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.

Finding Caché’s JDBC driver JAR

The JAR file containing the Caché JDBC driver is installed automatically by the Caché installer when installing a full Caché instance or when installing client components only.

As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.

Outline

• What are the connection parameters you need to connect to a remote database?
• What is the JDBC Gateway vs the Java Gateway Service in Ensemble?
• What tools and methods are available to debug issues?

Keywords: Python, JDBC, SQL, IRIS, Jupyter Notebook, Pandas, Numpy, and Machine Learning 

1. Purpose

This is another 5-minute simple note on invoking the IRIS JDBC driver via Python 3 within i.e. a Jupyter Notebook, to read from and write data  into an IRIS database instance via SQL syntax, for demo purpose. 

Last year I touched on a brief note on Python binding into a Cache database (section 4.7) instance.

Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.

With the release of InterSystems IRIS Cloud SQL, we're getting more frequent questions about how to establish secure connections over JDBC and other driver technologies. While we have nice summary and detailed documentation on the driver technologies themselves, our documentation does not go as far to describe individual client tools, such as our personal favourite DBeaver. In this article, we'll describe the steps to create a secure connection from DBeaver to your Cloud SQL deployment.

IRIS and Ensemble are designed to act as an ESB/EAI. This mean they are build to process lots of small messages.

But some times, in real life we have to use them as ETL. The down side is not that they can't do so, but it can take a long time to process millions of row at once.

To improve performance, I have created a new SQLOutboundAdaptor who only works with JDBC.

BatchSqlOutboundAdapter

Extend EnsLib.SQL.OutboundAdapter to add batch batch and fetch support on JDBC connection.

Benchmark

Benchmarks released on Postgres 11.2 with 1 000 000 rows fetched and 100 000 rows inserted on 2 columns.

This is a sample Ensemble/Health Connect production which demonstrates how to receive an HL7 order (ORM) inbound from a file, extract fields (in this case, basic demographic information), and insert those into a table in an external SQL database via ODBC.  

Included in the zip file:

• Exported code
• Sample ORM message
• 'How to configure' doc 

The last days I've work with the great new feature: LOAD DATA With this post I would like to share my first experiences with you. The following points do not contain any order or other evaluation. These are only things that I noticed when using the LOAD DATA command. It should also be noted that these points are based on the IRIS Version 2021.2.0.617 which is a preview release. So it may be that my observations do not apply to newer IRIS versions. But maybe they are helpful for others.

1) The file path is on server side

I have done my first tests via JDBC.

Several steps should be done in order to secure the connection through xDBC clients to an IRIS Server instance using TLS. Most of the information can be obtained from the documentation about TLS on IRIS here, about configuring the security layer for encrypted connections. In the next paragraphs we will cover an step-by-step guide on how to configure and test the connection using SQL Clients apps using ODBC and JDBC.

Astronomers’ tools

5 years ago, on December 19, 2013, the ESA launched an orbital telescope called Gaia. Learn more about the Gaia mission on the official website of the European Space Agency or in the article by Vitaly Egorov (Billion pixels for a billion stars).

However, few people know what technology the agency chose for storing and processing the data collected by Gaia. Two years before the launch, in 2011, the developers were considering a number of candidates (see “Astrostatistics and Data Mining” by Luis Manuel Sarro, Laurent Eyer, William O’Mullane, Joris De Ridder, pp. 111-112):

• IBM DB2,
• PostgreSQL,
• Apache Hadoop,
• Apache Cassandra and
• InterSystems Caché (to be more precise, the Caché eXTreme Event Persistence technology).

Comparing the technologies side-by-side produced the following results (source):

The first four will probably sound familiar even to schoolchildren. But what is Caché XEP?

Keyword: Pandas DataFrame, IRIS, Python, JDBC

Purpose

Pandas DataFrame is popular tool for EDA (Exploratory Data Analysis). In ML tasks, the first thing we usually perform is to understand the data a bit more. Last week I was trying this Covid19 dataset in Kaggle Basically the data is a spreadsheet of 1925 encounter rows with 231 columns, and the task is simply to predict whether a patient (linked to  1 or more encounter records) would be admitted to ICU. So it's a normal classification task, and we would as usual use padas.DataFrame to take a quick look first.

DataGrip is a multi-engine database environment targeting the specific needs of professional SQL developers, DataGrip makes working with databases an enjoyable and productive experience.

To work with InterSystems IRIS from DataGrip you'll need to add InterSystems JDBC driver first (once per DataGrip) and after that add all your InterSystems IRIS connections.

Part 1: Add InterSystems IRIS JDBC Driver

1. Go To File → DataSources

2. Go to + → Driver

3. Set Driver properties:

• Name: InterSystems IRIS
• Class: com.intersystems.jdbc.

In this article, we will establish an encrypted JDBC connection between Tableau Desktop and InterSystems IRIS database using a JDBC driver. While documentation on configuring TLS with Java clients covers all possible topics on establishing an encrypted JDBC connection, configuring it with Tableau might be a little bit tricky, so I decided to write it down.

Securing SuperServer

Before we start with client connections, you need to configure SuperServer, which by default runs on port 1972 and is responsible for xDBC traffic to accept encrypted connections.

WIN SQL is the normal editor used by most of the users .But we can't download large amount of data using winsql . So I have written a tutorial how to connect with a new Java based editor called Squirrel SQL which can easily download or export data in excel or any other formats. Also I included a Java JCBC connection program to connect with the IRIS database especially a mirroring/failover server.

SSH framework is a relatively representative framework of Java, which was popular many years ago. There are Struts+Spring+hibernate and Spring MVC+Spring+hibernate. Of course, I used the second one in college. If I can connect IRIS to Hibernate as a library, does it also mean that IRIS can be developed using SSH framework in theory?

Tools and environment

JDK 1.8

       Maven

       Hibernate 5.X.X

       IRISHealth-2022.1.3

       intellij idea

       Windows 10 64

Create database

       Create several tables in code mode

Class BKIP.SOA.MonitorScreen.CacheTable.

As a former JAVA developer it has always been a challenge to decide which database was the most suitable for the project we were going to develop, one of the main criteria I used was their performance, as well as their HA configuration capabilities ( high availability). Well, now is the time to put IRIS to the test with respect to some of the most commonly used databases, so I've decided to create a small Java project based on SpringBoot that connects via JDBC with a MySQL database, another of PostgreSQL and finally with IRIS.

Introduction

There are many entities in IRIS which are extremely difficult to transfer to another system.They usually contain important system-stored objects: users, roles, privileges, mappings, and applications. The exception to this list is for resources, which are facilitated by the ability to select and save them from the management portal interface [System > Security Management > Resources] Yet, things are not as good with other system objects.

Not sure there are many that connect to MS SQL to execute queries, stored procedures, etc, but our Healthsystem has many different MS SQL based databases we use within the Interoperability environment for various reasons.

With the push to moving from on-prem to the Cloud we ran into some difficulties with our SQL Gateway connections and knowing how to config them to use Microsoft Entra for Active Directory Authentication.

There are many articles out on the web, but there was not one that could give us the full answer to what we needed to do, and Microsoft wasn’t much help.

Many times it is necessary copy or send files to your docker container instance.

In my case was with IRIS JDBC driver.

Docker has this recipe for this (credits to https://docs.docker.com/engine/reference/commandline/cp/):

docker cp [OPTIONS] CONTAINER:SRC_PATH DEST_PATH|-
docker cp [OPTIONS] SRC_PATH|- CONTAINER:DEST_PATH

But to copy you need your container name. Write this command for this:

docker ps

In my, my-iris is the container name.

If you need to know file location into your docker file system too, write:

1. To go to bash of your docker instance: docker exec -it my-iris /bin/bash.
2. Write cd .

I've asked a lot of questions leading up to this, so I wanted to share some of my progress.

The blue line represents the number of messages processed.  The background color represents the average response time.  You can see ticks for each hour (and bigger ticks for each day).   Hovering over any point in the graph will show you the numbers for that period in time.

This is super useful for "at a glance" performance monitoring as well as establishing patterns in our utilization.

Here is the query used:

SELECT
    mh.name                                  AS MessageType,
    COUNT(mh.

Problems with Strings

I am accessing IRIS databases with JDBC (or ODBC) using Python. I want to fetch the data into a pandas dataframe to manipulate the data and create charts from it. I ran into a problem with string handling while using JDBC. This post is to help if anyone else has the same issues. Or, if there is an easier way to solve this, let me know in the comments!

I am using OSX, so I am unsure how unique my problem is. I am using Jupyter Notebooks, although the code would generally be the same if you used any other Python program or framework.

Dear community members!

A very common problem of our users is to use an external database as data source in an IRIS production. As many of you already know, we have two ways to connect directly to an external database, the first one is using an ODBC connection, the second is using JDBC.

In our example we are going to create a connection using JDBC, and we are going to build a simple Docker's project, in this way you will be able to modify the example as you wish.

The code is available from this URL: https://github.com/intersystems-ib/workshop-sql-jgw

In our docker-compose.

A Quick Start to InterSystems Cloud SQL Data in Databricks

Production Configuration

This demo has an interoperability production with 16 items. 

Production Configuration HL7 + Kafka Producer

The first part of this demonstration consists of sending an HL7 SIU file which will be transmitted to the 2 other HL7 flows (HTTP and TCP), and transformed and transmitted to the Kafka server. HTTP and TCP flows will transform HL7 messages in the same way before sending them to Kafka as well.

What comes to the data platform (not the user facing application) most of the the events of interest/required are available as predefined system audit events in audit log - out of the box. They just need to be enabled.

Hi, I hope this post helps.

The bottom line: MAXLEN is relevant mostly for odbc/jdbc connections and you need to specify an appropriate value within your  tables (classes), otherwise the data might be truncated when you query it, or even fail when you try to insert data.

Introduction

This article aims to explore how the FHIR-PEX system operates and was developed, leveraging the capabilities of InterSystems IRIS.

Streamlining the identification and processing of medical examinations in clinical diagnostic centers, our system aims to enhance the efficiency and accuracy of healthcare workflows. By integrating FHIR standards with InterSystems IRIS database Java-PEX, the system help healthcare professionals with validation and routing capabilities, ultimately contributing to improved decision-making and patient care.

Intro

In a fast-paced digital era, effective communication is crucial. This article introduces a Java-based chat project, combining the strength of IRIS database and ChatGPT intelligence. Built on Java, it goes beyond real-time messaging, leveraging IRIS and ChatGPT for an enhanced chat experience. Also, the name of the project references the cultural classic - Star Wars.

Building Application

Building our dynamic chat application involves a seamless integration of key components and technologies. Java serves as the heart that drives server-side logic and business operations.

Introduction

Managing databases and performing CRUD operations are fundamental tasks for developers building data-driven applications. While many database management systems (DBMS) exist, they can be complex and cumbersome to interact with, especially when it comes to creating databases and tables, handling constraints, and performing real-time data operations through an API.

This web-based Database Management Tool simplifies the entire process, offering an intuitive UI for managing databases and tables, alongside a powerful REST API for interacting with the data.

GmOwl is a solution that offers an organized and engaging learning platform. It was developed to cater to the increasing need, for learning tools providing a versatile quiz environment that meets users requirements.

The main objective of GmOwl is to deliver an user experience for individuals participating in quizzes while giving administrators comprehensive control, over content and user engagement.

GmOwl uses Java EE with MVC template, and the InterSystems IRIS database is used to store data. The InterSystems JDBC Driver is used to connect to the database.