Hi Developers!

This is the second post on the resources for Developers. This part is about Open Exchange

Using Open Exchange to Learn InterSystems

InterSystems Open Exchange is a applications gallery of tools, connectors, and libraries which InterSystems Developers submit to share the experience, approaches and do business. All the applications are either built with InterSystems data platforms or are intended to use for development with InterSystems data platforms.

If you are a beginner developer you can take a look at applications in Technology Example category. All the applications in this category come with open source code repositories, so you are able to run the samples and examples in a docker container with IRIS on your laptop or in the cloud IRIS sandbox. Examples:

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Recently I wanted to get a list of all cached queries and their texts. Here's how to do that.

First create an SQL Procedure returning Cache Query text from a Cached Query routine name:

Class test.CQ
{

/// SELECT test.CQ_GetText()
ClassMethod GetText(routine As %String) As %String [ CodeMode = expression, SqlProc ]
{
##class(%SQLCatalog).GetCachedQueryInfo(routine)
}

}

And after that you can execute this query:

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InterSystems FAQ rubric

Data for InterSystems products (table row data, object instance data) is stored in global variables.
The data size of each global can be obtained by clicking the properties of the global you want to view from the Management Portal > System > Configuration > Local Database > Globals page, and then clicking the Calculate Size button on the Global Attributes page that appears.
To display the data sizes of globals in a namespace, you can call ^%GSIZE utility on the terminal.

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Hi Developers!

Recently I was asked, “How can a beginner in InterSystems technologies learn from InterSystems Developers community content to improve his developer skills”?

This is a really good question. It has several answers so I decided to write the post with the hope it could be useful for developers.

So! How to learn Intersystems Data Platforms(IRIS, IRIS for Health) from InterSystems Developers community content if you are a beginner?

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Hi Community!

It's that time of year again—the time of the Global Summit! All the Developer Ecosystem teams, in general, and the Developer Community team, in particular, are doing their best to bring even more new, interesting people into our midst!

We had this beautiful booth ready on Sunday to welcome everyone when the Summit officially started:

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For some time I have been planning to do some type of proof of concept with the Workflow functionality, which, like so many other functionalities present in IRIS, tends to go quite unnoticed by our clients (and for which I say mea culpa). That's why I decided a few days ago to develop an example of how to configure and exploit this functionality by connecting it with a user interface developed in Angular.

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InterSystems FAQ rubric

If you want to run an OS executable file, command, or a program created within an InterSystems product when the InterSystems product starts, write the processing in the SYSTEM^%ZSTART routine. (The %ZSTART routine is created in the %SYS namespace).

Before you write any code in SYSTEM^%ZSTART, make sure that it works properly under all conditions.

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We're excited to continue to roll out new features to InterSystems IRIS Cloud SQL, such as the new Vector Search capability that was first released with InterSystems IRIS 2024.1. Cloud SQL is a cloud service that offers exactly that: SQL access in the cloud. That means you'll be using industry-standard driver technologies such as JDBC, ODBC, and DB-API to connect to this service and access your data. The documentation describes in proper detail how to configure the important driver-level settings, but doesn't cover specific third-party tools as - as you can imagine - there's an infinite number of them.

In this article, we'll complement that reference documentation with more detailed steps for a popular third-party data visualization tool that several of our customers use to access IRIS-based data: Microsoft Power BI.

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Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.

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When developing a new Interoperability Production, it is quite natural that settings are initially added in the Production.

However, as soon as you want to move the Production from development to a test or staging environment, it becomes clear that some settings like HTTP Servers, IP addresses and/or ports need to be changed. In order to avoid these settings being overwritten during a redeployment later on, it is essential that you move these settings from the Production to the System Default settings.

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Data Analysis

This is the sequel to Data Collection. If you have not had a chance to go through and install that you should first do that.

What is provided here is the analysis for the collection of that data that was collected earlier.

In much the same way as was done in that repository you will need to import the xml that makes up this repository.

Starting at the topmost level there is a task:

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In our previous article, we have explored the most common Kubernetes components:

  • We started with the pods and the services we needed to communicate with each other.
  • Then, we examined the Ingress component used to Route traffic into the cluster.
  • We also skimmed through an external configuration using ConfigMaps and Secrets.
  • Afterward, we analyzed Data persistence with the help of Volumes.
  • Finally, we took a quick look at pod blueprints with such replicating mechanisms as Deployments and StatefulSets (the latter is employed specifically for such stateful applications as databases).

In this article, we will explore Kubernetes architecture and configuration.

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Columnar storage is one of the newer offers provided by InterSystems IRIS. Unlike traditional row-based storage, it optimizes query processing by storing data in columns rather than rows, enabling faster access and retrieval of relevant information.

A couple of articles have been written on when it should be used to give a system the biggest boost, how to create tables like that using SQL

CREATE TABLE table (column1 type1, column2 type2, column3 type3) WITH STORAGETYPE = COLUMNAR  -- ex 1
CREATE TABLE table (column1 type1, column2 type2, column3 type3 WITH STORAGETYPE = COLUMNAR)  -- ex 2

and even the performance tests.

As we all know, InterSystems IRIS is a multi-model DBMS and it gives seamless access to the same data using relational and object access. So the former is covered in other articles, but what about the latter?

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Translated from the Spanish Community Article Contest.

Following the latest programming contest on OEX I had some surprising observation.
There were almost exclusive applications based on AI in combination with pre-cooked Py modules.
But digging deeper, all examples used the same technical pieces of IRIS.

Seen from point of view of IRIS it was pretty much the same whether searching for text
or searching for images or other pattern. It ended in almost exchangeable methods.

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image

Hi Community

In this article, I will introduce my application irisChatGPT which is built on LangChain Framework.

First of all, let us have a brief overview of the framework.

The entire world is talking about ChatGPT and how Large Language Models(LLMs) have become so powerful and has been performing beyond expectations, giving human-like conversations. This is just the beginning of how this can be applied to every enterprise and every domain!

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InterSystems FAQ rubric

To disable the timeout, set the query timeout to disabled in the DSN settings:

Windows Control Panel > Administrative Tools > Data Sources (ODBC) > System DSN configuration

If you check Disable query timeout, the timeout will be disabled.

If you want to change it on the application side, you can set it at the ODBC API level.

Set the SQL_ATTR_QUERY_TIMEOUT attribute when calling the ODBC SQLSetStmtAttr function before connecting to the data source.

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Article
· May 24 15m read
VIP in GCP

If you're running IRIS in a mirrored configuration for HA in GCP, the question of providing a Mirror VIP (Virtual IP) becomes relevant. Virtual IP offers a way for downstream systems to interact with IRIS using one IP address. Even when a failover happens, downstream systems can reconnect to the same IP address and continue working.

The main issue, when deploying to GCP, is that an IRIS VIP has a requirement of IRIS being essentially a network admin, per the docs.

To get HA, IRIS mirror members must be deployed to different availability zones in one subnet (which is possible in GCP as subnets always span the entire region). One of the solutions might be load balancers, but they, of course, cost extra, and you need to administrate them.

In this article, I would like to provide a way to configure a Mirror VIP without using Load Balancers suggested in most other GCP reference architectures.

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We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

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