Setting the TZ Environment Variable on Linux

The Update Checklist for v2015.1 recommends setting the TZ environment variable on Linux platforms and points to the manpage for tzset. This is recommended to improve the performance of Cache’s time-related functions. You can find out more about this here:

https://community.intersystems.com/post/linux-tz-environment-variable-not-being-set-and-impact-caché

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What is a core file? and When are they use­ful?

The in­for­ma­tion in this doc­u­ment is cur­rent as ver­sions of In­ter­Sys­tems prod­ucts re­leased through 2019–06–30. This up­date cov­ers er­rors in that have been dis­cov­ered up to 2020–04–14, but not changes present in new ver­sions of In­ter­Sys­tems prod­ucts.

Nev­er­the­less, the de­tails for ex­ist­ing prod­ucts are not sub­ject to fre­quent change.

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Date range queries going too slow for you?  SQL Performance got you down?  I have one weird trick that might just help you out! (SQL Developers hate this!)*

If you have a class that records timestamps when the data is added, then that data will be in sequence with your IDKEY values - that is, TimeStamp< TimeStampif and only if ID1 < IDfor all IDs and TimeStamp values in table - then you can use this knowledge to increase performance for queries against TimeStamp ranges.  Consider the following table:

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Intro

 

Please note, this article is considered deprecated, check out the new revision over here: https://community.intersystems.com/post/tutorial-websockets

The goal of this post is to discuss working with Websockets in a Caché environment. We are going to have a quick discussion of what websockets are and then talk through an example chat application implemented on top of Websockets.

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This time I want to talk about something not specific to InterSystems IRIS, but that I think is important if you want to work with Docker and your server at work is a PC or laptop with Windows 10 Pro or Enterprise.

As you likely know, containers technology comes basically from Linux world and, nowadays, is on Linux hosts were it shows maximum potential. Those who use Windows on a normal basis see that both, Microsoft and Docker, have done important efforts during these last years that allow us to run containers based on Linux images on our Windows system in a really easy way... but it's something not supported for production systems and, this is the big problem, is not reliable if we want to keep persistent data outside of containers, in the host system,... mostly due to the big differences between Windows and Linux file systems. In the end, Docker for Windows itself uses a small linux virtual machine (MobiLinux) to run the containers... it does it transparently for the windows user... and it works perfectly well if, as I said, you don't require that your databases survive longer than the container...

Well,...let's get to the point,... the point is that many times, to avoid issues and simplify, we need a full Linux system and, if our server is based on Windows, the only way of having it is through a virtual machine. At least till WSL2 in Windows is released, but that will be another story and sure it'll take a bit of time to become robust enough.

In this article, I'll tell you, step by step, how to install an environment where you'll be able to work, if you need it, with Docker containers on an Ubuntu system in your Windows server. Let's go...

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Here are a few examples of conversions and operations you might need, along with links to documentation where you can learn more.

At the time I wrote this, Eastern Daylight Time was in effect for my Caché system.

How Caché keeps the time and date

Caché has a simple time format, with a longer range of recognized dates compared to some other technologies.

The current time is maintained in a special variable $HOROLOG ($H):

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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Article
Mikhail Khomenko · 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.

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The Caché System Management Portal includes a robust web-based SQL query tool, but for some applications it’s more convenient to use a dedicated SQL client installed on a user’s PC.

SQuirreL SQL is a well known open source SQL client built in Java, which uses JDBC to connect to a DBMS. As such, we can configure SQuirreL to connect to Caché using the Caché JDBC driver.

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This article will describe and include an example of how to embed an external PDF file into an HL7 segment, specifically ADT_A01:2.3.1 OBX().  This can be useful when attempting to insert pictures or other external data into an HL7 message.  In this example, the name of the PDF file to be embedded is provided in the incoming HL7 message in OBX(1):ObservationValue field.

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This post will show you an approach to size shared memory requirements for database applications running on InterSystems data platforms including global and routine buffers, gmheap, and locksize as well as some performance tips you should consider when configuring servers and when virtualizing Caché applications. As ever when I talk about Caché I mean all the data platform (Ensemble, HealthShare, iKnow and Caché).


A list of other posts in this series is here

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In this post I show strategies for backing up Caché using External Backup with examples of integrating with snapshot based solutions. The majority of solutions I see today are deployed on Linux on VMware so a lot of the post shows how solutions integrate VMware snapshot technology as examples.

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The topic of for/while loop performance in Caché ObjectScript came up in discussion recently, and I'd like to share some thoughts/best practices with the rest of the community. While this is a basic topic in itself, it's easy to overlook the performance implications of otherwise-reasonable approaches.

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Enterprises need to grow and manage their global computing infrastructures rapidly and efficiently while simultaneously optimizing and managing capital costs and expenses. Amazon Web Services (AWS) and Elastic Compute Cloud (EC2) computing and storage services meet the needs of the most demanding Caché based application by providing
 a highly robust global computing infrastructure.

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There are often questions surrounding the ideal Apache HTTPD Web Server configuration for HealthShare.  The contents of this article will outline the initial recommended web server configuration for any HealthShare product. 

As a starting point, Apache HTTPD version 2.4.x (64-bit) is recommended.  Earlier versions such as 2.2.x are available, however version 2.2 is not recommended for performance and scalability of HealthShare.

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Article
Daniel Kutac · Feb 11, 2019 4m read
Using Oauth2 with SOAP (Web)Services

Hi guys,

 

Couple days ago, a customer approached me with the wish to enhance their existing legacy application, that uses SOAP (Web)Services so it shares the same authorization with their new application API based on REST. As their new application uses OAuth2, the challenge was clear; how to pass access token with SOAP request to the server.

After spending some time on Google, it turned out, that one of possible ways of doing so was adding an extra header element to the SOAP envelope and then making sure the WebService implementation does what is needed to validate the access token.

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So, one day you're working away at WidgetsDirect, the leading supplier of widget and widget accessories, when your boss asks you to develop the new customer facing portal to allow the client base to access the next generation of Widgets..... and he wants you to use Angular 1.x to read into the department's Caché server.   

There's only one problem:  You've never used Angular, and don't know how to make it talk to Caché.

This guide is going to walk through the process of setting up a full Angular stack which communicates with a Caché backend using JSON over REST.  

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Article
Eduard Lebedyuk · Feb 5, 2016 11m read
Class Queries in InterSystems IRIS

Class Queries in InterSystems IRIS (and Cache, Ensemble, HealthShare) is a useful tool that separates SQL queries from Object Script code. Basically, it works like this: suppose that you want to use the same SQL query with different arguments in several different places.In this case you can avoid code duplication by declaring the query body as a class query and then calling this query by name. This approach is also convenient for custom queries, in which the task of obtaining the next row is defined by a developer. Sounds interesting? Then read on!

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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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I am often asked by customers, vendors or internal teams to explain CPU capacity planning for large production databases running on VMware vSphere.

In summary there are a few simple best practices to follow for sizing CPU for large production databases:

  • Plan for one vCPU per physical CPU core.
  • Consider NUMA and ideally size VMs to keep CPU and memory local to a NUMA node.
  • Right-size virtual machines. Add vCPUs only when needed.

Generally this leads to a couple of common questions:

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This post provides guidelines for configuration, system sizing and capacity planning when deploying Caché 2015 and later on a VMware ESXi 5.5 and later environment.

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I wanted to write it as a comment to article of @Evgeny Shvarov . But it happens to be so long, so, decided to post it separately.

Image result for docker clean all images

I would like to add a bit of clarification about how docker uses disk space and how to clean it.  I use macOS, so, everything below, is mostly for macOS, but docker commands suit any platform.

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