Recently I have been posting some updates to our JSON capabilities and I am very glad that so many of you provided feedback. Today I would like to focus on another facet: Producing JSON with a SQL query.

Earlier in this series, we've presented four different demo applications for iKnow, illustrating how its unique bottom-up approach allows users to explore the concepts and context of their unstructured data and then leverage these insights to implement real-world use cases. We started small and simple with core exploration through the Knowledge Portal, then organized our records according to content with the Set Analysis Demo, organized our domain knowledge using the Dictionary Builder Demo and finally build complex rules to extract nontrivial patterns from text with the Rules Builder Demo.

This time, we'll dive into a different area of the iKnow feature set: iFind. Where iKnow's core APIs are all about exploration and leveraging those results programmatically in applications and analytics, iFind is focused specifically on search scenarios in a pure SQL context. We'll be presenting a simple search portal implemented in Zen that showcases iFind's main features.

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!

What is Unstructured Data?
Unstructured data refers to information lacking a predefined data model or organization. In contrast to structured data found in databases with clear structures (e.g., tables and fields), unstructured data lacks a fixed schema. This type of data includes text, images, videos, audio files, social media posts, emails, and more.

An interesting pattern around unique indices came up recently (in internal discussion re: isc.rest) and I'd like to highlight it for the community.

As a motivating use case: suppose you have a class representing a tree, where each node also has a name, and we want nodes to be unique by name and parent node. We want each root node to have a unique name too. A natural implementation would be:

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."

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.

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:

Quotes (1NF/2NF/3NF)^ru:

Every row-and-column intersection contains exactly one value from the applicable domain (and nothing else).
The same value can be atomic or non-atomic depending on the purpose of this value. For example, “4286” can be

• atomic, if its denotes “a credit card’s PIN code” (if it’s broken down or reshuffled, it is of no use any longer)
• non-atomic, if it’s just a “sequence of numbers” (the value still makes sense if broken down into several parts or reshuffled)

This article explores the standard methods of increasing the performance of SQL queries involving the following types of fields: string, date, simple list (in the $LB format), "list of <...>" and "array of <...>".

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())

See Part 1 here.

Part 2: Index Handling

Apache Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

And now it is possible to use with InterSystems IRIS as well.

An online demo is available and it uses IRIS Cloud SQL as a data source.

October 17, 2019

Anton Umnikov
Sr. Cloud Solutions Architect at InterSystems
AWS CSAA, GCP CACE

AWS Glue is a fully managed ETL (extract, transform, and load) service that makes it simple and cost-effective to categorize your data, clean it, enrich it, and move it reliably between various data stores.

What is %SQLRESTRICT

%SQLRESTRICT is a special %FILTER clause for use in MDX queries in InterSystems IRIS Business Intelligence. Since this function begins with %, it means this is a special MDX extension created by InterSystems. It allows users to insert an SQL statement that will be used to restrict the returned records in the MDX Result Set. This SQL statement must return a set of Source Record IDs to limit the results by. Please see the documentation for more information.

Why is this useful?

This is useful because there are often times users want to restrict the results in their MDX Result Set based on information that is not in their cubes. It may be the case that this information may not make sense to be in the cube. Other times this can be useful when there is a large set of values you want to restrict. As mentioned before, this is not a standard MDX function, it was created by InterSystems to handle cases were queries were not performing well or cases that were not easily solved by existing functions.