#Caché

Is there someone that has developped a program in order to create a 
"decisiontree"? Depending The answer to a question leads to another question, and so on, 
and so on, and there is an option to return to another point in the decisiontree.

Best regards,

Simon.

p.s. I've already got something, but it's not workable. But to get an idea:

Often times support and sales engineers are asked about recent benchmark results on various platforms and large scale configurations.  These will be made available here in the Developer Community in the "Documentation" section, and as an example here's a link to a recent Intel E7 v2 series processor benchmark.

https://community.intersystems.com/documentation/data-scalability-intersystems-caché-and-intel-processors-0

There are several reports available and more will be made available on an on-going basis.

You may have missed the news that support for older version of Internet Explorer ends next week Tuesday, January 12th. The original blog post from Microsoft can be found here:

https://www.microsoft.com/en-us/WindowsForBusiness/End-of-IE-support

A patch will go live next week Tuesday, that will nag users of older IE versions to upgrade to a recent version. The patch is identified as KB3123303. You can find more information about this patch here:

https://support.microsoft.com/en-us/kb/3123303?sd=rss&spid=14019

I am trying to define the charset for a JQM Application and it is not working. I have tried the following options without success:

Hi,

Is there any API equivalent (within Config.Databases class, or elsewhere) that has the same functionality as the 'Recreate a database' option in the ^DATABASE routine?

This option was added to ^DATABASE (according to internal Devlog CFL1263):

to recreate a database which is equivalent to deleting the .DAT file and recreating it.

Is there a way to select distinct keys from an field that has a collection index? I have a field defined as follows: Property data As %Library.String(COLLATION = "EXACT", MAXLEN = "", TRUNCATE = 0); Index data On data(KEYS) [ Type = bitmap ]; And I define a build value array method that parses my data outputs an array in the format array(KEYS)=VALUES. This is very useful because I can query my data using criteria such as  WHERE FOR SOME %ELEMENT(data) (%KEY='param') My question is whether there is some way to select distinct key values, e.g. SELECT DISTINCT KEYS____ FROM ____ . Should I come

Hi All,

I am trying to disable a button on a JQM application.

I started the button as disabled according to this code: {type:'$button',caption: Button',key:'button',disabled:true}

However, I would like to enable or disable the button via JavaScript code . I have tried the following, but it don´t have the same behavior and style as the code above.  

var view = zen('mainView');
              view.disableItem('button',true,0);

There seems to be little point to journal audit db updates; why rollback an audit entry for an attempted update?

I’m working on some auditing code and I have a few questions (feel free to respond regarding 2016.1 or later).

I am using &html<> to output some CSS to my page (which is a class-based and not a tag-based page), and the selectors contain the '>' character which the compiler chokes on.  How can I escape the '>' so it still displays as such in the web page source but doesn't trip up the compiler?

This is for 2012.2 btw.

Hi -

If you have Cache installed on a Cent OS machine, and you want to switch the OS to Red Hat 7, and your Caché is installed on a non-OS drive, do you need to reinstall Caché?

I don't think so, but I wanted to check

The attached zip file contains a bunch of examples of Cache SQL Storage mappings that I have done over the years.

If you have existing globals and want to expose them via Objects or SQL you need to setup Cache SQL Storage mapping.  If you do not see an example that helps with your case send me an example and I can help you out.

Tip dvacátý šestý: objekty a concurrency 2 - swizzling

Introduction

To overcome the performance limitations of traditional relational databases, applications - ranging from those running on a single machine to large, interconnected grids - often use in-memory databases to accelerate data access. While in-memory databases and caching products increase throughput, they suffer from a number of limitations including lack of support for large data sets, excessive hardware requirements, and limits on scalability.

Executive Overview

One way financial services firms can improve their operational efficiency is to revamp their data management infrastructure. Creating a central repository for data that is used by multiple applications can ensure data consistency and quality across the enterprise, ease integration bottlenecks, and lower the number of failed trades.However, different applications have different database usage patterns. To satisfy them all, any central data repository must:

Customers who switch to Caché from relational databases report that their average performance is up to 20 time faster, running on the same hardware, with no changes to the application. What is it about Caché that lets applications run so fast?

Introduction

By now, anybody working in the technology sector will have heard of Cloud computing. But the concept is increasingly being paid attention to outside of IT departments, with growing recognition among boardlevel executives of the potential of this range of innovations. Frequently, senior personnel are hearing stories about how the Cloud helps organizations reduce costs, boost efficiency and expand their operations, so they’ll be excited about what the Cloud can do for them.

Abstract

In a recent benchmark test of an application based on InterSystems Caché, a sustainable rate of 8.9million database accesses/second, with peaks of 16.9 million database accesses/second, was achieved. These results were from a test performed on a connected system of eight applications servers, using Intel Xeon 5570 processors, and running Linux as the operating system. This benchmark shows that:

Introduction

With the growing popularity of smart phones and tablet computers, consumers are coming to expect that software solutions will be presented as "apps" on their mobile devices. The challenge for most application developers is to find ways to make their existing solutions run on modern mobile platforms without incurring the delay and cost of a complete rewrite.

Introduction

Because of increasing business and governmental pressures to integrate their operations, the financial services industry is developing a number of standards for data exchange and other common functions. Standards such as XBRL, FpML, MDDL, RIXML, and FIXML are all specialized dialects of XML (Extensible Markup Language). Any financial services application with good support for XML will be able to communicate effectively using one or more of the emerging industry standards.

Executive Summary

InterSystems has implemented a broad set of MultiValue extensions for its Caché multidimensional database. These extensions enable the migration of MultiValue applications to Caché and bring the full range of Caché object and SQL development technologies to MultiValue developers. The result: your existing MultiValue investments are preserved, you gain a broad spectrum of highly scalable deployment options, and your developers can combine the best of MultiValue, object, relational, and technologies to extend existing applications and build new ones.

Introduction

InterSystems encourages the adoption of a flexible, practical approach to application development, rather than strict adherence to one of the prevalent development theories. This paper offers advice based upon our experience. However needs, attitudes, and styles vary; we recommend that each programmer choose the development approach that works best for them. Caché supports a wide range of development methodologies, not just those recommended here.

Using Intel® Advanced Encryption Standard New Instructions with InterSystems Caché Substantially Improves Encryption Performance and Reduces Computational Overhead

Executive Summary

Executive Summary

The best way to compare the performance of database products is in a head-to-head test using a real application, preferably one of your own. This is especially true when evaluating Caché's post-relational technology, because "standard" transaction processing benchmarking methodologies assume the restrictive "row and columns" format of a relational database. They cannot accurately predict the performance of real applications, which often use complex data models.

Abstract

The European Space Agency (ESA) has chosen InterSystems Caché as the database technology for the AGIS astrometric solution that will be used to analyze the celestial data captured by the Gaia satellite.

The Gaia mission is to create an accurate phase-map of about a billion celestial objects. During the mission, the AGIS solution will iteratively refine the accuracy of Gaia's spatial observations, ultimately achieving accuracies that are on the order of 20 microarcseconds.

Abstract

A benchmark of a real-world application, which loads data into a data warehouse for subsequent analysis, was performed. To conduct the benchmark, one module of the Oracle-based application was replicated in Caché ObjectScript. Only about 40 person-hours of work was required to duplicate the functionality of the original module in Caché.

Introduction

If the administrators responsible for securing applications had their way, passwords would be long complex strings of random symbols, and users would memorize different passwords for every application they use. But in the real world, few people are capable of such prodigious feats of memory. The typical user can only remember a handful of relatively short passwords.

Providing a reliable infrastructure for rapid, unattended, automated failover

Technology Overview

Traditional availability and replication solutions often require substantial capital investments in infrastructure, deployment, configuration, software licensing, and planning. Caché Database Mirroring (Mirroring) is designed to provide an economical solution for rapid, reliable, robust, automatic failover between two Caché systems, making mirroring the ideal automatic failover high-availability solution for the enterprise.

Introduction

This document is intended to provide a survey of various High Availability (HA) strategies that can be used in conjunction with InterSystems Caché, Ensemble, and HealthShare Foundation. This document also provides an overview of the various types of system outages that can occur, as well as how each strategy would handle a given outage, with the goal of helping you choose the right strategy for your specific deployment.

The strategies surveyed in this document are based on three different HA technologies: