#Caché

Hi all,

I'm pleased to announce this personal project to convert a number to text, in spanish, english, catalan and russian.

the aim of this function is to convert numbers into text. It allows a maximum number of 15 digits.

Introduction

Despite the fact that InterSystems has long recommended using external backup tools, many users have opted to use the internal Online Backup facility, which is included in all distributions of InterSystems products (IRIS Data Platform, Caché, etc.). The reasons why are quite obvious:

$LIST string format and %DynamicArray and %DynamicObject classes

IRIS, and previously Cache, contain several different ways to create a sequence containing a mixture of data values. A data sequence that has been available for many years is the $LIST string. Another more recent data sequence is the %DynamicArray class, which along with the %DynamicObject class, is part of the IRIS support for JSON string representation. These two sequences involve very different tradeoffs.

$LIST String Format

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.

The Caché / Ensemble standard distribution contains in namespace SAMPLES
a nice example of a CSP page consuming WebService as a Client.
I have modified it not only to display the replies but to feed them back into a Global.
I used the classic Hyperevent to achieve this. The replies end up as a log in global^WSREPLY.
When there is no input anymore the page closes and goes away.

There are 2 versions with visible and hidden display during operation.
dc.WSCSP.reverseVerbose.cls and dc.WSCSP.reverseHidden.cls

Hi Community,

This post is to introduce one of my first project in COS, I created when started to learn the language and until today I'm keeping improve it.

The CosFaker(here on Github) is a pure COS library for generating fake data.

cosFaker vs Populate Utils

So why use cosFaker if caché has the populate data utility?

A few people wrote to me asking about the infrastructure behind the Atelier Server implementation. Its neat and a worthwhile story to share so I am writing it up here as a post on the community. I want to go in to a little detail on why it was needed and then I will outline in detail how we went about implementing this.

Have you ever thought what could be a reason why some development environment (database, language) would eventually become popular? What part of this popularity could be explain as language quality? What by new and idioms approaches introduced by early language adopters? What is due to healthy ecosystem collaboration? What is due to some marketing genius?

Cache tricks

Several years ago, long before Developer Community Portal was launched, I published a series of Caché tricks at one of Czech web sites. In this article, I’m posting translated version of one of them.

Capturing output of someone else’s methods or routines

Suppose you, or someone else created a useful method or routine, that was producing some computation that you’d like to benefit from, but the routine was writing output to process principal device.

You would like to use the data, but you need it not written to a device, but assigned to a variable. And, for any reason, you can’t modify the code. What can you do?

This is the third article (see Part 1 and Part 2) where I continue to introduce you to the internal structure of Caché databases. This time, I will tell you a few interesting things and explain how my Caché Blocks Explorer project can help make your work more productive.

Pouring The Coffee: Creating and scheduling a task

Don't you wish a fresh, hot cup of coffee could be waiting for you right when you get into the office? Let's automate that!

Cache and IRIS come with a built-in Task Manager, which should have a familiar feel to those used to using the Windows task scheduler or using cron on Linux. Your user account will need access to the %Admin_Task resource to use it, and you can access it in the management portal under System Operation -> Task Manager. When first installed, there are roughly 20 types of task that you can schedule.

For those of you who might be new to IRIS, and even those who have used Cache or IRIS for some time but want to explore beyond its usually-assumed boundaries and practices, you might want to dive into this detailed exploration of the database engine that is at its heart, and discover just what you can really do with it, going way beyond what InterSystems have done with it for you.

I have been meaning to make a post about this topic for a few weeks and the other day an issue came in through the WRC about it so it seems this is a conversation we should be having. I want to begin by taking a few moments to explain "Why Atelier" then we can talk about what this means in the general sense for Studio and Atelier and Caché developers. We have wrestled with what to do with Studio for years. When I moved to Product Management in 2008 this was already a "thing". At the time we could not reach a consensus. Some felt Studio was fine as is.

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.