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


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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While reviewing our documentation for our ^pButtons (in IRIS renamed as ^SystemPerformance) performance monitoring utility, a customer told me: "I understand all of this, but I wish it could be simpler… easier to define profiles, manage them etc.".

After this session I thought it would be a nice exercise to try and provide some easier human interface for this.

The first step in this was to wrap a class-based API to the existing pButtons routine.

I was also able to add some more "features" like showing what profiles are currently running, their time remaining to run, previously running processes and more.

The next step was to add on top of this API, a REST API class.

With this artifact (a pButtons REST API) in hand, one can go ahead and build a modern UI on top of that.

For example -

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Your application is deployed and everything is running fine. Great, hi-five! Then out of the blue the phone starts to ring off the hook – it’s users complaining that the application is sometimes ‘slow’. But what does that mean? Sometimes? What tools do you have and what statistics should you be looking at to find and resolve this slowness? Is your system infrastructure up to the task of the user load? What infrastructure design questions should you have asked before you went into production? How can you capacity plan for new hardware with confidence and without over-spec'ing? How can you stop the phone ringing? How could you have stopped it ringing in the first place?

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Hi Guys,

Can you please advise on the below queries. 

Query 1:

Example 1:

 S a="345",b="arun",c="kumar",d="hi",e="yello",f="orange"

Example 2:

S a="345"

S b="arun"

S c="kumar"

S d="hi"

S e="yello"

S f="orange"

Can you please advise me, which one is performance wise is better. 

Query 2:

Example 1:

S:a=1 R="Arun"

Example 2:

I a=2 R="Arun"

Please advise me, which one is giving better performance in this. 

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David Satorres · Aug 7, 2018
Speeding up $listget


I'm trying to find the faster way to get the data from a class, and I find it very slow compared to traditional globals. So, I hope some of you can bring some light to me :-)

I have thousands of registers in a class, and to access it quickly I'm going with $o at the index. From there, I get the values using $listget(). Something like that:

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In the last post we scheduled 24-hour collections of performance metrics using pButtons. In this post we are going to be looking at a few of the key metrics that are being collected and how they relate to the underlying system hardware. We will also start to explore the relationship between Caché (or any of the InterSystems Data Platforms) metrics and system metrics. And how you can use these metrics to understand the daily beat rate of your systems and diagnose performance problems.

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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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Globals, these magic swords for storing data, have been around for a while, but not many people can use them efficiently or know about this super-weapon altogether.

If you use globals for tasks where they truly shine, the results may be amazing, either in terms of increased performance or dramatic simplification of the overall solution (1, 2).

Globals offer a special way of storing and processing data, which is completely different from SQL tables. They were first introduced in 1966 in the M(UMPS) programming language, which was initially used in medical databases. It is still used in the same way, but has also been adopted by some other industries where reliability and high performance are top priorities: finance, trading, etc.

Later M(UMPS) evolved into Caché ObjectScript (COS). COS was developed by InterSystems as a superset of M. The original language is still accepted by developers' community and alive in a few implementations. There are several signs of activity around the web: MUMPS Google group, Mumps User's group), effective ISO Standard, etc.

Modern global based DBMS supports transactions, journaling, replication, partitioning. It means that they can be used for building modern, reliable and fast distributed systems.

Globals do not restrict you to the boundaries of the relational model. They give you the freedom of creating data structures optimized for particular tasks. For many applications reasonable use of globals can be a real silver bullet offering speeds that developers of conventional relational applications can only dream of.

Globals as a method of storing data can be used in many modern programming languages, both high- and low-level. Therefore, this article will focus specifically on globals and not the language they once came from.

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The following steps show you how to display a sample list of metrics available from the /api/monitor service.

In the last post, I gave an overview of the service that exposes IRIS metrics in Prometheus format. The post shows how to set up and run IRIS preview release 2019.4 in a container and then list the metrics.

This post assumes you have Docker installed. If not, go and do that now for your platform :)

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I want to process more requests per second in Ensemble 2015 (soap service). My problem is in a business process that makes a great transformation. I thought that I can put its group size to 4 (the current value is 1), or put 4 business processes and apply, for example, the round-robin algorithm.
Which alternative is better?

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Currently, we have an application running in one namespace ("Database B") that has globals and routines mapped to another database ("Database A"). After enforcing clean up on Database A, we found that 90% of the disk is free. We would like to compact Database A and release the unused space. However, we are running OpenVMS, which seems to be the issue.

For databases consisting of only globals, we are able to use ^GBLOCKCOPY; however, we need to ensure that the routines and mappings are also copied.

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Delab guz · Feb 11
Driver odbc performance


I'm using the InterSystems Iris odbc driver (DriverODBCVer=02.10) to get data from Iris table but it is slow.

Is there any options to improve performance ? Increase the packet size ?

Change to do in odbcinst.ini / odbc.ini to make it quicker ?



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While the integrity of Caché and InterSystems IRIS databases is completely protected from the consequences of system failure, physical storage devices do fail in ways that corrupt the data they store.  For that reason, many sites choose to run regular database integrity checks, particularly in coordination with backups to validate that a given backup could be relied upon in a disaster.

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We don't often use SQL within our org, which is mostly due to the performance issue we experience due to the quantity of data we are reviewing.

Aside from the standard performance measures for non-Caché databases, are there any recommended approaches when querying large tables?

The table would have roughly 50M records, but there are not a finite amount of sub-nodes.

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Guillaume Rongier · Apr 9, 2019 3m read
IRIS/Ensemble as an ETL

IRIS and Ensemble are designed to act as an ESB/EAI. This mean they are build to process lots of small messages.

But some times, in real life we have to use them as ETL. The down side is not that they can't do so, but it can take a long time to process millions of row at once.

To improve performance, I have created a new SQLOutboundAdaptor who only works with JDBC.


Extend EnsLib.SQL.OutboundAdapter to add batch batch and fetch support on JDBC connection.

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we're planning some work on our SQL Query Plan functionality for a future release of InterSystems IRIS and are interested to hear how you're using them today, or what'd keep you from using them. Rather than try and fit everything in a rigid survey, I thought a simple thread on our beloved DC might also reveal some use patterns that we support or could do a better job on.

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Myself and the other Technology Architects often have to explain to customers and vendors Caché IO requirements and the way that Caché applications will use storage systems. The following tables are useful when explaining typical Caché IO profile and requirements for a transactional database application with customers and vendors.  The original tables were created by Mark Bolinsky.

In future posts I will be discussing more about storage IO so am also posting these tables now as a reference for those articles. 

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Hyper-Converged Infrastructure (HCI) solutions have been gaining traction for the last few years with the number of deployments now increasing rapidly. IT decision makers are considering HCI when scoping new deployments or hardware refreshes especially for applications already virtualised on VMware. Reasons for choosing HCI include; dealing with a single vendor, validated interoperability between all hardware and software components, high performance especially IO, simple scalability by addition of hosts, simplified deployment and simplified management.

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Hello Community,

I recently encountered a issue with Caché and I can't figure out where the problem is coming from.

I noticed that the license limit (200)  was reached whenever I was opening my Studio (so it seems). When this occurs, I restart Caché (with the Cube in the Taskbar), and the number of license used is back to 1%, but grows back after.  The time taken before the number of license  grows back again looks pretty random.

Here is a couple of screenshots :

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Can someone direct me to where in the documentation we can find how consumption may be calculated for global storage?

Caché Version2010.1
Operating SystemHP OpenVMS 8.4

EDIT: After receiving some responses, it seems I was unclear in my initial inquiry. I am looking to determine our rate of consumption of storage; however, I am having some difficulty in doing that.

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