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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.

Article
· Jul 26, 2017 3m read
What is APM?

What is APM?

I am talking about Application Performance Management at global summit, and several people have asked what that means so it is time for a bit of an explanation.

APM or Application Performance Management (sometimes referred to as Application Performance Monitoring) has a very good (if complicated) explanation on Wikipedia but to me it just means looking at performance from the users’ point of view and the level of service provided to them.

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Article
· Jul 7, 2017 19m read
Indexing of non-atomic attributes

Quotes (1NF/2NF/3NF)ru:

Every row-and-column intersection contains exactly one value from the applicable domain (and nothing else).
The same value can be atomic or non-atomic depending on the purpose of this value. For example, “4286” can be
  • atomic, if its denotes “a credit card’s PIN code” (if it’s broken down or reshuffled, it is of no use any longer)
  • non-atomic, if it’s just a “sequence of numbers” (the value still makes sense if broken down into several parts or reshuffled)

This article explores the standard methods of increasing the performance of SQL queries involving the following types of fields: string, date, simple list (in the $LB format), "list of <...>" and "array of <...>".

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In the previous parts (1, 2) we talked about globals as trees. In this article, we will look at them as sparse arrays.

A sparse array - is a type of array where most values assume an identical value.

In practice, you will often see sparse arrays so huge that there is no point in occupying memory with identical elements. Therefore, it makes sense to organize sparse arrays in such a way that memory is not wasted on storing duplicate values.

In some programming languages, sparse arrays are part of the language - for example, in J, MATLAB. In other languages, there are special libraries that let you use them. For C++, those would be Eigen and the like.

Globals are good candidates for implementing sparse arrays for the following reasons:

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Globals, these magic swords for storing data, have been around for a while, but not many people can use them efficiently or know about this super-weapon altogether.

If you use globals for tasks where they truly shine, the results may be amazing, either in terms of increased performance or dramatic simplification of the overall solution (1, 2).

Globals offer a special way of storing and processing data, which is completely different from SQL tables. They were first introduced in 1966 in the M(UMPS) programming language, which was initially used in medical databases. It is still used in the same way, but has also been adopted by some other industries where reliability and high performance are top priorities: finance, trading, etc.

Later M(UMPS) evolved into Caché ObjectScript (COS). COS was developed by InterSystems as a superset of M. The original language is still accepted by developers' community and alive in a few implementations. There are several signs of activity around the web: MUMPS Google group, Mumps User's group), effective ISO Standard, etc.

Modern global based DBMS supports transactions, journaling, replication, partitioning. It means that they can be used for building modern, reliable and fast distributed systems.

Globals do not restrict you to the boundaries of the relational model. They give you the freedom of creating data structures optimized for particular tasks. For many applications reasonable use of globals can be a real silver bullet offering speeds that developers of conventional relational applications can only dream of.

Globals as a method of storing data can be used in many modern programming languages, both high- and low-level. Therefore, this article will focus specifically on globals and not the language they once came from.

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Have you ever thought about leveraging IIS (Internet Information Services for Windows) to improve performance and security for your Caché web applications?
Are you worried about the complexity of properly setting up IIS?

See the webinar Configuring a Web Server presented by @Kyle.Baxter, InterSystems Senior Support Specialist. Learn how to install IIS, set up it up to work with the CSP Gateway, and configure the CSP Gateway to talk to Caché.

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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

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I have been asked to assist in the planning of the a new server for our database, which we will be changing operating systems from OpenVMS to Linux (RedHat distribution). However, its difficult to find material regarding what would be recommended, which is likely due to the database being proprietary.

In looking at the information provided below and hoping to decrease processing time, would anyone be able to recommend type of configuration we should have for the new Linux server? Please feel free to ask any clarifying questions.

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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.

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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.

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If I were trying to access an index of a global variable, what time complexity would this operation have? My understanding of languages like Java/C++ is that arrays are stored as blocks of memory so that x[15] would have a lookup time complexity of O(1) because it just goes to (address of the array + 15) and retrieves the value stored there.

How does this work in Cache where the index of a variable isn't necessarily an integer value? If I were to have a variable like the following:

x("Adam") = "Red"

x("George") = "Blue"

x("Bryan") = "Green"

etc...

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

Caché Version2010.1
Operating SystemHP OpenVMS 8.4

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.

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Currently, we have an application running in one namespace ("Database B") that has globals and routines mapped to another database ("Database A"). After enforcing clean up on Database A, we found that 90% of the disk is free. We would like to compact Database A and release the unused space. However, we are running OpenVMS, which seems to be the issue.

For databases consisting of only globals, we are able to use ^GBLOCKCOPY; however, we need to ensure that the routines and mappings are also copied.

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Currently, namespace Alpha is configured to use database AlphaDB as its global database. How would we go about having namespace Alpha configured to use database AlphaDB for its global database except where global ^Customers(CustomerId) has a CustomerId greater than 10M, which we would like to have it redirected to database BetaDB.

In other words, ^|"AlphaDB"|Customers contains all customers between 1 and 10,000,000; and ^|"BetaDB"|Customers contains all customers greater than 10,000,000. Any help would be appreciated.

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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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Hyper-Converged Infrastructure (HCI) solutions have been gaining traction for the last few years with the number of deployments now increasing rapidly. IT decision makers are considering HCI when scoping new deployments or hardware refreshes especially for applications already virtualised on VMware. Reasons for choosing HCI include; dealing with a single vendor, validated interoperability between all hardware and software components, high performance especially IO, simple scalability by addition of hosts, simplified deployment and simplified management.

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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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Myself and the other Technology Architects often have to explain to customers and vendors Caché IO requirements and the way that Caché applications will use storage systems. The following tables are useful when explaining typical Caché IO profile and requirements for a transactional database application with customers and vendors. The original tables were created by Mark Bolinsky.

In future posts I will be discussing more about storage IO so am also posting these tables now as a reference for those articles.

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Article
· May 25, 2016 5m read
Random Read IO Storage Performance Tool

New Tool Available

Please see PerfTools IO Test Suite for a later version of the Random Read IO tool.

Purpose

This tool is used to generate random read Input/Output (IO) from within the database. The goal of this tool is to drive as many jobs as possible to achieve target IOPS and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis.

Open Exchange app
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This post will show you an approach to size shared memory requirements for database applications running on InterSystems data platforms including global and routine buffers, gmheap, and locksize as well as some performance tips you should consider when configuring servers and when virtualizing Caché applications. As ever when I talk about Caché I mean all the data platform (Ensemble, HealthShare, iKnow and Caché).

A list of other posts in this series is here

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