Article
· Feb 13, 2023 4m read
When to use Columnar Storage

With InterSystems IRIS 2022.2, we introduced Columnar Storage as a new option for persisting your IRIS SQL tables that can boost your analytical queries by an order of magnitude. The capability is marked as experimental in 2022.2 and 2022.3, but will "graduate" to a fully supported production capability in the upcoming 2023.1 release.

The product documentation and this introductory video, already describe the differences between row storage, still the default on IRIS and used throughout our customer base, and columnar table storage and provide high-level guidance on choosing the appropriate storage layout for your use case. In this article, we'll elaborate on this subject and share some recommendations based on industry-practice modelling principles, internal testing, and feedback from Early Access Program participants.

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I've asked a lot of questions leading up to this, so I wanted to share some of my progress.

The blue line represents the number of messages processed. The background color represents the average response time. You can see ticks for each hour (and bigger ticks for each day). Hovering over any point in the graph will show you the numbers for that period in time.

This is super useful for "at a glance" performance monitoring as well as establishing patterns in our utilization.

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Article
· May 25, 2017 2m read
The Interns are Coming!

The Data Platforms department here at InterSystems is gearing up for this year's crop of interns, and I for one am very excited to meet them all next week!

We've got folks from top technical colleges with diverse specialties from hard core engineers to pure computer scientists to mathematicians to business professionals. They come from countries around the world like Vietnam, China, and Finland and they all come with impressive backgrounds. We're sure they will do very well this summer.

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In this article, we will establish an encrypted JDBC connection between Tableau Desktop and InterSystems IRIS database using a JDBC driver.
While documentation on configuring TLS with Java clients covers all possible topics on establishing an encrypted JDBC connection, configuring it with Tableau might be a little bit tricky, so I decided to write it down.

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On the Latest GlobalSummit 2022, InterSystems Introduced Cloud SQL. So, you may have lightweight InterSystems IRIS with access to SQL only. Well, what if you would still need some Interoperability features in the cloud as well? There are various solutions on the market nowadays, which offer a bunch of integration adapters out of the box and can be extended with support from the community. Some time ago, I've implemented an adapter for the Node-RED project, which can be deployed manually everywhere you want. Now I would like to introduce a new integration with my recent discovery, n8n.io

Banner image

n8n.io is a workflow automation platform, that supports over 200 different integrations out of the box and from a community, and now including InterSystems IRIS.

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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:

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This is the third article in our short series around innovations in IRIS SQL that deliver a more adaptive, high-performance experience for analysts and applications querying relational data on IRIS. It may be the last article in this series for 2021.2, but we have several more enhancements lined up in this area. In this article, we'll dig a little deeper into additional table statistics we're starting to gather in this release: Histograms

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Case description

Let’s imagine that you are a Python developer or have a well-trained team specialized in Python, but the deadline you got to analyze some data in IRIS is tight. Of course, InterSystems offers many tools for all kinds of analyses and treatments. However, in the given scenario, it is better to get the job done using the good old Pandas and leave the IRIS for another time.

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Article
· Feb 2, 2016 1m read
Creating an IDKEY with a chosen name

What do you do if you want to have the ID field have a meaningful name for your application?

Sometimes it comes to pass that when you're making a new table that you want to have the unique row identifier (a.k.a. IDKEY) to be a field that has a name that is meaningful for your data. Moreover, sometimes you want to set this value directly. Caché fully supports this functionality and it works Suppose you have a class Test.Kyle. The data will be stored like so:

^Test.Kyle(IDKEY)=$LB("",Field1,Field2,...,Fieldn)

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So I know it's been a while, and I hate to let my adoring fans down... just not enough to actually start writing again. But the wait is over and I'm back! Now bask in my beautiful ginger words!

For this series, I am going to look at some common problems we see in the WRC and discuss some common solutions. Of course, even if you find a solution here, you are always welcome to call in and expression you gratitude, or just hear my voice!

This week's common problem: "My query returns no data."

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Our team is reworking an application to use REST services that use the same database as our current ZEN application. One of the new REST endpoints uses a query that ran very slowly when first implemented. After some analysis, we found that an index on one of the fields in the table greatly improved performance (a query that took 35 seconds was now taking a fraction of a second).

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Let's say we have two serial classes, one as a property of another:

Class test.Serial Extends %SerialObject
{
Property Serial2 As test.Serial2;
}

Class test.Serial2 Extends %SerialObject
{
Property Property As %String;
}

And a persistent class, that has a property of test.Serial type:

Class test.Persistent Extends %Persistent
{

Property Datatype As %String;

Property Serial As test.Serial;

}

So it's a serial, inside a serial, inside a persistent object.

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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.

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Article
· Jun 22, 2023 1m read
Countermeasures against SQL injection

InterSystems FAQ rubric

Countermeasures against SQL injection have been published on various websites, but we believe that it is possible to prevent SQL injection in applications using InterSystems SQL as well as other RDBMS by implementing these countermeasures appropriately. In addition, InterSystems Data Platform (hereinafter referred to as IRIS) incorporates several measures that make SQL injection more difficult than general RDBMS.

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Introduction

This article is intended to be a simple tutorial on how to create ODBC connections and working with them, since I found starting with them a little bit confused, but I had amazing people to take my hand and walk me through it, and I think everyone deserves that kind of help too.
I'm going to divide each little part in sections, so feel free to jump to the one you feel the need to, although I recommend reading everything.

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Article
· Mar 29, 2023 1m read
Named Parameter In SQL with Python

Quick Tips: Total Productive Maintenance

Named parameters can be achieved with SQLAlchemy :

from sqlalchemy import create_engine, text,types,engine

_engine = create_engine('iris+emb:///')

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

or with native api

from sqlalchemy import create_engine, text,types,engine

# set URL for SQLAlchemy
url = engine.url.URL.create('iris', username='SuperUser', password='SYS', host='localhost', port=33782, database='FHIRSERVER')

_engine = create_engine(url)

with _engine.connect() as conn:
    rs = conn.execute(text("select :some_private_name"), {"some_private_name": 1})
    print(rs.all())

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Hey developers!

Sometimes we need to insert or refer to the data of classes directly in globals.

And maybe a lot of you expect that data structure of global with records is:

^Sample.Person(Id)=$listbuild("",col1,col2,...,coln).

And this article is a heads up, that this is not always true, don't expect it as granted!

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One of the reasons why I love Cache and Iris is that not only you can do anything you can imagine, also you can do it in a lot of different ways!!.

Imagine that you have an integration running with IRIS connected by ODBC you probably only run SQL queries but you can also create stored procedures and inside write the code to do everything you can imagine.

I'm going to give you some examples but the limit is your imagination!!

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Presenter: Anton Umnikov
Task: Run SQL queries quickly on huge amounts of data
Approach: Use a shared-nothing architecture to leverage a cluster of small, cost-effective servers

Explains how a shared nothing architecture allows you to leverage a cluster of small, costeffective servers to serve query results that would have taken much longer on a single, big and expensive box. This brings affordable horizontal scalability.

Content related to this session, including slides, video and additional learning content can be found here.

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Presenter: Anton Umnikov
Task: Identify your slowest SQL queries and tune them for better performance
Approach: Use InterSystems’ query profiling and analysis tools. Discuss how system configuration can affect performance

This session will show you how you identify the weakest link in your application SQL and introduce you to the fine art of tuning those queries. To do this we will take a look at InterSystems query profiling and analysis tools, as well as how system configuration can impact SQL performance.

Problem: Obscurity on how our SQL engine works

Content related to this session, including slides, video and additional learning content can be found here.

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Article
· Feb 22 4m read
IRIS 2024.1 Preview - New Feature

There is an interesting new feature in the recently announced 2024.1 preview, JSON_TABLE. JSON_TABLE is one of a family of functions introduced by the 2016 version of the SQL Standard (ISO Standard, published in early 2017). It allows for JSON values to be mapped to columns and queried using SQL. JSON_TABLE is valid in the FROM clause of some SQL statements.

The syntax of JSON_TABLE is quite large, allowing for exceptional conditions where the provided JSON values don't match expectations, nested structures and so on.

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Article
· Jan 28, 2022 2m read
Embedded SQL Bug and Workaround

We recently encountered an Embedded SQL issue while upgrading to IRIS 2021.1, and thought the issue and workaround might be interesting to share.

Key takeaway: Host variables in an ORDER BY clause of an embedded SQL query that is inside of a method don't work as expected. IRIS versions starting with 2020.1 are affected. As a workaround, add the host variable to the Method's PublicList list and "new" them so the embedded query has access to them.

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InterSystems FAQ rubric

It can be retrieved using the schema INFORMATION_SCHEMA.

INFORMATION_SCHEMA is a system schema and is not displayed by default in the SQL menu of the Management Portal.

The method to display it is as follows.

  1. Open Management Portal → System Explorer → SQL menu.
  2. Check "System" on the left of the schema drop-down.
  3. Select INFORMATION_SCHEMA from the schema dropdown.

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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.

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