#Performance

Please excuse my ignorance. I am trying to identify what areas would be best to review in the System Dashboard (for Cache 2010.2) for performance issues with the database. It seems to be running slower than usual, but I am trying to find out the best way to go about identifying what the issue is.

The following are captures from the System Dashboard.

As always, thanks a lot for your help.

Is there a difference in outcome between the two screengrabs below?

In both cases, when certain conditions are met, a transformation is called and the output sent on to two targets. In the first case we surmise the transformation is called twice, and the output of the first run sent to the first target, the output of the second run to the second target. In the second case we surmise the transformation is called once, and the output duplicated and sent to the two targets.

Hi Community! I need your advice.

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

Currently, we are receiving an alert that states, "Write Daemon still on pass 31". It's been that way for a few hours.

I was wondering if it is possible to identify what the WD has left to work on so that we can see how we can reduce this and possibly identify if there are issues with the way something is written.

Thanks in advance for any insight.

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

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.

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.

Hi,

Has anyone got any experience of using the Microsoft diskspd utility to test the storage infrastructure in Healthshare/Ensemble environment.

I am interested in getting some figures to highlight any issues with different approaches to provisioning the disks on our new environment.

I am at a loss as to what parameters I should use to give a reasonable synthetic load that will give me any indication of potential issues. Any pointers would be greatly appreciated!

Kind Regards,

Jason

Any recommendations, to this VMware disk type debate, with Cache installations in particular?

Thick Provision Lazy Zeroed

Thick Provision Eager Zeroed

Thin Provision

Hi,

If I test the Native api for Node.js from the documentation, I noticed (if I'm correct) all methods and calls are synchronous. By default due to the nature of Node.js, there is only one thread of execution and normally all JavaScript methods and all calls should be asynchronous and use either a callback function (the "old way") or promises or the async/await contruct to return their result, e.g.:

Suppose we need to store millions of values temporarily, that means, we don't care about them if we lose them but our application use them to get realtime information. Should I use Cachetemp or whatever other DB without journaling enabled? If answer is Cachetemp, shouldn't be a problem if we decide to scale using App Server + ECP? I'm not sure what would happen with the app logic in such architecture as I guess I couldn't map and share cachetemp...

Any idea/suggestion?

Cache version: Cache for Windows (x86-64) 2017.2.1 (Build 801_3U)

Good Afternoon,

I have a co-worker who is trying to run the below query via ODBC. The issue is that the query appears to be running extremely slow (nearly 2 hours).

I am designing the software architecture for an Ensemble/Healthshare production to be deployed on Amazon AWS EC2 servers (2 mirrored m4.large - 4 vCPUs / 16 GiB RAM running RedHat Linux 3.10.0-327.el7.x86_64 and Healthshare for RHEL 64-bit 2016.2.1). It's a rather CPU-intensive production involving massive XSLT 2.0 transformations (massive both in terms of size and volume). I was wondering if anyone has experience configuring Ensemble productions on EC2 servers. My question or concern has to do with the following statement in the Ensemble documentation:

Hello everyone,

Recently, I've been working on a Business Process that processes a large JSON FHIR message containing up to 50k requests in an array within the JSON.

Currently, the code imports the JSON as a dynamic object from the original message stream, obtains an iterator from it, and processes each request one at a time in a loop.

Hello everyone,

I’m facing issues with replicating data from my Caché 2016 database to a PostgreSQL database. I need to handle around 300 data updates per minute, and whenever certain tables are modified, those changes must be reflected in other databases.

So far, I’ve tried various approaches, including: