Requirement: Transform source XML message to target JSON.

step1: First create json equivalent xml from any online tool.

step2: use add in studio utility create persistent classes from json equivalent xml and compile it , now target persistent classes are ready

step3: Do the above step for source xml or xsd and generate persistent classes for source and compile it

step4: complete the DTL by selecting root node from source, target persistent classes and complete the mappings and compile it

Hi community,

This is the third article in the series about initializing IRIS instances with Docker. This time, we will focus on Enterprise Cache Protocol (ECP).

In a very simplified way, ECP allows configuring some IRIS instances as application servers and others as data servers. Detailed technical information can be found in the official documentation.

This article aims to describe:

In this article, I’d like to present details of which technologies we had been using to develop our application for the IRIS for Health Contest:

Welcome community members to a new article! this time we are going to test the interoperability capabilities of IRIS for Health to work with DICOM files.

Let's go to configure a short workshop using Docker. You'll find at the end of the article the URL to access to GitHub if you want to make it run in your own computer.

Previously to any configuration we are going to explain what is DICOM:

Recently I needed to restore a version of a production class, which was overwritten by compilation and running UpdateProduction. As the correct version was unavailable in the source control, I used journals to restore the data. Journals store a plethora of information about what's happening in the system and are quite a powerful tool. This article explains how to work with journals to extract the data you require.

We return to the attack with our EMPI!

In previous articles we have seen how to configure and customize our EMPI, we have seen how we can include new patients in our system through HL7 messaging, but of course, not everything is HL7 v.2 in this life! How could we configure our EMPI instance to work with FHIR messaging?

InterSystems FAQ rubric

Record maps are used to efficiently map files containing delimited records or fixed-width records to message classes used by the interoperability function, and to map files from interoperability function message classes to text files.

Record map mapping definitions can be created using the Management Portal, and we also provide a CSV record wizard that allows you to define while reading a CSV file.

Hi Community,

In this article, I will introduce my application iris-image-vector-search.
The image vector retrieval demo uses IRIS Embedded Python and OpenAI CLIP model to convert images into 512 dimensional vector data. Through the new feature of Vector Search, VECTOR-COSINE is used to calculate similarity and display high similarity images.

Accessing an Azure cloud storage to upload/download blobs is quite easy using the designated %Net.Cloud.Storage.Client class API methods, or using the EnsLib.CloudStorage.* inbound/outbound adaptors.

Note that you'll need to have the %JavaServer External Language Server up and running to use the cloud storage API or adaptors, since they both use the PEX framework using the Java Server.

Here is a quick summary:

In the modern world, the most valuable asset for companies is their data. Everything from business processes and applications to transactions is based on data which defines the success of the organization's operations, analysis, and decisions. In this scenario, the data structures need to be ready for frequent changes, yet in a managed and governed way. Otherwise, we will inevitably lose money, time, and quality of corporate solutions.

I recently had to refresh my knowledge of the HealthShare EMPI module and since I've been tinkering with IRIS's vector storage and search functionalities for a while I just had to add 1 + 1.

For those of you who are not familiar with EMPI functionality here's a little introduction:

Enterprise Master Patient Index

In general, all EMPIs work in a very similar way, ingesting information, normalizing it and comparing it with the data already present in their system. Well, in the case of HealthShare's EMPI, this process is known as NICE:

Hello everyone,

I want to share my experience configuring an IIS server to enable secure HTTPs access to HealthShare/HealthConnect.

RabbitMQ is a message broker that allows producers (those who send a data message) and consumers (those who receive a data message) to establish asynchronous, real-time, and high-performance massive data flows. RabbitMQ supports AMQP (Advanced Message Queuing Protocol), an open standard application layer protocol.
The main reasons to employ RabbitMQ include the following:

• You can improve the performance of the applications using an asynchronous approach.
• It lets you decouple and reduce dependencies between services, microservices, and applications with the help of a data message mediator, meaning that there is no need for producers and consumers of exchanged data to know each other.
• It allows the long-running processing of sent data (with the results) to be delivered after utilizing a response queue.
• It helps you migrate from monolithic to microservices, where microservices exchange data via Rabbit in a decoupled and asynchronous way.
• It offers reliability and resilience by making it possible for messages to be stored and forwarded. A message can be delivered multiple times until it is processed.
• Message queueing is the key to scaling your application. As the workload increases, you will only have to add more workers to handle the queues faster.
• It works well with data streaming applications.
• It is beneficial for IoT applications.
• It is a must for Bots’ communication.

Introduction

This paper describes how Ensemble behaves after a system crash or similar uncontrolled shutdown or failover. Ensemble is normally configured to start processing messages automatically when the operating system restarts or when the system has failed over to a cluster member or mirror member. No manual intervention is required. But, in order for your system to robustly handle system failure and restart, you must understand how Ensemble handles these conditions and develop your productions using the rules and guidelines in this document.