#Distributed Data Management

    Hi, 

   I  like to validate some use cases and have the following question. I am relatively new to IRIS. Perhaps someone can help:

   1. I have a global m[x,y,z,f] distributed across multiple sharded instances
   2. I know that i can set assign computed SQL expressions to class variables using Objectscript 
   3. Is there a possibility in Globals API to do the same ? Set f = x + y as a computed expression in the global  m[x,y,z,f]  ?

       a.  We would want to use the global API to change f programmatically using code

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 !

Running a Background Job using JOB command is a well-known feature.
Using ECP to distribute databases to several servers is also well know.
But using the combination of both to run a process on a different server
seems to be a rare case.

Last week, we announced the InterSystems IRIS Data Platform, our new and comprehensive platform for all your data endeavours, whether transactional, analytics or both. We've included many of the features our customers know and loved from Caché and Ensemble, but in this article we'll shed a little more light on one of the new capabilities of the platform: SQL Sharding, a powerful new feature in our scalability story.

While creating namespaces, there is a provision for keeping the data, and code separately in database.

What I am looking for,

What are the benefit we can achieve by doing this?

Is there any documentation of article which might help understanding?

Thanks You!

In part I of this series we have introduced MapReduce as a generic concept, and in part II we started to approach Caché ObjectScript implementation via introducing abstract interfaces. Now we will try to provide more concrete examples of applications using MapReduce.

The technology of load balancing between several servers with relatively low capacity has been a standard feature of Caché for quite a while. It is based on the distributed cache technology called ECP (Enterprise Cache Protocol). ECP provides a host of possibilities for horizontal scaling of an application, and yet keeping the project budget fairly low. Another apparent advantage of ECP network is the possibility to conceal its architecture in the depths of Caché configuration so that applications developed for the traditional (vertical) architecture can be fairly easily migrated to a horizontal ECP environment. The ease of this process is so mesmerizing, that you start wishing it was always this way. For instance, everybody is used to having a possibility to control Caché processes: the $Job system variable and associated classes/functions work magic in skilful hands. Stop, but now processes can end up being on different Caché servers…

This article is about how to gain as much transparency in controlling processes in ECP environment as in traditional (non ECP) one.