While I can see the benefits that $ZSTORAGE could have if used properly, I have not seen it used in the environments I have worked in. I was wondering if there are any developers that promote its usage.

If used properly, I would imagine it could be highly effective in maximizing free memory since some processes will never go over X amount, while others may very well need much more.

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.

While utilizing ^%GSIZE, which is used by the %GlobalEdit class, the results appeared odd. I have provided my results below, which illustrate the global structure on the left and the usage indicated by ^%GSIZE on the right.

I was benchmarking the populate utils when I noticed something strange. Consider this simple benchmarking method:

ClassMethod runBench(count As %Integer = 300000)
{
		s types=["name","ssn","company","title","phone","city","street","zip","mission","state","color","product","string","integer","float"]
		//s types=["name","ssn"]
		s iter=types.%GetIterator()
		while iter.%GetNext(.key,.value){
			s start=$P($ZTS,",",2)
			s opt={}
			s opt.type=value
			for i=1:1:count{
				s res=##class(DataGen.Generator).

One of the great availability and scaling features of Caché is Enterprise Cache Protocol (ECP). With consideration during application development distributed processing using ECP allows a scale out architecture for Caché applications. Application processing can scale to very high rates from a single application server to the processing power of up to 255 application servers with no application changes.

ECP was used widely for many years in TrakCare deployments I was involved in. A decade ago a 'big' x86 server from one of the major vendors might only have a total of eight cores.

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.

Index

This is a list of all the posts in the Data Platforms’ capacity planning and performance series in order. Also a general list of my other posts. I will update as new posts in the series are added.

You will notice that I wrote some posts before IRIS was released and refer to Caché. I will revisit the posts over time, but in the meantime, Generally, the advice for configuration is the same for Caché and IRIS. Some command names may have changed; the most obvious example is that anywhere you see the ^pButtons command, you can replace it with ^SystemPerformance.

A short post for now to answer a question that came up. In post two of this series I included graphs of performance data extracted from pButtons. I was asked off-line if there is a quicker way than cut/paste to extract metrics for mgstat etc from a pButtons .html file for easy charting in Excel.

See: - Part 2 - Looking at the metrics we collected

pButtons compiles data it collects into a single html file to make it easier to send to WRC and review the collated data.

This is a follow-up to Murray's article for scripting pButtons data extraction on Unix/MacOS:     Extracting pButtons data to CSV for UNIX/MacOS

###Extracting pButtons data to a CSV file on Windows

PowerShell scripting was used in this article because it is available by default on Windows platforms.

The script, Extract_pButtons.ps1, will search the given pButtons file until it finds the marker for the beginning of the section. The section will be printed line-by-line, from the header to the line before the section end marker.

It has been noticed that some customers running JAVA programs (for example, FOP) on AIX would see the server eventually running low then out of memory. Customer would notice the system pages heavily and user experience becomes bad. And the server would crash when out of memory.

When the problem happens, we can see in ipcs a lot of shared memory segment marked for deletion (Capital D at the beginning of MODE section). This means they will not disappear until the last process attached to the segment detaches it.

I saw someone recently refer to ECP as magic. It certainly seems so, and there is a lot of very clever engineering to make it work. But the following sequence of diagrams is a simple view of how data is retrieved and used across a distributed architecture.

For more more on ECP including capacity planning follow this link: Data Platforms and Performance - Part 7 ECP for performance, scalability and availability

To start

• There are three globals on disk ^A, ^B and ^C.
• Global ^B equals "B"
• There is one Data server and two or more Application servers.

Date range queries going too slow for you?  SQL Performance got you down?  I have ANOTHER weird trick that SQL Developers don't want you to know!*

Often times support and sales engineers are asked about recent benchmark results on various platforms and large scale configurations.  These will be made available here in the Developer Community in the "Documentation" section, and as an example here's a link to a recent Intel E7 v2 series processor benchmark.

https://community.intersystems.com/documentation/data-scalability-intersystems-caché-and-intel-processors-0

There are several reports available and more will be made available on an on-going basis.