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.

Hello IRIS Community,

Could anyone please explain why Caché has a %STARTSWITH function while it supports ANSI SQL "LIKE"?

thank you very much.

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. 

A list of other posts in this series is here
 

Since Caché 2017 the SQL engine has included new set of statistics. These record the number of times a query is executed and the time it takes to run.

This is a gold mine for anyone monitoring and trying to optimize the performance of an application that includes many SQL statements but it isn’t as easy to access the data as some people want.

This article and the associated sample code explains how to use this information and how to routinely extract a summary of daily statistics and keep a historic record of the SQL performance of your application.

What is recorded?

Hello,

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 ?

Thanks

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.

I am surprised with the performance (poor) of Native API for .NET

       Following code (where ^testGlobal,node1 has 50 records) takes 5 seconds to run.  Anyone else think there is room for the improvement? 

One of my colleagues had developed an interface in Health Connect (HealthShare 2019.1) to add large amounts of data to an external SQL Server database. The data comes from many text files with delimited rows and data for one table per file. There is a business process to read a file line by line and send an Insert Request to an operation. The request contains an Insert statement like ‘Insert into TABLE columns (col1, col2, … colZ) values (val1, val2, … valZ).’ The Health Connect operation utilizes Outbound SQL Adapter to insert one row into a table per request. You can probably imagine this

When looking at system performance and capacity planning I need to know what processors a server is running.

In ^SystemPerformance Linux systems report Intel processors explicitly, for example:

processor	: 0
vendor_id	: GenuineIntel
cpu family	: 6
model		: 79
model name	: Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30GHz
stepping	: 1
microcode	: 0xffffffff
cpu MHz	: 2294.685

Its pretty obvious this is a Broadwell E5-2673 v4 processor, and I can get the specifications and enough details to look at the SPECint rating and other information, for example:

Intel reference

I use the following code to start a start a job :

Class MyClass Extends (...)
{
    ClassMethod Foo()
    {
       job $CLASSMETHOD("MyClass","MyMethod") //take forever depending hardware
    }

    ClassMethod MyMethod()
    {
       //do database related stuff
    }
}

On local environment, calling Foo() is instantaneous (a few ms). On production/test servers (which have much better hardware than local) calling this function is slow and take between 200 ms to 800 ms. Obviously starting a new job with "job" command take lot of time on those environments.

I would like to know if an encrypted caché database can run significantly slower than a normal "unencrypted" database, in a way that is noticeable to the end user (e.g. slower response time for most pages, especially the ones that rely on read/writing to globals).

I searched in Intersystems knowledge base and couldn't find anything related. I'm looking for possible before/after benchmarks.

Like hardware hosts, virtual hosts in public and private clouds can develop resource bottlenecks as workloads increase. If you are using and managing InterSystems IRIS instances deployed in public or private clouds, you may have encountered a situation in which addressing performance or other issues requires increasing the capacity of an instance's host (that is, vertically scaling).

Hello everyone!

Some time ago, I changed the configuration in SQL Runtime Statistic to "Turn on Stats code generation to gather stats at the Open and Close of a query". With this change, the CACHE base (cache/mgr/cache/) has grown a lot to reach 198GB.

Yesterday, I returned the configuration of SQL Runtime Statistic to the default which is "Turn off Stats code generation" and the cache base is no longer growing.

My question is?

How to delete this data that was created in the CACHE base (cache/mgr/cache/) and what data I can delete without affecting the system.

Thanks,
Fábio Louly.

We are seeing more and more customers being lured with latest infrastructure technologies, particularly Composable Infrastructure. Coming with all sorts of data center consolidations and costs savings.

Question is: are there any concerns for HealthShare/TrakCare being run on these platforms or things to look out for? Anyone out there, already on these platforms?

To be more specific this is HPe Synergy with 480 Compute blades booting as bare metal.

Regards;

Anzelem.

Want to perform SNMP performance monitoring of cache2010 on AIX 5.3. Since the SNMP service that comes with AIX does not support agentX, it cannot extend the support for cache database. Therefore, I plan to deploy net-snmp on AIX first, then enable agentX, and finally configure cache's subagent. Is this workable? Any documents? Thx!

AWS launched their first generation of Amazon EC2 A1 instances last year, powered by Arm-based AWS Graviton processors. At AWS re:Invent 2019, Amazon announced the second-generation AWS Graviton2 processors and associated Amazon EC2 M6g instance type, boasting up to 40% better price performance over current generation Intel Xeon based M5 instances.

Introduction

InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging.

New Tool Available

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

Purpose

Dynamic PoolSize (DPS) Experiment

Purpose:

Enhance Ensemble or IRIS production so it can dynamically allocate pool size for adapter-based components based on their utilization.

Sometimes, an unexpected traffic volume occurs, and default pool size allocated to production components may become a bottleneck. To avoid such situations, I created a demonstrator project some 2 years ago to see, whether it would be possible and feasible to modify production, so it allowed for dynamically modifying its components per their load.

Hi Community!

We're pleased to invite you to the upcoming "Speed Test: ESG Labs Database Performance Test" webinar on August 5 at 9:30 AM EDT!

Join our live webinar with Mike Leone, senior analyst with Enterprise Strategy Group’s Validation Services, to learn about a speed test that measures and compares the concurrent real-time data ingest and query performance of InterSystems IRIS^® data platform, a leading in-memory database, a cloud relational database, and a traditional relational database. 

 Hi Community:

Watch your inboxes for our latest issues of Developments and Developments Healthcare Edition.

Running cache 5.0.21 64 bit on Windows server 2016 in virtual environment. Trying to understand why every single process disk read speed (simple sql data walks) caps  around ~20MB/s, however 2 paralell such tasks on different data areas can reach 19MB/s each, four - 17MB/s each, that is 70MB/s total, etc. Also simple copy file to nul on that system reach ~400MB/s.

What can keep single query on idle system from reaching for example 200MB/s? Virtualization? Windows? Cache? Processors are below 1-3%

AWS has officially released their second-generation Arm-based Graviton2 processors and associated Amazon EC2 M6g instance type, which boasts up to 40% better price performance over current generation Intel Xeon based M5 instances. 

A few months ago, InterSystems participated in the M6g preview program, and we ran a few benchmarks with InterSystems IRIS that showed compelling results. This led us to support ARM64 architectures for the first time.

Hi Community! I need your advice.

The method below is 6 times slower on production server than on developing machine:

ClassMethod runme4()
{
    s cnt=615210
    s st=$zh
    for i=1:1:cnt {
        s p=##class(digi.packet).%OpenId("packet||5237")
        w:p="" "not found",!
        k p
    }
    w $zh-st,!
}

BUT the server is 6 times faster if OpenId replaced with simple read of a large global (s p=^someLargeGlobal). Any ideas what makes OpenId so slow only on the server?

A More Industrial-Looking Global Storage Scheme

In the first article in this series, we looked at the entity–attribute–value (EAV) model in relational databases, and took a look at the pros and cons of storing those entities, attributes and values in tables. We learned that, despite the benefits of this approach in terms of flexibility, there are some real disadvantages, in particular a basic mismatch between the logical structure of the data and its physical storage, which causes various difficulties.

Hi, 

iris version: IRIS for UNIX (Ubuntu Server LTS for x86-64 Containers) 2019.4 (Build 383U) Fri Dec 6 2019 08:49:54 EST

os: Ubuntu 18.04 LTS

memory: 16G

Disk: 256G SSD

Iris config: default.

soft/hard limit: 65535

I build follow simplest flow to do performance test.

1. create A EnsLib.HTTP.GenericService name it IncomingHTTPService listen on 9980

checked create connection per request

Keepalived = 0

Qsize = 1000

2. create A EnsLib.HTTP.GenericOperation name it OutgoingHTTPOperator to connect localhost:8080(it's a nginx server serve a static html page)

Note (October 2022): yape has been deprecated and replaced by YASPE, there is no more development on yape.

Note (June 2019): A lot has changed, for the latest details go here

Note (Sept 2018): There have been big changes since this post first appeared, I suggest using the Docker Container version, the project and details for running as a container are still in the same place  published on GitHub so you can download, run - and modify if you need to.

Previously I showed you how to run pButtons to start collecting performance metrics that we are looking at in this series of posts.

• Part 1 - Getting started on the Journey, collecting metrics
• Part 2 - Looking at the metrics we collected

Since this post was written several years ago, we have moved from Caché to IRIS. See the comments for an updated link to the documentation for pButtons (Caché) and SystemPerformance (IRIS). Also, a note on how to update your systems to the latest versions of the performance tools.

Introduction

In the first article in this series, we’ll take a look at the entity–attribute–value (EAV) model in relational databases to see how it’s used and what it’s good for. Then we'll compare the EAV model concepts to globals.

Sometimes you have objects with an unknown number of fields, or perhaps hierarchically nested fields, for which, as a rule, you need to search.