Article
Robert Cemper · May 30, 2019 2m read
Background Jobs over ECP
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.

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Article
Robert Cemper · Mar 26, 2019 2m read
Synchronize Data with DSTIME

 For Data Synchronization inside Caché you have a range of ways to synchronize objects and tables.
At DB level you can use Shadowing  or Mirroring 

This works excellent and if you need just a part of your data to be synchronized you may split your
data into smaller pieces using Global mapping 
Or if you need bi-directional synchronization on Class/Table level you can use the Object Synchronization Feature 


The limit of all these excellent features:
They just work from Caché/IRIS to Caché/IRIS.

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Article
Tony Pepper · May 25, 2016 5m read
Random Read IO Storage Performance Tool

Purpose

This tool is used to generate random read Input/Output (IO) from within the database. The goal of this tool is to drive as many jobs as possible to achieve target IOPS and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis.

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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.

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Article
Eduardo Anglada · May 11 8m read
IRIS in Astronomy

In this article we are going to show the results of the comparision between IRIS and Postgress when handling Astronomy data.

Introduction

Since the earliest days of human civilization we have been fascinated by the sky at night. There are so many stars! Everybody has dreamed about them and fantasized about life in other planets.

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Astronomers’ tools

5 years ago, on December 19, 2013, the ESA launched an orbital telescope called Gaia. Learn more about the Gaia mission on the official website of the European Space Agency or in the article by Vitaly Egorov (Billion pixels for a billion stars).

However, few people know what technology the agency chose for storing and processing the data collected by Gaia. Two years before the launch, in 2011, the developers were considering a number of candidates (see “Astrostatistics and Data Mining” by Luis Manuel Sarro, Laurent Eyer, William O’Mullane, Joris De Ridder, pp. 111-112):

Comparing the technologies side-by-side produced the following results (source):

Technology Time
DB2 13min55s
PostgreSQL 8 14min50s
PostgreSQL 9 6min50s
Hadoop 3min37s
Cassandra 3min37s
Caché 2min25s

The first four will probably sound familiar even to schoolchildren. But what is Caché XEP?

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Mirroring 101

Caché mirroring is a reliable, inexpensive, and easy to implement high availability and disaster recovery solution for Caché and Ensemble-based applications. Mirroring provides automatic failover under a broad range of planned and unplanned outage scenarios, with application recovery time typically limited to seconds. Logical data replication eliminates storage as a single point of failure and a source of data corruption. Upgrades can be executed with little or no downtime.

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At the heart of IRIS and Cache is a very interesting database architecture that we, at M/Gateway Developments, refer to as "Global Storage".  If you ever wanted to know more about the fundamentals and capabilities of this underlying database, you might want to read a major analysis we've put together:

https://github.com/robtweed/global_storage

Amongst other things you'll discover that:

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This text is a continuation of my article where I explained the structure a Caché database. In this article, I described the types of blocks, connections between them and their relation to globals. The article was purely theoretical. I made a project that helps visualize the block tree - and this article will explain how it works in great detail.

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Article
Jorma Sinnamo · Nov 8, 2016 4m read
Returning Disk Space to File Systems

This is the first article in a series discussing how to regain disk space from Caché databases at the operating system level. This introductory article discusses Caché database growth and gives an overview of various methods you can use to return unused disk space that is allocated to database files back to the file system. But before we talk about returning space to the file system, let’s first review how does it get allocated in the first place.

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The following post outlines an architectural design of intermediate complexity for DeepSee. As in the previous example, this implementation includes separate databases for storing the DeepSee cache, DeepSee implementation and settings. This post introduces two new databases: the first to store the globals needed for synchronization, the second to store fact tables and indices.

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在Aix7.1上安装使用root用户安装cache2016.1.1.107,且在安装过程中创建cacheusr用户;更改操作系统上的cacheusr的umask后,通过数据库修改编译后的文件(如,js,csp等)在小机上查看权限不变(-rwxrw-r--  cacheusr cacheusr test.js)。

目的:通过数据库编译后的文件的other用户有读写权限。

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Article
Sergey Kamenev · Nov 11, 2019 11m read
Transactions in Global InterSystems IRIS

InterSystems IRIS supports a unique data structure, called globals, for information storage. Essentially, globals are persistent arrays with multi-level indices, having several extra capabilities—transactions, quick traversal of tree structures, and a programming language known as ObjectScript.

I'd note that for the remainder of the article, or at least the code samples, we'll assume you have familiarised yourself with the basics of globals:

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Article
David Underhill · Jul 12, 2019 2m read
Basic Database Metrics example

This is a self contained class that can be run from the Intersystems Task Scheduler which records peak usage details for databases and licenses built up throughout the day and retaining 30 days history.

To schedule the task to run every hour:  

d ##class(Metrics.Task).Schedule()

You can also specify your own start time, stop time, and run interval:

d ##class(Metrics.Task).Schedule(startTime, stopTime, intervalMins)

Metrics are stored in ^Metrics in the namespace that the class resides in/is run from.

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Article
Nikolay Soloviev · Aug 1, 2019 3m read
Nested set model for ObjectScript

In many projects I was faced with storing hierarchical data (tree) in classes.
By tree, I mean such data, where each node has a parent node — an object of the same class.
Many examples of such data can be given. For example, a catalog in the online store. Suppose that this online store sells books, in this case, the category tree might look like this:

 

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Mirror Outage Procedures

Caché mirroring is a reliable, inexpensive and easy to implement high availability and disaster recovery solution for Caché and Ensemble-based applications. This article provides an overview of recommended procedures for dealing with a variety of planned and unplanned mirror outage scenarios.

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