Hey Community,

We're pleased to invite you all to the Virtual Summit 2020 session dedicated to InterSystems online programming contests, best winning projects, and their developers! Please join:

⚡️ "Best applications of InterSystems programming contest series: Best IntegratedML, FHIR, REST API, Native API, ObjectScript solutions" session ⚡️

Please check the details below.

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Hi Developers,

If you are planning to attend the Focus Sessions of InterSystems Virtual Summit 2020, please do not miss the session dedicated to InterSystems Developer Community and Open Exchange!

⚡️ "Developer Ecosystem: Developer Community forum and Open Exchange applications gallery" session ⚡️

Speakers: 
🗣 @Anastasia Dyubaylo, Community Manager, InterSystems 
🗣 @Evgeny Shvarov, Starups and Community Manager, InterSystems 

What awaits you?

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD
  • Why containers?
  • Containers infrastructure
  • CD using containers

In the first article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software.

In the second article, we covered GitLab Workflow - a complete software life cycle process and Continuous Delivery.

In the third article, we covered GitLab installation and configuration and connecting your environments to GitLab

In the fourth article, we wrote a CD configuration.

In the fifth article, we talked about containers and how (and why) they can be used.

In the sixth article let's discuss main components you'll need to run a continuous delivery pipeline with containers and how they all work together.

In this article, we'll build Continuous Delivery configuration discussed in the previous articles.

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Announcement
Henry Pereira · Mar 27, 2020
Give it a try on SQLBuilder tool

SQLBuilder is a flexible and powerful SQL query string builder for InterSystems IRIS,

With SQLBuilder you have nice and clean object oriented methods, instead of having to use concatenation and substituition to generate dynamic queries.

A Dynamic SQL without SQLBuilder

A Dynamic SQL with SQLBuilder

 

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Your application is deployed and everything is running fine. Great, hi-five! Then out of the blue the phone starts to ring off the hook – it’s users complaining that the application is sometimes ‘slow’. But what does that mean? Sometimes? What tools do you have and what statistics should you be looking at to find and resolve this slowness? Is your system infrastructure up to the task of the user load? What infrastructure design questions should you have asked before you went into production? How can you capacity plan for new hardware with confidence and without over-spec'ing? How can you stop the phone ringing? How could you have stopped it ringing in the first place?

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Those of you who are following the FullStack competition here in the Developer Community will know that I submitted an entry named qewd-conduit.  I wanted to summarise why I think it's something worth you taking a bit of time to check out.

qewd-conduit uses the Node.js-based QEWD framework alongside IRIS to implement the back-end REST APIs for something known as the RealWorld Conduit application:

https://github.com/gothinkster/realworld

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Hi 

Has anyone used Health Connect/Ensemble to receive results directly from POCT devices (Glucose monitors etc)?

I've been looking for information on the POCT01-A  protocol, and as far as I can tell it is a HL7v3 XML schema, I should be able to get results from these devices, though I expect I need a webserver endpoint. (though I can't find any reference in the Health Connect documentation)

Does anyone have any knowledge of this?

KR

 

Stephen

EDIT:  from the silence I'm wondering if this in normally handed off to specialist middleware?

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Hi, I am new to IRIS and We are planning to setup a CI pipeline on AWS VM deploying the iris data platform container. I am trying to find out which folders needs to be inside the source control and where (exact folder) the updated code needs to be pulled in the container. I would be much obliged if anyone cant point the CI CD related documentation.

Thanks,
Raj

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Hey, 

I have a value in epoch time in which I need convert in order to be able to lookup a table that has dates in YYYY-MM-DD HH:MM:SS format

I thought the below would work but it is not.

select COUNT ('Arrival Time') FROM dbo.table where 'Arrival Time' < DATEADD(ms, CONVERT(int,LEFT(1603173432000, 20)), '1970-01-01 00:00:00')

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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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