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:

In this article we are going to show the results of the comparision between IRIS and Postgress when handling Astronomy data.

Introduction

Since the earliest days of human civilization we have been fascinated by the sky at night. There are so many stars! Everybody has dreamed about them and fantasized about life in other planets.

October 17, 2019

Anton Umnikov
Sr. Cloud Solutions Architect at InterSystems
AWS CSAA, GCP CACE

AWS Glue is a fully managed ETL (extract, transform, and load) service that makes it simple and cost-effective to categorize your data, clean it, enrich it, and move it reliably between various data stores.

Standard error logs in IRIS / Caché / Ensemble are written global ^ERRORS.
As this piece dates back some decades back to previous millennium its structure
is far from the typical SQL storage structures.

Hi folks!

Sometimes when we develop a mockup or PoC there is a need for a simple interface that will provide data in IRIS in JSON against SQL queries.

And recently I contributed a simple module that does exactly that:

accepts SQL string and returns the JSON.

How to install? Just call:

zpm "install sql-rest"

If you install it in a namespace X it will setup a /sql endpoint to your system that will accept POST requests with SQL string and will return the result for you for the data available in the namespace X.

Image search like Google's is a nice feature that wonder me - as almost anything related to image processing.

A few months ago, InterSystems released a preview for Python Embedded. As Python has a lot of libs for deal with image processing, I decided to start my own attemptive to play with a sort of image search - a much more modest version in deed :-)

Mapping Examples

Clearly if you have a fourth article in the trilogy you need to go for the money grab and write the fifth, so here it is!

Class Queries in InterSystems IRIS (and Cache, Ensemble, HealthShare) is a useful tool that separates SQL queries from Object Script code. Basically, it works like this: suppose that you want to use the same SQL query with different arguments in several different places.In this case you can avoid code duplication by declaring the query body as a class query and then calling this query by name. This approach is also convenient for custom queries, in which the task of obtaining the next row is defined by a developer. Sounds interesting? Then read on!

Keywords: IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle

Purpose

Recently I noticed a Kaggle dataset for the prediction of whether a Covid-19 patient will be admitted to ICU. It is a spreadsheet of 1925 encounter records of 231 columns of vital signs and observations, with the last column of "ICU" being 1 for Yes or 0 for No. The task is to predict whether a patient will be admitted to ICU based on known data.

In most cases, a global used by default storage has just 1 subscript level that represents the IDKEY.
For an index-globals we may see 2 or more subscript levels.
Arrays, or parent-child relationships or persistent classes extending a base data class
are examples where we see more levels. Though all these globals are quite uniform.

The Art of Mapping Globals to Classes (4 of 3)

The forth in the trilogy, anyone a Hitchhikers Guide to the Galaxy fan?

If you are looking to breathe new life into an old MUMPS application follow these steps to map your globals to classes and expose all that beautiful data to Objects and SQL.

If the above does not sound familiar to you please start at the beginning with the following:

The Art of Mapping Globals to Classes (1 of 3)

A More Industrial-Looking Global Storage Scheme

In the first article in this series, we looked at the entity–attribute–value (EAV) model in relational databases, and took a look at the pros and cons of storing those entities, attributes and values in tables. We learned that, despite the benefits of this approach in terms of flexibility, there are some real disadvantages, in particular a basic mismatch between the logical structure of the data and its physical storage, which causes various difficulties.

Introduction

In the first article in this series, we’ll take a look at the entity–attribute–value (EAV) model in relational databases to see how it’s used and what it’s good for. Then we'll compare the EAV model concepts to globals.

If you define a Persistent Class / Table the class compiler generates for you an appropriate Storage definition.
A different option is to define a SQL mapping for an already existing Global storage. This has been excellently
explained already in a different series of articles. The Art of Mapping Globals to Classes 1 of 3