Article
· Jul 28, 2022 1m read
Approach to InterSystems IRIS

Hi Folks,

Before I begin my writing journey here I wish to introduce myself briefly, so that everyone who reads and follows me will get a clear picture.

To start with I did my Bachelors in Physical Sciences, Mathematics and Computer Science were my core subjects. I have 4+ years of experience in HealthCare Revenue Cycle operations including Medical Coding, Billing, AR Collections, Denial Management and Fincial Reconciliation. Also, 2+ years of experience in Data Operations and Analytics, specifically in Python, PowerBI, SQL and MsExcel.

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In the previous parts (1, 2) we talked about globals as trees. In this article, we will look at them as sparse arrays.

A sparse array - is a type of array where most values assume an identical value.

In practice, you will often see sparse arrays so huge that there is no point in occupying memory with identical elements. Therefore, it makes sense to organize sparse arrays in such a way that memory is not wasted on storing duplicate values.

In some programming languages, sparse arrays are part of the language - for example, in J, MATLAB. In other languages, there are special libraries that let you use them. For C++, those would be Eigen and the like.

Globals are good candidates for implementing sparse arrays for the following reasons:

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The last time that I created a playground for experimenting with machine learning using Apache Spark and an InterSystems data platform, see Machine Learning with Spark and Caché, I installed and configured everything directly on my laptop: Caché, Python, Apache Spark, Java, some Hadoop libraries, to name a few. It required some effort, but eventually it worked.

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In this article I'll show you how to set up in your laptop, very quickly, a cluster of IRIS nodes in sharding. It's not the goal of this article neither to talk about sharding in detail nor define a deployment of a production ready architecture, but to show how to set up quickly, in your own machine, a cluster of IRIS instances configured as shard nodes, with which you'll able to play and test this functionality. If you're insterested in knowing more about sharding in IRIS, take a look at the documentation clicking here.

First and foremost, I want to remark that IRIS sharding will allow us 2 things:

  • Define, load and query shard tables, which data will be distributed transparently between the cluster's nodes
  • Define federated tables, which offer a global and composed view of data belonging to different tables that will be physically stored in different distributed nodes

So, as I said, we let for other article playing with shard or federated tables, and just focus now in the previous step, that is, setting up the cluster of shard nodes.

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD

In the previous article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software. Still, our focus was on the implementation part of software development, but this part presents:

  • GitLab Workflow - a complete software life cycle process - from idea to user feedback
  • Continuous Delivery - software engineering approach in which teams produce software in short cycles, ensuring that the software can be reliably released at any time. It aims at building, testing, and releasing software faster and more frequently.

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InterSystems products (IRIS, Caché, Ensemble) already include a built-in Apache web server. But the built-in server is designed for the development and administration tasks and thus has certain limitations. Though you may find some useful workarounds for these limitations, the more common approach is to deploy a full-scale web server for your production environment. This article describes how to set up Apache to work with InterSystems products and how to provide HTTPS access. We will be using Ubuntu, but the configuration process is almost the same for all Linux distributions.

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This article was written as an attempt to share the experience of installing the InterSystems Caché DBMS for production environment.
We all know that the development configuration of a DBMS is very different from real-life conditions.
As a rule, development is carried out in “hothouse conditions” with a bare minimum of security measures, but when we publish our project online, we must ensure its reliable and uninterrupted operation in a very aggressive environment.

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Hi InterSystems Developers!

Recently I've updated the FHIR dev template so that it now publishes an IPM package fhir-server that makes the setup of InterSystems FHIR server a trivial manual or automatic or programmatic procedure one command long.

Please see below how you can benefit from it.

TLDR

USER>zpm "install fhir-server"

All the details below.

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In this article, we will run an InterSystems IRIS cluster using docker and Merge CPF files - a new feature allowing you to configure servers with ease.

On UNIX® and Linux, you can modify the default iris.cpf using a declarative CPF merge file. A merge file is a partial CPF that sets the desired values for any number of parameters upon instance startup. The CPF merge operation works only once for each instance.

Our cluster architecture is very simple, it would consist of one Node1 (master node) and two Data Nodes (check all available roles). Unfortunately, docker-compose cannot deploy to several servers (although it can deploy to remote hosts), so this is useful for local development of sharding-aware data models, tests, and such. For a productive InterSystems IRIS Cluster deployment, you should use either ICM or IKO.

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Hi Developers!

Often I find questions on how to install IRIS, connect to IRIS from IDE, setup the environment, compile, debug, maintain the repository.

Here below possibly the shortest way to set up all the environment and start development with ObjectScript on InterSystems IRIS.

Prerequisites

Make sure you have Git, Docker, and VSCode installed

Install Docker and ObjectScript extensions into VSCode

Sign in or Create an account on Github

Here we go!

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Article
· Aug 1, 2019 3m read
Nested set model for ObjectScript

In many projects I was faced with storing hierarchical data (tree) in classes.
By tree, I mean such data, where each node has a parent node — an object of the same class.
Many examples of such data can be given. For example, a catalog in the online store. Suppose that this online store sells books, in this case, the category tree might look like this:

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Article
· Jul 27, 2018 4m read
Load a ML model into InterSystems IRIS

Hi all. Today we are going to upload a ML model into IRIS Manager and test it.

Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.

Introduction

These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.

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Here you have an easy way to write and execute COS code from your unix scripts. This way one does not need to write routines or even open Studio or Atelier. It can be an option for simple and small actions for instance things like installation tasks or compiling.

See sample bash script (compile.sh) to compile classes:

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Article
· Sep 23, 2016 6m read
Creating a RESTful Service using Ensemble

This is a detailed guide to develop RESTful services using InterSystems Ensemble. The goal of this guide is to make you understanding the basic concept and building blocks of a RESTful service. The service is going to provide a very basic functionality (a “Hello world!”).

You will learn how to create required components as Ensemble classes, configure the run-time as an Ensemble Production and create a service configuration as a web application.

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