#Indexing

TL;DR: This article demonstrates how to run GraphRAG-style hybrid retrieval—combining vector similarity, graph traversal, and full-text search—entirely within InterSystems IRIS using the iris-vector-graph package. We use a fraud detection scenario to show how graph patterns reveal what vector search alone would miss.

Why Fraud Detection Needs Graphs

Every year, businesses and consumers lose billions to fraud. In 2024 alone, consumers reported $12.5 billion lost—a 25% increase year over year. What makes modern fraud so difficult to detect is that fraudsters rarely work alone.

Hello!!!

Data migration often sounds like a simple "move data from A to B task" until you actually do it. In reality, it is a complex process that blends planning, validation, testing, and technical precision.

Over several projects where I handled data migration into a HIS which runs on IRIS (TrakCare), I realized that success comes from a mix of discipline and automation.

Here are a few points which I want to highlight.

1. Start with a Defined Data Format.

Before you even open your first file, make sure everyone, especially data providers, clearly understands the exact data format you expect. Defining templates early avoids unnecessary bank-and-forth and rework later. 

While Excel or CSV formats are common, I personally feel using a tab-delimited text file (.txt) for data upload is best. It's lightweight, consistent, and avoids issues with commas inside text fields. 

PatID   DOB Gender  AdmDate
10001   2000-01-02  M   2025-10-01
10002   1998-01-05  F   2025-10-05
10005   1980-08-23  M   2025-10-15

Make sure that the date formats given in the file is correct and constant throughout the file because all these files are usually converted from an Excel file and an Basic excel user might make mistakes while giving you the date formats wrong. Wrong date formats can irritate you while converting into horolog.

The Power of Indexing in Database Tables

When working with databases, most developers understand the concept of an index and why it's used: to speed up data retrieval. But the real impact of indexing often becomes clear only when you compare scenarios with and without it.

Do you Know what Happens Without an Index?
Imagine a table with three columns: Name, Age, and MobileNumber.

Now, consider this query:

If the Age column does not have an index, the database engine will:

• Check if the WHERE condition field has an index.
• If not, it will scan the entire table (a full table scan).

Hello. I need to transform a message

FROM:

MSH|^~\&|
SCH||61490||
PID|1||
RGS|1||1
AIS|1||
AIS|2||
AIS|3||
AIL|1||
AIP|1||

TO:

MSH|^~\&|
SCH||61490||
PID|1||
RGS|1||1
AIS|1||
AIL|1||
AIP|1||
RGS|1||1
AIS|2||
AIL|1||
AIP|1||
RGS|1||1
AIS|3||
AIL|1||
AIP|1||

The RGS, AIS, AIL and AIP are all under the RGS group. The one RGS segment that comes in will be copied across the group. If 3 AIS segments come in then I need 3 RGS groups, if 2 I need 2 RGS groups etc.

In my DTL (screenshot below) I have currently hardcoded the RGS index (1,2,3) but this will not be sufficient incase 4 AIS segments are sent in.

Hello community,

I wanted to share my experience about working on Large Data projects. Over the years, I have had the opportunity to handle massive patient data, payor data and transactional logs while working in an hospital industry. I have had the chance to build huge reports which had to be written using advanced logics fetching data across multiple tables whose indexing was not helping me write efficient code.

Here is what I have learned about managing large data efficiently.

Choosing the right data access method.

As we all here in the community are aware of, IRIS provides multiple ways to access data. Choosing the right method, depends on the requirement.

• Direct Global Access: Fastest for bulk read/write operations. For example, if i have to traverse through indexes and fetch patient data, I can loop through the globals to process millions of records. This will save a lot of time.

Set ToDate=+H
Set FromDate=+$H-1 For  Set FromDate=$O(^PatientD("Date",FromDate)) Quit:FromDate>ToDate  Do
. Set PatId="" For  Set PatId=$Order(^PatientD("Date",FromDate,PatID)) Quit:PatId=""  Do
. . Write $Get(^PatientD("Date",FromDate,PatID)),!

• Using SQL: Useful for reporting or analytical requirements, though slower for huge data sets.

This article describes a significant enhancement of how InterSystems IRIS deals with table statistics, a crucial element for IRIS SQL processing, in the 2025.2 release. We'll start with a brief refresher on what table statistics are, how they are used, and why we needed this enhancement. Then, we'll dive into the details of the new infrastructure for collecting and saving table statistics, after which we'll zoom in onto what the change means in practice for your applications. We'll end with a few additional notes on patterns enabled by the new model, and look forward to the follow-on phases of this initial delivery.

This will be a short article about Python dunder methods, also known as magic methods.

What are Dunder Methods?

Dunder methods are special methods in Python that start and end with double underscores (__). They allow you to define the behavior of your objects for built-in operations, such as addition, subtraction, string representation, and more.

Some common dunder methods include:

• __init__(self, ...): Called when an object is created.
  • Like our %OnNew method in ObjectScript.
• __str__(self): Called by the built-in function and print to represent the object as a string.

Hi Community,

Enjoy the new video on InterSystems Developers YouTube from our Tech Video Challenge:

⏯ Using Character Slice Index in InterSystems IRIS

Hello,

I have a class with a "Unique" index (pxfactidIndex) on a %Numeric property (pxfactid) (partially-edit code snippet below):

PropertyAs%Library.Numeric

I see the following odd behavior when counting how many records have that property set to null:

• The first query (17) returns the number of records in the table. The 2nd query (18) returns what I expect: all records have non-null values for that "pxfactid" property. However, when I run the 3rd query (19) which counts all records with non-null values in that field, I get a much smaller, unexpected, number.