIS supported OpenTelemetry as they where seeking to measure the time that IRIS implemented SOAP Services take to complete. The customer already has several other technologies that support OpenTelemetry for process tracing. At this time, InterSystems IRIS (IRIS) do not natively support OpenTelemetry.

In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used.

I have challenged to create a bot application using Azure Bot that can retrieve and post data to IRIS for Health.

A patient's data has already been registered in the FHIR repository of IRIS for Health.

The patient's MRN is 1001. His name is Taro Yamada. (in Japanese :山田 太郎)

This bot can post new pulse oximeter readings as an observation resource linked to the patient.

When there's a performance issue, whether for all users on the system or a single process, the shortest path to understanding the root cause is usually to understand what the processes in question are spending their time doing. Are they mostly using CPU to dutifully march through their algorithm (for better or worse); or are they mostly reading database blocks from disk; or mostly waiting for something else, like LOCKs, ECP or database block collisions?

Since my initial question on ordering json properties a few things have happened.

The %Net.SSH.Session class lets you connect to servers using SSH. It's most commonly used with SFTP, especially in the FTP inbound and outbound adaptors.

In this article, I'm going to give a quick example of how to connect to an SSH server using the class, describe your options for authenticating, and how to debug when things go wrong.

Here's an example of making the connection:

I have been using embedded python for more than 2 years now on a daily basis.
May be it's time to share some feedback about this journey.

Why write this feedback? Because, I guess, I'm like most of the people here, an ObjectScript developer, and I think that the community would benefit from this feedback and could better understand the pros & cons of chosing embedded python for developing stuff in IRIS. And also avoid some pitfalls.

• Feedback : Using embedded python daily for 2 years
• Introduction
• Starting with Python
  • Python is not ObjectScript
    • Pep8
    • Modules
    • Dunders
  • Conclusion
• Embedded Python
  • What is Embedded Python ?
  • How to use Embedded Python ?
  • How I use Embedded Python
    • Use Python libraries and code as they were ObjectScript classes
      • With the language tag
      • Without the language tag
      • Conclusion
    • Use a python first approach
      • Example : iris-fhir-python-strategy
      • Remarks
      • Where to find the code
      • How to implement a Strategy
      • Implementation of InteractionsStrategy
      • Implementation of Interactions
      • Interactions in Python
      • Implementation of the abstract python class
      • Too long, do a summary

Welcome to the next chapter of my CI/CD series, where we discuss possible approaches toward software development with InterSystems technologies and GitLab.
Today, we continue talking about Interoperability, specifically monitoring your Interoperability deployments. If you haven't yet, set up Alerting for all your Interoperability productions to get alerts about errors and production state in general.

Inactivity Timeout is a setting common to all Interoperability Business Hosts. A business host has an Inactive status after it has not received any messages within the number of seconds specified by the Inactivity Timeout field. The production Monitor Service periodically reviews the status of business services and business operations within the production and marks the item as Inactive if it has not done anything within the Inactivity Timeout period.
The default value is 0 (zero). If this setting is 0, the business host will never be marked Inactive, no matter how long it stands idle.