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What if you could serialize/deserialize objects in whatever format: JSON, XML, CSV,...; attending different criteria: export/import some properties and not others, transform values in this or that way before exporting/importing,...; and all of this without having to change the class definition? Wouldn't that be great??

Well, perhaps it's a goal too ambitious to reach 100% but, exploring this idea, I've developed a bunch of classes that I thought it was good to share. If you want to test, change, modify or improve the code, or just take a look at it, you can do it here. There you'll find a more detailed explanation (see Readme.md)

Be aware, this is a proof of concept for myself done in spare times, sure it's not robust enough or it can be done much better... but, I was just playing...ok, I could just wait to the new JSON Adaptor (coming soon!) that sure is going to resolve much more scenarios in a cleaner way, but... meanwhile... :-) ...

Jose-Tomas Salvador's picture
Post by Jose-Tomas Salvador 1 days ago
Last comment 2 hours 17 min ago
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"Telegram" is a well-known instant messenger, which provides an API for creating bots. The features of this API allow you to create bots with a wide range of functionality including receiving payments. 
With the help of the telegram bot, I solved a simple task - sending Alerts from Ensemble to Telegram.

Advantages: Alerts come to the mobile phone, a notification appears, so there is no need to install any additional applications (in contrast to the solution https://community.intersystems.com/post/sending-alerts-mobile-phone-using-pushover- httpoutboundadapter).

The bot can be extended by adding new commands, for example, for managing the Production or for solving other tasks in Iris, Ensemble or Cache.

 

Nikolay Soloviev's picture
Post by Nikolay Soloviev 1 days ago
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** Revised Feb-12, 2018

While this article is about InterSystems IRIS, it also applies to Caché, Ensemble, and HealthShare distributions.

Introduction

Memory is managed in pages.  The default page size is 4KB on Linux systems.  Red Hat Enterprise Linux 6, SUSE Linux Enterprise Server 11, and Oracle Linux 6 introduced a method to provide an increased page size in 2MB or 1GB sizes depending on system configuration know as HugePages.

At first HugePages required to be assigned at boot time, and if not managed or calculated appropriately could result in wasted resources.  As a result various Linux distributions introduced Transparent HugePages with the 2.6.38 kernel as enabled by default.  This was meant as a means to automate creating, managing, and using HugePages.  Prior kernel versions may have this feature as well however may not be marked as [always] and potentially set to [madvise].  

Transparent Huge Pages (THP) is a Linux memory management system that reduces the overhead of Translation Lookaside Buffer (TLB) lookups on machines with large amounts of memory by using larger memory pages.  However in current Linux releases THP can only map individual process heap and stack space.

Mark Bolinsky's picture
Post by Mark Bolinsky 29 January 2016
Last comment 22 February 2017
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