#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

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:

Introduction

Impedance mismatch is a term commonly used to describe the problem of an object-oriented (OO) application housing its data in legacy relational databases (RDBMS). C++ programmers have dealt with it for years, and it is now a familiar problem to Java and other OO programmers.

InterSystems Caché 2015.1 soars from 6 million to more than 21 million end-user database accesses per second on the Intel® Xeon® processor E7 v2 family compared to Caché 2013.1 on the Intel® Xeon® processor E5 family

Overview

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.

Abstract

A global provider of mobile telecommunications software tested the performance of InterSystems Caché and Oracle as the database in a simulated data mart application. They found Caché to be 41% faster than Oracle at building a data mart. When testing the response time to SQL queries of the data mart, Caché's performance ranged from 1.8 times to 513 times faster than Oracle.

Introduction

Introduction

With the maturation and wide acceptance of Java, object-oriented programming has moved to the foreground of the application development landscape. Because of their rich data models and support for productivity-enhancing concepts such as encapsulation, inheritance, and polymorphism, object technologies like Java, C++, and COM, are favored by today's application developers.

Introduction

Experts estimate that 85% of all data exists in unstructured formats – held in e-mails, documents (contracts, memos, clinical notes, legal briefs), social media feeds, etc. Where structured data typically accounts for quantitative facts, the more interesting and potentially more valuable expert opinions and conclusions are often hidden in these unstructured formats. And with massive volumes of text being generated at unprecedented speed, there’s very little chance this information can be made useful without some process of synthesis or automation.

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?