This is the first in a pair of articles on SQL indices.

Part 1 - Know your indices

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:

Here is a snippet that I learned yesterday

You can define an index on a collection property but when I tried to use it, I failed. I was using

     Select ….. where …. :xx %INLIST collproperty

But this will not use an index, but the equivalent syntax

     SELECT .. WHERE ... FOR SOME %ELEMENT(collproperty) (%VALUE=:xx)

will use the index

Check out

http://docs.intersystems.com/latest/csp/docbook/DocBook.UI.Page.cls?KEY=...

There are three things most important to any SQL performance conversation: Indices, TuneTable, and Show Plan. The attached PDFs includes historical presentations on these topics that cover the basics of these 3 things in one place. Our documentation provides more detail on these and other SQL Performance topics in the links below. The eLearning options reinforces several of these topics. In addition, there are several Developer Community articles which touch on SQL performance, and those relevant links are also listed.

There is a fair amount of repetition in the information listed below. The most important aspects of SQL performance to consider are:

1. The types of indices available
2. Using one index type over another
3. The information TuneTable gathers for a table and what it means to the Optimizer
4. How to read a Show Plan to better understand if a query is good or bad

Beginning - see Part 1.

3. Variants of structures when using globals

A structure, such as an ordered tree, has various special cases. Let's take a look at those that have practical value for working with globals.

3.1 Special case 1. One node without branches

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).

YASPE is the successor to YAPE (Yet Another pButtons Extractor). YASPE has been written from the ground up with many internal changes to allow easier maintenance and enhancements.

YASPE functions:

• Parse and chart InterSystems Caché pButtons and InterSystems IRIS SystemPerformance files for quick performance analysis of Operating System and IRIS metrics.
• Allow a deeper dive by creating ad-hoc charts and by creating charts combining the Operating System and IRIS metrics with the "Pretty Performance" option.
• The "System Overview" option saves you from searching your SystemPerformance files for system details or common configuration options.

YASPE is written in Python and is available on GitHub as source code or for Docker containers at:

• https://github.com/murrayo/yaspe

I am often asked to review customers' IRIS application performance data to understand if system resources are under or over-provisioned.

This recent example is interesting because it involves an application that has done a "lift and shift" migration of a large IRIS database application to the Cloud. AWS, in this case.

A key takeaway is that once you move to the Cloud, resources can be right-sized over time as needed. You do not have to buy and provision on-premises infrastructure for many years in the future that you expect to grow into.

Continuous monitoring is required. Your application transaction rate will change as your business changes, the application use or the application itself changes. This will change the system resource requirements. Planners should also consider seasonal peaks in activity. Of course, an advantage of the Cloud is resources can be scaled up or down as needed.

For more background information, there are several in-depth posts on AWS and IRIS in the community. A search for "AWS reference" is an excellent place to start. I have also added some helpful links at the end of this post.

AWS services are like Lego blocks, different sizes and shapes can be combined. I have ignored networking, security, and standing up a VPC for this post. I have focused on two of the Lego block components;
- Compute requirements.
- Storage requirements.

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

What is %SQLRESTRICT

%SQLRESTRICT is a special %FILTER clause for use in MDX queries in InterSystems IRIS Business Intelligence. Since this function begins with %, it means this is a special MDX extension created by InterSystems. It allows users to insert an SQL statement that will be used to restrict the returned records in the MDX Result Set. This SQL statement must return a set of Source Record IDs to limit the results by. Please see the documentation for more information.

Why is this useful?

This is useful because there are often times users want to restrict the results in their MDX Result Set based on information that is not in their cubes. It may be the case that this information may not make sense to be in the cube. Other times this can be useful when there is a large set of values you want to restrict. As mentioned before, this is not a standard MDX function, it was created by InterSystems to handle cases were queries were not performing well or cases that were not easily solved by existing functions.

In last week's discussion we created a simple graph based on the data input from one file. Now, as we all know, sometimes we have multiple different datafiles to parse and correlate. So this week we are going to load additional perfmon data and learn how to plot that into the same graph.
Since we might want to use our generated graphs in reports or on a webpage, we'll also look into ways to export the generated graphs.

It's almost time to get your customers upgraded to new versions - are you worried about showing off your SQL Performance after upgrades? If you want to upgrade without worrying, then I have just the program for you!!! Check out this video from Global Summit 2016 featuring yours truly explaining how to upgrade a system without worrying about pesky SQL queries showing on your waistline!

https://www.youtube.com/watch?v=GfFPYfIoR_g

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.

I attended Cloud Native Security Con in Seattle with full intention of crushing OTEL day, then perusing the subject of security applied to Cloud Native workloads the following days leading up to CTF as a professional excercise. This was happily upended by a new understanding of eBPF, which got my screens, career, workloads, and atitude a much needed upgrade with new approaches to solving workload problems.

So I made it to the eBPF party and have been attending clinic after clinic on the subject ever since, here I would like to "unbox" eBPF as a technical solution, mapped directly to what we do in practice (even if its a bit off), and step through eBPF through my experimentation on supporting InterSystems IRIS Workloads, particularly on Kubernetes, but not necessarily void on standalone workloads.

eBee Steps with eBPF and InterSystems IRIS Workloads