In the vast and varied SQL database market, InterSystems IRIS stands out as a platform that goes way beyond just SQL, offering a seamless multimodel experience and supporting a rich set of development paradigms. Especially the advanced Object-Relational engine has helped organizations use the best-fit development approach for each facet of their data-intensive workloads, for example ingesting data through Objects and simultaneously querying it through SQL. Persistent Classes correspond to SQL tables, their properties to table columns and business logic is easily accessed using User-Defined Functions or Stored Procedures. In this article, we'll zoom in on a little bit of the magic just below the surface, and discuss how it may affect your development and deployment practices. This is an area of the product where we have plans to evolve and improve, so please don't hesitate to share your views and experiences using the comments section below.

NewBie's Corner Session 27 Traversing A Global with $Order Part 1

Welcome to NewBie's Corner, a weekly or biweekly post covering basic Caché Material.

Traversing A Global

Perhaps the most difficult concept in Caché/MUMPS is its Global Structure. This session and several that follow it deals with the Global Structure. However, just presenting the material will not guarantee your understanding of it. You must experiment with the data and concepts that are presented.

Productions often need to receive REST requests.

Here's how to do that.

1. Create proxy Service:

/// Empty BS we would use to send Produciton requests
Class production.ProxyService Extends Ens.BusinessService
{
}

2. Add it to production as RESTService (or any other name).

Hi,

We are wondering how to create translation profile for HL7 to SDA in "HEALTH SHARE". can you please help us with the class definition containing the mapping for that(so that we can import directly and understand the mapping).

Thanks,

Sam

Earlier in this series, we've presented four different demo applications for iKnow, illustrating how its unique bottom-up approach allows users to explore the concepts and context of their unstructured data and then leverage these insights to implement real-world use cases. We started small and simple with core exploration through the Knowledge Portal, then organized our records according to content with the Set Analysis Demo, organized our domain knowledge using the Dictionary Builder Demo and finally build complex rules to extract nontrivial patterns from text with the Rules Builder Demo.

This time, we'll dive into a different area of the iKnow feature set: iFind. Where iKnow's core APIs are all about exploration and leveraging those results programmatically in applications and analytics, iFind is focused specifically on search scenarios in a pure SQL context. We'll be presenting a simple search portal implemented in Zen that showcases iFind's main features.

I was able to run the Cache terminal from the command prompt with the following command, in the namespace that I provided in the brackets:

cterm /console=cn_ap:ENSEMBLE[TEST_1]

But the command suddenly stopped opening the terminal in the correct namespace. It just opens it in the default namespace. I tried it with different namespaces or invalid namespaces, it always opens the terminal in the default namespace now.

I cannot figure out what is causing this behaviour.

Cache rendering of an old classic:

I created the Process to extract the required data from ADT message to a Dynamic Object. I wanted to send the JSON stream to EnsLib.File.PassthroughOperation operation and generate a file with the content of JSON stream.

Here are the codes for Process:

Hi,

this is a public announcement for the first release of Intersystems Cache Object-Relational Mapper in Python 3. Project's main repository is located at Github (healiseu/IntersystemsCacheORM).

About the project

CacheORM module is an enhanced OOP porting of Intersystems Cache-Python binding. There are three classes implemented:

• CacheClient This is the super class of CachePython module. It wraps two functions from intersys.pythonbind module pythonbind3.connection() and pythonbind3.database().

• CacheQuery A subclass of CacheClient that wraps methods and adds extra functionality in intersys.pythonbind.databaseand intersys.pythonbind.query classes

• CacheClass A subclass of CacheClient, that wraps methods and adds extra functionality in intersys.pythonbind.databaseand intersys.pythonbind.object classes

The intersys.pythonbind package is a Python C extension that provides Python application with transparent connectivity to the objects stored in the Caché database.

For practical reasons, it may be desirable that after a Linux server restart, the IRIS instance is automatically started.

Below you will find the steps to follow to automate the startup of IRIS during a reboot of the Linux server, via systemd :

1. Create an iris.service file in /etc/systemd/system/iris.service containing the following information

Stable Releases of the Atelier plugin are now available from the Eclipse Marketplace. Just search for Atelier on the Eclipse website (https://marketplace.eclipse.org) or - even better - in the Eclipse IDE.

This is an convenient way to install this plugin, because you no longer have to enter the URL.

Hi All, I need a documentation to configure csp in iis version 7, Any one have documentation regards?

RESTful API Call From Cache to Particle.io Electron

Tom Fitzgibbon | Multidata | 212-967-6700 x537 | tom@mul.com

Summary: Simple Blink Tutorial for Particle.io Electron Device from Cache

Electron device is a tiny ARM processor ($40-$60) that connects to Particle’s world wide leased 2G/3G network (about $3/mo) and runs off an included LiPo battery. Using Cache’s %Net.HttpRequest you can send/receive data, control hardware and read sensors.

Step by Step (about 1 hour)

1) Get the Electron from store.particle.io.

Imagine you want to see what InterSystems can give you in terms of data analytics. You studied the theory and now you want some practice. Fortunately, InterSystems provides a project that contains some good examples: Samples BI. Start with the README file, skipping anything associated with Docker, and go straight to the step-by-step installation. Launch a virtual instance, install IRIS there, follow the instructions for installing Samples BI, and then impress the boss with beautiful charts and tables. So far so good.

Inevitably, though, you’ll need to make changes.