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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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.

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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.

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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.

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I'd like to share with you some storage features that also exist in Caché but are almost 
unknown and mostly not used. They are of course available in IRIS and gain importance
with large and distributed storage architectures.

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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?

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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).

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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.



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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!


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In the context of IKO (Iris Kubernetes Operator) the question of Service not redirecting dynamically to the correct Pod is still pending.
In production this can be dangerous since an overload (or any other simpler problem) can cause you to change the main Pod and leave the application inoperable until we intervene.

Intersystems support warned that this is still an issue of IKO, but there are some possibilities that I am studying.

To explore an idea I had, I would like the help of this Forum to answer the following question:

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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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Dynamic PoolSize (DPS) Experiment



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.

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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. 

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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%

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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.

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alex chang · May 21, 2020
why http performance so bad?


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

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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.

Now you can try InterSystems IRIS and InterSystems IRIS for Health on Graviton2-based Amazon EC2 M6g instances for yourselves through the AWS Marketplace!

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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.

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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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Hi all.

A long time ago I enabled Activity Monitoring to be able to save myself headaches in the future when looking at the performance of various message routes through our productions.  It's served it's purpose of answering questions on how many messages we process a week etc but I had not had the chance to really dig down into the stats for specific message types or destinations to pin point issues.

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