#SQL

GmOwl is a solution that offers an organized and engaging learning platform. It was developed to cater to the increasing need, for learning tools providing a versatile quiz environment that meets users requirements.

The main objective of GmOwl is to deliver an user experience for individuals participating in quizzes while giving administrators comprehensive control, over content and user engagement.

GmOwl uses Java EE with MVC template, and the InterSystems IRIS database is used to store data. The InterSystems JDBC Driver is used to connect to the database.

Hello community! I have to work with queries using all kinds of methods like embedded sql and class queries. But my favorite is dynamic sql, simply because of how easy it is to manipulate them at runtime. The downside to writing a lot of these is the maintenance of the code and interacting with the output in a meaningful way.

Since Caché 2017 the SQL engine has included new set of statistics. These record the number of times a query is executed and the time it takes to run.

Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

• Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
• Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
• Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

In the good old days (tm) determining the size of the data, streams, and indices for a class/table was easy - you just ran %GSIZE and check D, S, and I globals respectively.

However, nowadays sharding, optimized global names, and indices in separate globals produce %GSIZE output looking like this:

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.

Hi Community,
In this article, I will introduce my application iris-mlm-explainer

In this article I will demonstrate the following :

• Update ReferencesRange(OBX:7) against ObservationIdentifier(OBX:3.1)[TestCode] from database by using custom utility function
• Update Abnormal Flag(OBX:8) against ObservationIdentifier(OBX:3.1)[TestCode] and ObservationValue(OBX:5)[Result] from database utility function
• Route Message based on Abnormal Flag(OBX:8)

Below is the primary and transformed HL7 2.5 ORU_R01 message:

The last days I've work with the great new feature: LOAD DATA With this post I would like to share my first experiences with you. The following points do not contain any order or other evaluation. These are only things that I noticed when using the LOAD DATA command. It should also be noted that these points are based on the IRIS Version 2021.2.0.617 which is a preview release. So it may be that my observations do not apply to newer IRIS versions.

For the upcoming Python contest, I would like to make a small demo, on how to create a simple REST application using Python, which will use IRIS as a database. Using this tools

• FastAPI framework, high performance, easy to learn, fast to code, ready for production
• SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL
• Alembic is a lightweight database migration tool for usage with the SQLAlchemy Database Toolkit for Python.
• Uvicorn is an ASGI web server implementation for Python.

Introduction

This is a simple tutorial on the quickest way I found to create a sample database for any purposes such as testing, making samples for tutorials, etc.

Creating a namespace

1. Open the terminal
2. Write the command "D $SYSTEM.SQL.Shell()"
3. Write "CREATE DATABASE " and the name you want for your namespace.

Now you have a new namespace in a faster way than creating it from the Management Portal - which of course offers way more configuration options.

It is often necessary to sort the results of a query on a string field containing a combination of alphabetic and numeric characters. In cases like this the default string collation may not always return the data in the expected sequence.

An example of this may be where a select from Samples.Person should order the results by the street address, but firstly ordered by the street number part as numeric, and then by the street name.

The default query will return the results as follows:

IRIS External Table is an InterSystems Community Open Source Project, that allows you to use files, stored in the local file system and cloud object storage such as AWS S3 as SQL Tables.

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: