#InterSystems IRIS

It's also an example of a customized SystemFunction extension (ZZISJSON) in Caché & IRIS
This time it is to be included in %ZLANGF00.mac

A JSON string is mostly imported from a file or over REST
You rely on a clean and compatible structure. This is the check.

required: ZPretty.mac

demo

Allow limited durability for demo and development IRIS-Docker-micro-Durability During development of a container based demo I found the need to access a fresh docker
an instance of IRIS image (e.g intersystems/iris-community:2020.2.0.199.0) over and over.
To bypass loading my code repeatedly I developed this workaround.

It is a reduced variant of Docker - light weight durability

Hi Developers!

In March we are starting our first InterSystems IRIS Programming Contest! It's a competition in creating open-source solutions using InterSystems IRIS Data Platform.

The topic for the first contest is InterSystems IRIS, Docker and ObjectScript!

The contest will last three weeks: March 9-31, 2020.

Prizes:

There will be money prizes for Experts Nomination - winners will be determined by a specially selected jury:

🥇 1st place - $2,000

🥈 2nd place - $1,000

🥉 3rd place - $500

Also, there will be Community Nomination - an application that will receive the most votes in total:

🏆 1st place - $1,000

And we provide winners with high-level badges on Global Masters.

I am happy to announce that InterSystems API Manager is now generally available. InterSystems API Manager (IAM) is a new feature of the InterSystems IRIS Data Platform™, enabling you to monitor, control and govern traffic to and from web-based APIs within your IT infrastructure.

Hyper-Converged Infrastructure (HCI) solutions have been gaining traction for the last few years with the number of deployments now increasing rapidly. IT decision makers are considering HCI when scoping new deployments or hardware refreshes especially for applications already virtualised on VMware. Reasons for choosing HCI include; dealing with a single vendor, validated interoperability between all hardware and software components, high performance especially IO, simple scalability by addition of hosts, simplified deployment and simplified management.

I saw someone recently refer to ECP as magic. It certainly seems so, and there is a lot of very clever engineering to make it work. But the following sequence of diagrams is a simple view of how data is retrieved and used across a distributed architecture.

For more more on ECP including capacity planning follow this link: Data Platforms and Performance - Part 7 ECP for performance, scalability and availability

Learn how to design scalable, autonomous AI agents that combine reasoning, vector search, and tool integration using LangGraph.

Why I've decided to write this

In my last article I've talked about returning values with Python. But returning them is simple, what can make it harder is what I'm going to talk about today: where the value is treated.

Python object in IRIS

Following the example of the last aricle, we have the method:

There are a lot of great community articles regarding "vector search on IRIS", and samples in OpenExchange. Everytime I see these, I'm so excited to know that so many developers already try vectors on IRIS!

But if you've not tried "Vector Search on IRIS" yet, please give me one minute 😄 I create one IRIS class - and with only one IRIS class you can see how you put vector data in your IRIS database and how you compare these in your application.

Who hasn't been developing a beautiful example using a Docker IRIS image and had the image generation process fail in the Dockerfile because the license under which the image was created doesn't contain certain privileges?

In my case, what I was deploying in Docker is a small application that uses the Vector data type. With the Community version, this isn't a problem because it already includes Vector Search and vector storage. However, when I changed the IRIS image to a conventional IRIS (the latest-cd), I found that when I built the image, including the classes it had generated, it returned this error:

Introduction

As the health interoperability landscape expands to include data exchange across on-premise as well as hosted solutions, we are seeing an increased need to integrate with services such as cloud storage. One of the most prolifically used and well supported tools is the NoSQL database DynamoDB (Dynamo), provided by Amazon Web Services (AWS).

Parallel query hinting boosts certain query performances on multi-processor systems via parallel processing. The SQL optimizer determines when this is beneficial. On single-processor systems, this hint has no effect.

Parallel processing can be managed by:

1. Setting the auto parallel option system-wide.
2. Using the %PARALLEL keyword in the FROM clause of specific queries.

%PARALLEL is ignored when it applied to:

Host Variables are a rather common programming feature in many implementations of SQL.
A recent question in DC made me aware that in IRIS, Caché, Ensemble, ...
host variables just exist within embedded SQL

> You can supply host variables for Embedded SQL queries only. <

Related examples are included in the available Documentation

This is a description for a workaround if you don't / can't use embedded SQL.

When you deploy code from a repo, class (file) deletion might not be reflected by your CICD system.
Here's a simple one-liner to automatically delete all classes in a specified package that have not been imported. It can be easily adjusted for a variety of adjunct tasks:

set packages = "USER.*,MyCustomPackage.*"
set dir = "C:\InterSystems\src\"
set sc = $SYSTEM.OBJ.LoadDir(dir,"ck", .err, 1, .loaded)
set sc = $SYSTEM.OBJ.Delete(packages _ ",'" _ $LTS($LI($LFS(loaded_",",".cls,"), 1, *-1), ",'"),, .err2)

The first command compiles classes and also returns a list of loaded classes. The second command deletes all classes from specified packages, except for the classes loaded just before that.