Hi everyone.

This is a full example how to use a %ScrollableResultSet for results pagination using %DynamicQuery:SQL and build a JSON response including page details.

Feel free to use, share, comment or improve it.

Kind Regards

Hi developers!

As you know InterSystems IRIS besides globals, object, document and XML data-models also support relational where SQL is expected as a language to deal with the data.

And as in other relational DBMS InterSystems IRIS has its own dialect.

I start this post to support an SQL cheatsheet and invite you to share your favorites - I'll update the content upon incoming comments.

Here we go!

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.

Let me introduce my new project, which is irissqlcli, REPL (Read-Eval-Print Loop) for InterSystems IRIS SQL

• Syntax Highlighting
• Suggestions (tables, functions)
• 20+ output formats
• stdin support
• Output to files

Install it with pip

pip install irissqlcli

Or run with docker

docker run -it caretdev/irissqlcli irissqlcli iris://_SYSTEM:SYS@host.docker.internal:1972/USER

Connect to IRIS

$ irissqlcli iris://_SYSTEM@localhost:1972/USER -W
Password for _SYSTEM:
Server:  InterSystems IRIS Version 2022.3.0.606 xDBC Protocol Version 65
Version: 0.1.0
[SQL]_SYSTEM@localhost:USER> select $ZVERSION
+---------------------------------------------------------------------------------------------------------+
| Expression_1                                                                                            |
+---------------------------------------------------------------------------------------------------------+
| IRIS for UNIX (Ubuntu Server LTS for ARM64 Containers) 2022.3 (Build 606U) Mon Jan 30 2023 09:05:12 EST |
+---------------------------------------------------------------------------------------------------------+
1 row in set
Time: 0.063s
[SQL]_SYSTEM@localhost:USER> help
+----------+-------------------+------------------------------------------------------------+
| Command  | Shortcut          | Description                                                |
+----------+-------------------+------------------------------------------------------------+
| .exit    | \q                | Exit.                                                      |
| .mode    | \T                | Change the table format used to output results.            |
| .once    | \o [-o] filename  | Append next result to an output file (overwrite using -o). |
| .schemas | \ds               | List schemas.                                              |
| .tables  | \dt [schema]      | List tables.                                               |
| \e       | \e                | Edit command with editor (uses $EDITOR).                   |
| help     | \?                | Show this help.                                            |
| nopager  | \n                | Disable pager, print to stdout.                            |
| notee    | notee             | Stop writing results to an output file.                    |
| pager    | \P [command]      | Set PAGER. Print the query results via PAGER.              |
| prompt   | \R                | Change prompt format.                                      |
| quit     | \q                | Quit.                                                      |
| tee      | tee [-o] filename | Append all results to an output file (overwrite using -o). |
+----------+-------------------+------------------------------------------------------------+
Time: 0.012s
[SQL]_SYSTEM@localhost:USER>

The Art of Mapping Globals to Classes (2 of 3)

If you are looking to breathe new life into an old MUMPS application follow these steps to map your globals to classes and expose all that beautiful data to Objects and SQL.

This example is going to cram in 4 or 5 different things beyond what was covered in Part 1

Since Caché 2017 the SQL engine has included new set of statistics. These record the number of times a query is executed and the time it takes to run.

Introduction

This is a simple tutorial on the quickest way I found to create a sample database for any purposes such as testing, making samples for tutorials, etc.

Creating a namespace

1. Open the terminal
2. Write the command "D $SYSTEM.SQL.Shell()"
3. Write "CREATE DATABASE " and the name you want for your namespace.

Now you have a new namespace in a faster way than creating it from the Management Portal - which of course offers way more configuration options.

With IRIS 2021.1, we released a significant revision our SQL utilities API at %SYSTEM.SQL. Yes, that's a while ago now, but last week a customer asked a few questions about this and then @Tom Woodfin applied gentle mental pressure ;-) to make me describe the rationale of these changes in a little more detail on the Developer Community. So here we go!

Host Variables are a rather common programming feature in many implementations of SQL.
A recent question in DC made me aware that in IRIS, Caché, Ensemble, ...
host variables just exist within embedded SQL

> You can supply host variables for Embedded SQL queries only. <

Related examples are included in the available Documentation

This is a description for a workaround if you don't / can't use embedded SQL.

As you may well remember from Global Summit 2022 or the 2022.2 launch webinar, we're releasing an exciting new capability for including in your analytics solutions on InterSystems IRIS. Columnar Storage introduces an alternative way of storing your SQL table data that offers an order-of-magnitude speedup for analytical queries. First released as an experimental feature in 2022.2, the latest 2022.3 Developer Preview includes a bunch of updates we thought were worth a quick post here.

The Caché System Management Portal includes a robust web-based SQL query tool, but for some applications it’s more convenient to use a dedicated SQL client installed on a user’s PC.

SQuirreL SQL is a well known open source SQL client built in Java, which uses JDBC to connect to a DBMS. As such, we can configure SQuirreL to connect to Caché using the Caché JDBC driver.

We're excited to continue to roll out new features to InterSystems IRIS Cloud SQL, such as the new Vector Search capability that was first released with InterSystems IRIS 2024.1. Cloud SQL is a cloud service that offers exactly that: SQL access in the cloud. That means you'll be using industry-standard driver technologies such as JDBC, ODBC, and DB-API to connect to this service and access your data. The documentation describes in proper detail how to configure the important driver-level settings, but doesn't cover specific third-party tools as - as you can imagine - there's an infinite number of them.

In this article, we'll complement that reference documentation with more detailed steps for a popular third-party data visualization tool that several of our customers use to access IRIS-based data: Microsoft Power BI.

The newer dynamic SQL classes (%SQL.Statement and %StatementResult) perform better than %ResultSet, but I did not adopt them for some time because I had learned how to use %ResultSet. Finally, I made a cheat sheet, which I find useful when writing new code or rewriting old code. I thought other people might find it useful.

First, here is a somewhat more verbose adaptation of my cheat sheet:

Hello IRIS community,

InterSystems Certification is developing a certification exam for InterSystems IRIS Developer professionals, and if you match the exam candidate description given below, we would like you to beta test the exam.