The MONITOR process (also called the Caché Monitor) scans the messages in your cconsole.log file and sends you emails based on the severity of those messages. The MONITOR is configured using the ^MONMGR utility in terminal.

The MONITOR should not be confused with the similarly named System Monitor, which checks a variety of system health and performance metrics and can log messages regarding them to the cconsole.log, where they can then be scanned by the MONITOR.

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DTL Transformations and GetValueAt/SetValueAt calls on HL7 messages will truncate any fields longer than 32K. To avoid this, the methods GetFieldStreamRaw and StoreFieldStreamRaw must be used when dealing with fields that might be larger than 32K. OBX:5 is a frequent example. These methods have some subtleties and must be used carefully.

This can't be done by simply dragging from left to right in a DTL. It must be done with a code action. Also, the StoreFieldStreamRaw call must be the last edit made to the segment because the segment becomes immutable after that.

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Created by Daniel Kutac, Sales Engineer, InterSystems

Warning: if you get confused by URLs used: the original series used screens from machine called dk-gs2016. The new screenshots are taken from a different machine. You can safely treat url WIN-U9J96QBJSAG as if it was dk-gs2016.

Part 2. Authorization server, OpenID Connect server

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Article
· Mar 3, 2016 2m read
Class Projections and Projection Classes

The purpose of this post is to raise the profile of a powerful mechanism that has long been available to us, and to open a discussion about ways in which it can be used or abused.

You can read more detail about the mechanism here. To summarize, your class definition can use the Projection keyword to reference one or more projection classes. A projection class can implement methods that get invoked at key points in the lifecycle of your class.

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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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When using Studio, ODBC or a terminal connection to Caché or Ensemble, you may have wondered how to secure the connection. One option is to add TLS (aka SSL) to your connection. The Caché client applications - TELNET, ODBC and Studio - all understand how to add TLS to the connection. They just need to be configured to do it.

Configuring these clients is easier in 2015.1 and later. I'm going to be discussing this new method. If you're already using the old, legacy method, it will continue to work, but I would recommend you consider switching to the new one.

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

New Tool Available

Please see PerfTools IO Test Suite for a later version of the Random Read IO 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.

Open Exchange app
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Article
· 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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Presenter: Anton Umnikov
Task: Identify your slowest SQL queries and tune them for better performance
Approach: Use InterSystems’ query profiling and analysis tools. Discuss how system configuration can affect performance

This session will show you how you identify the weakest link in your application SQL and introduce you to the fine art of tuning those queries. To do this we will take a look at InterSystems query profiling and analysis tools, as well as how system configuration can impact SQL performance.

Problem: Obscurity on how our SQL engine works

Content related to this session, including slides, video and additional learning content can be found here.

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Article
· Oct 7, 2016 4m read
Forwarding Requests in a REST Service

One useful feature of our REST framework is the ability for a dispatch class to identify request prefixes and forward them to another dispatch class. This approach of modularizing your URL map will improve code readability, enable you to easily maintain separate versions of an interface, and provide a means to protect API calls that only certain users will be allowed to access.

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Let's say we have two serial classes, one as a property of another:

Class test.Serial Extends %SerialObject
{
Property Serial2 As test.Serial2;
}

Class test.Serial2 Extends %SerialObject
{
Property Property As %String;
}

And a persistent class, that has a property of test.Serial type:

Class test.Persistent Extends %Persistent
{

Property Datatype As %String;

Property Serial As test.Serial;

}

So it's a serial, inside a serial, inside a persistent object.

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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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One of the topics that comes up often when managing Ensemble productions is disk space:

The database (the CACHE.DAT file) grows in a rate that was unexpected; or the Journal files build up at a fast pace; or the database grows continuously though the system has a scheduled purge of the Ensemble runtime data.

It would have been better if these kind of phenomena would have been observed and accounted for yet at the development and testing stage rather than on a live system.

For this purpose I created a basic framework that could aid in this task.

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Hi!

I believe the simplest is (to work with csv delimited by ";"):


set file = ##class(%File).%New( "data.csv" )
    set sc = file.Open( "R" ) 
    if $$$ISERR(sc) quit    ; or do smth

    while 'file.AtEnd {
        set str=file.ReadLine() 
        for i=1:1:$length( str, ";" ) {
            set id=$piece( str, ";" ,i ) 
            write !, id  // or do smth
        }
    }
    do file.Close()

Possible options:

different variants of error handling with sc code.

Embrace while loop into try/catch block.

And what's yours?

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This post provides further detail on the suggestions from the DeepSee Troubleshooting Guide about what to do if a user is not able to view a listing in a DeepSee cube, but instead sees errors like this:

ERROR #5540: SQLCODE: -99 Message: User <username> is not privileged for the operation [zfindStatement+118^%SQL.DynamicStatement.1:<namespace>] (8)

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Article
· May 16, 2016 11m read
Accelerate Ensemble

Introducing non-persistent messages. eXpert-to-eXpert

Background

InterSystems Ensemble as a tool does a lot for the Developer. One of the nice features is the Message trace utility. It shows a message flow diagram. The diagram shows the progress of the message processing real time. You can get many-many useful information from the production. In any case, someone needs to find a bug in a production implementation, without the Message trace utility it could turn into a real nightmare.

On the other hand, keeping message “traceability” is not for free. A heavy loaded production can very quickly run out of resources just because of the house keeping functions of Ensemble. House keeping functions such as maintaining message header, log entries, message queue generates a significant load on the Caché database used by Ensemble.

This article is about to show how to force Ensemble work more for the everyday life, instead of being prepared for “any-time-debugging”.

This is an eXpert-to-eXpert article. Therefore, I assume the deep understanding of Ensemble.

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This week I am going to look at CPU, one of the primary hardware food groups :) A customer asked me to advise on the following scenario; Their production servers are approaching end of life and its time for a hardware refresh. They are also thinking of consolidating servers by virtualising and want to right-size capacity either bare-metal or virtualized. Today we will look at CPU, in later posts I will explain the approach for right-sizing other key food groups - memory and IO.

So the questions are:

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This article will provide tips and tricks on customizing Ensemble business hosts with configurable settings.

Ensemble production Settings are configurable values that control the behavior of a production and its hosts.

The documentation for adding and removing Settings and specifying categories and controls for Settings is provided at the link:

http://docs.intersystems.com/latest/csp/docbook/DocBook.UI.Page.cls?KEY=EGDV_prog#EGDV_prog_settings

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