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#Performance

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Performance tag groups posts regarding software performance issues and the best practices on solving and monitoring performance issues.

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.

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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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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.

While some posts are updated to preserve links, others will be marked as strikethrough to indicate that the post is legacy. Generally, I will say, "See: some other post" if it is appropriate.

Capacity Planning and Performance Series

Generally, posts build on previous ones, but you can also just dive into subjects that look interesting.

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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

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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.

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Article
· Sep 30, 2016 1m read
ECP Magic

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

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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

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