In a customer project I was asked how you can keep track of database changes: Who changed what at which date and time. Goal was to track insert, update and delete for both SQL and object access.
This is the table that I created to keep the Change Log:
Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.
InterSystems Certification is developing a certification exam for InterSystems IRIS SQL specialists, and if you match the exam candidate description given below, we would like you to beta test the exam. The exam will be available for beta testing on June 9 - 12, 2024 at InterSystems Global Summit 2024, but only for Summit registrants (visit this page to learn more about Certification at GS24). Beta testing will open for all other interested beta testers on June 24, 2024. However, interested beta testers should sign up now by emailing certification@intersystems.com (please let us know if you will be beta testing at Global Summit or in our online proctored environment). The beta testing must be completed by August 2, 2024.
We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.
The TIMESTAMP type corresponds to the %Library.TimeStamp data type (=%TimeStamp) in InterSystems products, and the format is YYYY-MM-DD HH:MM:SS.nnnnnnnnn.
If you want to change the precision after the decimal point, set it using the following method.
This is a detailed, candid walkthrough of the IRIS AI Studio platform. I speak out loud on my thoughts while trying different examples, some of which fail to deliver expected results - which I believe is a need for such a platform to explore different models, configurations and limitations. This will be helpful if you're interested in how to build 'Chat with PDF' or data recommendation systems using IRIS DB and LLM models.
In the previous article, we saw in detail about Connectors, that let user upload their file and get it converted into embeddings and store it to IRIS DB. In this article, we'll explore different retrieval options that IRIS AI Studio offers - Semantic Search, Chat, Recommender and Similarity.
You need to install the application first. If not installed, please refer to the previous article
Application demonstration
After successfully running the iris image vector search application, some data needs to be stored to support image retrieval as it is not initialized in the library.
In this article, I will introduce my application iris-VectorLab along with step by step guide to performing vector operations.
IRIS-VectorLab is a web application that demonstrates the functionality of Vector Search with the help of embedded python. It leverages the functionality of the Python framework SentenceTransformers for state-of-the-art sentence embeddings.
Application Features
Text to Embeddings Translation.
VECTOR-typed Data Insertion.
View Vector Data
Perform Vector Search by using VECTOR_DOT_PRODUCT and VECTOR_COSINE functions.
Demonstrate the difference between normal and vector search
HuggingFace Text generation with the help of GPT2 LLM (Large Language Model) model and Hugging Face pipeline
The basic idea is to use Vectors in the mathematical sense. I used geographic coordinates. These are of course only 2-dimensional but much easier to follow as vectors in text analysis with >200 dimensions.
Did you know that you can get JSON data directly from your SQL tables?
Let me introduce you to 2 useful SQL functions that are used to retrieve JSON data from SQL queries - JSON_ARRAY and JSON_OBJECT. You can use those functions in the SELECT statement with other types of select items, and they can be specified in other locations where an SQL function can be used, such as in a WHERE clause
The JSON_ARRAY function takes a comma-separated list of expressions and returns a JSON array containing those values.
Building my tech. example provided me with a bunch of findings htt I want to share. The first vectors I touched appeared with text analysis and more than 200 dimensions. I have to confess that I feel well with Einstein's 4 dimensional world. 7 to 15 dimensions populating the String Theory are somewhat across the border. But 200 and more is definitely far beyond my mathematical horizon.
Imagine the scene. You are working happily at Widgets Direct, the internet's premier retailer of Widgets and Widget Accessories. Your boss has some devastating news, some customers might not be fully happy with their widgets, and we need a helpdesk application to track these complaints. To makes things interesting, he wants this with a very small code footprint and challenges you to deliver an application in less than 150 lines of code using InterSystems IRIS. Is this even possible?
I'm executing the same query with same column name but in different case. An unique cached query generated while query executed first time. The query preparser only normalize the keywords and send to the SQL engine generates the Hash. Eventually use the cached query next use.
Now my question, The hash values are same for both of the queries. Then why it creates two cached queries.
Query1: select * from MyLearn.Test where Name['Kev1'
Query2: select * from MyLearn.Test where NamE['Kev1'
The InterSystems IRIS has a series of facilitators to capture, persist, interoperate, and generate analytical information from data in XML format. This article will demonstrate how to do the following:
Capture XML (via a file in our example);
Process the data captured in interoperability;
Persist XML in persistent entities/tables;
Create analytical views for the captured XML data.
Capture XML data
The InterSystems IRIS has many built-in adapters to capture data, including the next ones:
I have a function that may end up being called from a number of transformations at the same time, and within the function there's some Embedded SQL to first check if a local table has an entry, and then adds the entry if it doesn't exist.
To prevent a race condition where the function is called by two transformations and they both end up attempting to insert the same value, I'm looking to use the table hint "WITH TABLOCK" on the insert, but this seems to be failing the syntax checks within vscode.
I was struggling with a procedure that was meant to receive a string and use it as a filter, I've found that since I want the procedure to do some data transformation and return a dataset, I needed to use objectScript language.
I've created the procedure using the SQL GUI in the portal, and everything works fine when calling the procedure from the SQL GUI but not through a JDBC connection here is the call "call spPatientOS('2024-04-07T12:35:32Z')"
I'm currently running into a very weird issue to where I am trying to connect with a 64 bit version of SQL Server Management Studio (SSMS) to a HealthShare instance. I have created a System DSN using the Drivers (image below) that were downloaded with the Client version of the install and I'm able to successfully connect using my credentials.