Working in support, I usually get asked how many days I should keep journals. Should it be two days or after two backups? More? Less? Why two?

The correct answer (for most of the environments) is that you should keep the journals since the last validated Backup. I.e., until you don't check if a Backup is valid (restoring the file and checking with the Integrity utility), you can't be sure there is a good copy of your data and can't purge the journals safely.

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InterSystems supports use of the InterSystems IRIS Docker images it provides on Linux only. Rather than executing containers as native processes, as on Linux platforms, Docker for Windows creates a Linux VM running under Hyper-V, the Windows virtualizer, to host containers. These additional layers add complexity that prevents InterSystems from supporting Docker for Windows at this time.

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If a picture is worth a thousand words, what's a video worth? Certainly more than typing a post.

Please check out my "Coding talks" on InterSystems Developers YouTube:

1. Analysing InterSystems IRIS System Performance with Yape. Part 1: Installing Yape

 

Running Yape in a container.

2. Yape Container SQLite iostat InterSystems

Extracting and plotting pButtons data including timeframes and iostat.

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Article
Robert Cemper · Mar 5, 2021 3m read
Using ECP across IRIS and Caché

Migration from Caché to IRIS can be quite a challenge if your code is grown over many years
and probably not so clean structured as you may like it. So you face the need to check your
migrated code against some reference data. A few samples might not be a problem,
but some hundred GB of data for testing might be.  

A possible step could be to have your fresh code in IRIS but leave your huge datastore on Caché and connect both environments over ECP.  I have created a demo project that gives you the opportunity to try this based on 2 Docker images with IRIS and with Caché connected over ECP.

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Article
Robert Cemper · Jul 27, 2020 3m read
ZPMshow - a helper for tired fingers
This is a coding example working on IRIS 2020.2 
It will not be kept in sync with new versions 
It is also NOT serviced by InterSystems Support !

A helper to List, Install, Uninstall ZPM packages

The offer of ZPM is growing daily and the short names and
acronyms of the offer are sometimes hard to understand and
also hard to type with my lazy fingers.

Video

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This is a coding example working on IRIS 2020.2 
It will not be kept in synch with new versions 
It is also NOT serviced by InterSystems Support !

My demo video is now also available to watch the demo in operation.
https://youtu.be/dSV-0RJ5Olg

 

Hi folks,
It's time now for a Micro Service Demo with a total fresh IRIS Image and an image that you both PULL with
docker  and run with only 4 lines of docker commands. 
June 1st, 2020 - rcc

There is now a compact All-in-1 version available that combines all parts in a single container image.
For details see: IRIS-NativeAPI-Nodejs-compact
May 24, 2020 - rcc

I have added a simplified installation using Docker, see context
May 25, 2020 - rcc

There are enhanced scripts suitable & tested for Linux & Windows available here
https://github.com/rcemper/WSockClientMicroSV/blob/master/READMEwindows.MD
May 26, 2020 - rcc

This demo is a redesign of the WebSocket Client based on Node.js existing already for Caché. The major changes:

  • use of the new IRIS Native API for Node.js  especially Working with Global Arrays
  • change from a directly triggered client to a server design
  • put the result into a separate docker image as an example for a MicroService / MicroServer
  • add a simple interface in IRIS to control the MicroService execution.

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As we all well know, InterSystems IRIS has an extensive range of tools for improving the scalability of application systems. In particular, much has been done to facilitate the parallel processing of data, including the use of parallelism in SQL query processing and the most attention-grabbing feature of IRIS: sharding. However, many mature developments that started back in Caché and have been carried over into IRIS actively use the multi-model features of this DBMS, which are understood as allowing the coexistence of different data models within a single database. For example, the HIS qMS database contains both semantic relational (electronic medical records) as well as traditional relational (interaction with PACS) and hierarchical data models (laboratory data and integration with other systems). Most of the listed models are implemented using SP.ARM's qWORD tool (a mini-DBMS that is based on direct access to globals). Therefore, unfortunately, it is not possible to use the new capabilities of parallel query processing for scaling, since these queries do not use IRIS SQL access.

Meanwhile, as the size of the database grows, most of the problems inherent to large relational databases become right for non-relational ones. So, this is a major reason why we are interested in parallel data processing as one of the tools that can be used for scaling.

In this article, I would like to discuss those aspects of parallel data processing that I have been dealing with over the years when solving tasks that are rarely mentioned in discussions of Big Data. I am going to be focusing on the technological transformation of databases, or, rather, technologies for transforming databases.

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Over the past year or so, my team (Application Services at InterSystems - tasked with building and maintaining many of our internal applications, and providing tools and best practices for other departmental applications) has embarked on a journey toward building Angular/REST-based user interfaces to existing applications originally built using CSP and/or Zen. This has presented an interesting challenge that may be familiar to many of you - building out new REST APIs to existing data models and business logic.

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In this article, I would like to talk about the spec-first approach to REST API development.

While traditional code-first REST API development goes like this:

  • Writing code
  • REST-enabling it
  • Documenting it (as a REST API)

Spec-first follows the same steps but reverse. We start with a spec, also doubling as documentation, generate a boilerplate REST app from that and finally write some business logic.

This is advantageous because:

  • You always have relevant and useful documentation for external or frontend developers who want to use your REST API
  • Specification created in OAS (Swagger) can be imported into a variety of tools allowing editing, client generation, API Management, Unit Testing and automation or simplification of many other tasks
  • Improved API architecture.  In code-first approach, API is developed method by method so a developer can easily lose track of the overall API  architecture, however with the spec-first developer is forced to interact with an API from the position if API consumer which usually helps with designing cleaner API architecture
  • Faster development - as all boilerplate code is automatically generated you won't have to write it, all that's left is developing business logic.
  • Faster feedback loops - consumers can get a view of the API immediately and they can easier offer suggestions simply by modifying the spec

Let's develop our API in a spec-first approach!

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Hi Developers!

Often when we develop some library, tool, package, whatever on InterSystems ObjectScript we have a question, how we deploy this package on the target machine?

Also, we often expect that some other libraries already installed, so our package depends on them, and often on some particular version of it.

When you code on javascript, python, etc the role of packages deployment with dependency management takes package manager.

So, I'm pleased to announce that InterSystems ObjectScript Package Manager available!

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Article
Robert Cemper · Apr 26, 2020 5m read
Materialized Views

A VIEW in SQL is basically a prepared SQL statement.
It has to be executed and assembled like any other SQL query.
MATERIALIZED VIEW means that the content is collected before hands and can be retrieved rather fast.
I saw the concept first with my favorite competitor named O* and they made a lot of noise about it.

  { favorite: because I could win every benchmark against them devil }

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I bet that not everyone familiar with InterSystems Caché knows about Studio extensions for working with the source code. You can actually use the Studio to create your own type of source code, compile it into interpretable (INT) and object code, and sometimes even add code completion support. That is, theoretically, you can make the Studio support any programming language that will be executed by the DBMS just as well as Caché ObjectScript. In this article, I will give you a simple example of writing programs in Caché Studio using a language that resembles JavaScript. If you are interested, please read along.

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Article
Oliver Wilms · Aug 4, 2021 3m read
IRIS Mirror in the cloud (AWS)

I have been working on redesigning a Health Connect production which runs on a mirrored instance of Healthshare 2019. We were told to take advantage of containers. We got to work on IRIS 2020.1 and split the database part from the Interoperability part. We had the IRIS mirror running on EC2 instances and used containers to run IRIS interoperability application. Eventually we decided to run the data tier in containers as well.

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This post provides guidelines for configuration, system sizing and capacity planning when deploying Caché 2015 and later on a VMware ESXi 5.5 and later environment.

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Article
Robert Cemper · Feb 8, 2019 2m read
Client for WebSockets based on CSP
This is a coding example working on Caché 2018.1.3 and IRIS 2020.2 
It will not be kept in sync with new versions 
It is also NOT serviced by InterSystems Support !

WebSockets as a communication technology wins increasing importance.
In the SAMPLES namespace, you find a nice example for running a WebSocket Server.
There is also a useful example for a Browser Client. But it is still in the browser. 

My point is:
How to consume the output of a WebSocket Server in your application?

 

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Article
Robert Cemper · Jul 20, 2020 2m read
SPOOL as SQL Table

Device #2 named SPOOL dates back to the predecessors of Caché and IRIS
It was the first "%Stream" like option to buffer output before printing.
It is also the first and still today the most simple way of output redirection.

Solution

This is also an example of a mapped Global. USE 2 write "actual date: ",$ZDT($h,3),!
redirects the output into the Global ^SPOOL

You can read the global manually or with some ancient utilities
or use this mapping to access it as class or a table with SQL.

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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Last week saw the launch of the InterSystems IRIS Data Platform in sunny California.

For the engaging eXPerience Labs (XP-Labs) training sessions, my first customer and favourite department (Learning Services), was working hard assisting and supporting us all behind the scene.

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