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#SQL

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SQL is a standard language for storing, manipulating and retrieving data in relational databases.

The related package avoids adding %JSONAdaptor to each class but uses instead
SQL functions JSON_OBJECT() to create my JSON objects. With this approach, you can
add JSON to any class - even deployed ones - without any need for change or recompiling.

The trigger was the Export of M:N relationships as JSON objects or arrays.

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Earlier this year I announced availability of a VS Code extension for coding in ObjectScript, Embedded Python or SQL using the notebook paradigm popularized by Jupyter. Today I published a maintenance release to correct a "getting started" problem.

Here's a video of the installation steps from the extension's README:

Why not try it for yourself?

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Nowadays so much noise around LLM, AI, and so on. Vector databases are kind of a part of it, and already many different realizations for the support in the world outside of IRIS.

Why Vector?

  • Similarity Search: Vectors allow for efficient similarity search, such as finding the most similar items or documents in a dataset. Traditional relational databases are designed for exact match searches, which are not suitable for tasks like image or text similarity search.
  • Flexibility: Vector representations are versatile and can be derived from various data types, such as text (via embeddings like Word2Vec, BERT), images (via deep learning models), and more.
  • Cross-Modal Searches: Vectors enable searching across different data modalities. For instance, given a vector representation of an image, one can search for similar images or related texts in a multimodal database.

And many other reasons.

So, for this pyhon contest, I decided to try to implement this support. And unfortunately I did not manage to finish it in time, below I'll explain why.

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Enhanced Password Management: Edit Passwords Seamlessly

In the ever-evolving landscape of digital security, robust password management tools have become indispensable. Our password management application, designed to simplify and secure your online life, now comes with an enhanced feature – the ability to edit passwords with ease.

Why is this feature a game-changer?

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I need to run a SQL query and use the output to map PV1 7.1. The query is :

SELECT ID
FROM TestTable
WHERE ProviderName = 'TEST,PROVIDER' AND IDType= 'BPI'

When I run this query with the 'TEST PROVIDER' I do pull the ID in question but I can't figure out how to do it from the DTL given that there are various providers sent in PV 1 7 . Any assistance will be greatly appreciated.

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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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Currently, the SQL privileges (SELECT, INSERT, UPDATE, DELETE) are managed at the tables level, which can be very tedious when you have to administer many roles in an organization, and need to keep them sync with a constantly evolving data models.
By managing privileges at the schemas level, will allow to give SELECT and other DML privileges to *all* or *several schemas* to a role|user, fixing the need to manually synchronize the new tables|views to the roles.

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Hi all,
I am trying to execute a query like the below code.
set statement = ##class(%ResultSet).%New("some_class:query_method"). // here query method is empty and with rowspec some columname

statement.Execute(param1)

I want to fetch data type of column value returned from above. eg - Name - VARCHAR, amount - INTEGER etc.
How can I get it. Or if not possible directly. Is there any other way to validate or get datatype of values returned. Line we have type() in python3

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on red hat, but I would also be interested in a wider answer.

after running a benchmark for 40 minutes, I have been asked if any rollbacks occurred in that time. Rollbacks from SQL or objects.

The application does not record this, so I am looking for a system level record.

The journal entries do the necessary reverse sets and commit just like any transaction. So i don't think i can detect them there.

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In today's landscape, enterprises have grown substantially in scale, amassing vast amounts of data. This data is collected from a plethora of sources including different applications, databases, and other channels. Given the diversity and volume of this data, it's only logical for these enterprises to seek a deeper understanding of what their data entails. Some of the data can be stored in IRIS, and it can be reasonable to be able to add this data to a data lake too.

The Internet now offers many different tools for such tasks, that do not yet support IRIS, but it's achievable.

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The program below works perfectly when I call it directly from the Terminal, however when I call it from within a CSP it does not work (It does not do the SELECT).

In the USER namespace, the program works both in the Terminal and on the CSP , but in another namespace it only works when called directly in the Terminal.

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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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Is it planned that LOAD DATA takes into account several DATE/DATETIME formats with, for example, a parameter indicating the format used in the source data?

example :

LOAD DATA .../...
USING
{
  "from": {
    "file": {
       "dateformat": "DD/MM/YYYY"
    }
  }
}
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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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