Article
· Sep 2, 2016 2m read
Advanced URL mapping for REST

By now it's a commonplace how to implement a basic REST API in Caché and there is good documentation about it here: REST in Caché

A question that comes up from time to time is:

How can I make a parameter in my REST url optional?

Simply put, is it possible to create a URL map in Caché that maps a URL like this:

12 1
0 2.7K

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.

12 4
3 843

Hi,

I'm doing a query in SQL and I need to sort my data by some non-repeated field.

Unfortunately, my data is grouped in a way that I cannot guarantee that any column will not have repeated data, so one solution would be to take the row number.

Also, the Cache is not accepting Row_Number () in my querry and I would like to know if there is another solution to return line numbers or some way to add this function to the Cache.

Best regards.

12 7
0 3.4K
Article
· 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.

12 2
0 784
InterSystems Official
· Feb 15, 2023
InterSystems Supported Platforms Update Feb-2023

InterSystems Supported Platforms Update Feb-2023

Welcome to the very first Supported Platforms Update! We often get questions about recent and upcoming changes to the list of platforms and frameworks that are supported by the InterSystems IRIS data platform. This update aims to share recent changes as well as our best current knowledge on upcoming changes, but predicting the future is tricky business and this shouldn’t be considered a committed roadmap.

We’re planning to publish this kind of update approximately every 3 months and then re-evaluate in a year. If you find this update useful, let us know! We’d also appreciate suggestions for how to make it better.

With that said, on to the update…

12 1
1 1.3K
Article
· Feb 13, 2017 14m read
Creating custom SNMP OIDs

This post is dedicated to the task of monitoring a Caché instance using SNMP. Some users of Caché are probably doing it already in some way or another. Monitoring via SNMP has been supported by the standard Caché package for a long time now, but not all the necessary parameters are available “out of the box”. For example, it would be nice to monitor the number of CSP sessions, get detailed information about the use of the license, particular KPI’s of the system being used and such. After reading this article, you will know how to add your parameters to Caché monitoring using SNMP.

12 14
3 11.5K

The %Net.SSH.Session class lets you connect to servers using SSH. It's most commonly used with SFTP, especially in the FTP inbound and outbound adaptors.

In this article, I'm going to give a quick example of how to connect to an SSH server using the class, describe your options for authenticating, and how to debug when things go wrong.

Here's an example of making the connection:

12 4
1 6.3K

The object and relational data models of the Caché database support three types of indexes, which are standard, bitmap, and bitslice. In addition to these three native types, developers can declare their own custom types of indexes and use them in any classes since version 2013.1. For example, iFind text indexes use that mechanism.

12 1
1 2.1K

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.

11 7
6 1.6K

Motivation

I started programming back in 2015, when I was doing my bachelor's in computer science. I didn't know about ObjectScript until I started my new job four months ago. Objectscript isn't actually a young programming language. Compared to C++, Java and Python, the community isn't as active, but we're keen to make this place more vibrant, aren't we?

11 6
3 139
Article
· Feb 8, 2019 2m read
Client Websockets based CSP

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

11 0
0 527

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:

11 0
2 489
Announcement
· Aug 25, 2016
JSON changes in Caché 2016.2

As Bill has mentioned earlier in his post, we have carefully reviewed the JSON capabilities and made some adjustments to ensure they deliver the best benefit to you. In this post, I am going to describe the modifications in more detail and provide guidance for you to understand the implication for your code base.

11 8
1 4K

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.

11 5
1 2.7K