David Underhill · Jul 12, 2019 2m read
Basic Database Metrics example

This is a self contained class that can be run from the Intersystems Task Scheduler which records peak usage details for databases and licenses built up throughout the day and retaining 30 days history.

To schedule the task to run every hour:

d ##class(Metrics.Task).Schedule()

You can also specify your own start time, stop time, and run interval:

d ##class(Metrics.Task).Schedule(startTime, stopTime, intervalMins)

Metrics are stored in ^Metrics in the namespace that the class resides in/is run from.

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Hello everyone, I’m a French student that just arrived in Prague for an academical exchange for my fifth year of engineering school and here is my participation in the interop contest.

I hadn’t much time to code since I was moving from France to Prague and I’m participating alone, so I decided to make a project that’s more like a template rather than an application.

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In this GitHub we gather information from a csv, use a DataTransformation to make it into a FHIR object and then, save that information to a FHIR server all that using only Python.

The objective is to show how easy it is to manipulate data into the output we want, here a FHIR Bundle, in the IRIS full Python framework.

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In this GitHub we fine tune a bert model from HuggingFace on review data like Yelp reviews.

The objective of this GitHub is to simulate a simple use case of Machine Learning in IRIS :
We have an IRIS Operation that, on command, can fetch data from the IRIS DataBase to train an existing model in local, then if the new model is better, the user can override the old one with the new one.
That way, every x days, if the DataBase has been extended by the users for example, you can train the model on the new data or on all the data and choose to keep or let go this new model.

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Iryna Mykhailova · Aug 2, 2022 8m read
Data models in InterSystems IRIS

Before we start talking about databases and different data models that exist, first we'd better talk about what a database is and how to use it.

A database is an organized collection of data stored and accessed electronically. It is used to store and retrieve structured, semi-structured, or raw data which is often related to a theme or activity.

At the heart of every database lies at least one model used to describe its data. And depending on the model it is based on, a database may have slightly different characteristics and store different types of data.

To write, retrieve, modify, sort, transform or print the information from the database, a software called Database Management System (DBMS) is used.

The size, capacity, and performance of databases and their respective DBMS have increased by several orders of magnitude. It has been made possible by technological advances in various areas, such as processors, computer memory, computer storage, and computer networks. In general, the development of database technology can be divided into four generations based on the data models or structure: navigational, relational, object and post-relational.

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This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.

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Hi Community,

This post is a introduction of my openexchange iris-python-apps application. Build by using Embedded Python and Python Flask Web Framework.
Application also demonstrates some of the Python functionalities like Data Science, Data Plotting, Data Visualization and QR Code generation.



  • Responsive bootstrap IRIS Dashboard

  • View dashboard details along with interoperability events log and messages.

  • Use of Python plotting from IRIS

  • Use of Jupyter Notebook

  • Introduction to Data Science, Data Plotting and Data Visualization.

  • QR Code generator from python.

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In this article I will explain the usage of %SQL_Diag.Result and %SQL_Diag.Message table along with all-new LOAD DATA functionality.

It is recommended to go through LOAD DATA documentation first.

After successful operation LOAD DATA insert one record in %SQL_Diag.Result table and details are inserted in %SQL_Diag.Message table

Below is the basic command when table is already created and source file does not contain header row.

LOAD DATA FROM FILE 'C://TEMP/mydata.txt' 
INTO MyTable

The file name must include a .txt or .csv (comma-separated values) suffix and both source and target have the same sequence of data columns.

Loading from File Source: Header

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Astronomers’ tools

5 years ago, on December 19, 2013, the ESA launched an orbital telescope called Gaia. Learn more about the Gaia mission on the official website of the European Space Agency or in the article by Vitaly Egorov (Billion pixels for a billion stars).

However, few people know what technology the agency chose for storing and processing the data collected by Gaia. Two years before the launch, in 2011, the developers were considering a number of candidates (see “Astrostatistics and Data Mining” by Luis Manuel Sarro, Laurent Eyer, William O’Mullane, Joris De Ridder, pp. 111-112):

Comparing the technologies side-by-side produced the following results (source):

Technology Time
DB2 13min55s
PostgreSQL 8 14min50s
PostgreSQL 9 6min50s
Hadoop 3min37s
Cassandra 3min37s
Caché 2min25s

The first four will probably sound familiar even to schoolchildren. But what is Caché XEP?

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Evgeniy Potapov · Jan 14, 2022 1m read
Real Webserver Logs Dataset

I'm happy to share with the community a web server log dataset from our longtime customer, an operating company.

Their webserver operates on Apache webserver and contains data which can be useful to analyse a load and search engines activity.

After installing the project, you will get the data for a few months that can show a typical load and activity of clients, robots and also you can see how it depends on day of week, holidays and time of a day.

The Cube is also included in package.

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Rob Tweed · Dec 20, 2021 1m read
Holiday Reading: What Lies Beneath!

For those of you who might be new to IRIS, and even those who have used Cache or IRIS for some time but want to explore beyond its usually-assumed boundaries and practices, you might want to dive into this detailed exploration of the database engine that is at its heart, and discover just what you can really do with it, going way beyond what InterSystems have done with it for you.

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to dismount/mount a database, use Dismount() and Mount() methods in SYS.Database class available in %SYS namespace.
NB: the database ID is its Directory

You'll find some examples of how to dismount/mount and check if a database is mounted (Mounted=1) or not (Mounted=0), and quickly see all the attributes of a database (via zwrite)

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Guillaume Rongier · Apr 9, 2019 3m read
IRIS/Ensemble as an ETL

IRIS and Ensemble are designed to act as an ESB/EAI. This mean they are build to process lots of small messages.

But some times, in real life we have to use them as ETL. The down side is not that they can't do so, but it can take a long time to process millions of row at once.

To improve performance, I have created a new SQLOutboundAdaptor who only works with JDBC.


Extend EnsLib.SQL.OutboundAdapter to add batch batch and fetch support on JDBC connection.

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At the heart of IRIS and Cache is a very interesting database architecture that we, at M/Gateway Developments, refer to as "Global Storage". If you ever wanted to know more about the fundamentals and capabilities of this underlying database, you might want to read a major analysis we've put together:

Amongst other things you'll discover that:

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Eduardo Anglada · May 11, 2021 8m read
IRIS in Astronomy

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


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.

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Tony Pepper · May 25, 2016 5m read
Random Read IO Storage Performance Tool

New Tool Available

Please see PerfTools IO Test Suite for a later version of the Random Read IO tool.


This tool is used to generate random read Input/Output (IO) from within the database. The goal of this tool is to drive as many jobs as possible to achieve target IOPS and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis.

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