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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.

Hello Community,

I recently encountered a issue with Caché and I can't figure out where the problem is coming from.

I noticed that the license limit (200) was reached whenever I was opening my Studio (so it seems). When this occurs, I restart Caché (with the Cube in the Taskbar), and the number of license used is back to 1%, but grows back after. The time taken before the number of license grows back again looks pretty random.

Here is a couple of screenshots :

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There is several classes that allow to create TCP/IP connections (eg: to connect to a service).

Example : %Net.FtpSession (port 21), %Net.HttpRequest (usually port 80 or 443)

AFAIK connection will stay open unless closed explicitly or if variable that hold the instance is garbage collected.

Is there a way to get a list of all active (open) TCP/IP connections IRIS is maintaining so far ?

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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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After what is seemed was weeks, I finally got SSL/TLS enabled on both Apache Web Server and IRIS using the Web Gateway. However while we can now use HTTPS to connect to our Development instance of IRIS, I am running into several errors when I have others try to access the Management Portal via HTTPS.

We are seeing...

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It seems like yesterday when we did a small project in Java to test the performance of IRIS, PostgreSQL and MySQL (you can review the article we wrote back in June at the end of this article). If you remember, IRIS was superior to PostgreSQL and clearly superior to MySQL in insertions, with no big difference in queries.

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Question
· May 21, 2020
why http performance so bad?

Hi,

iris version: IRIS for UNIX (Ubuntu Server LTS for x86-64 Containers) 2019.4 (Build 383U) Fri Dec 6 2019 08:49:54 EST

os: Ubuntu 18.04 LTS

memory: 16G

Disk: 256G SSD

Iris config: default.

soft/hard limit: 65535

I build follow simplest flow to do performance test.

1. create A EnsLib.HTTP.GenericService name it IncomingHTTPService listen on 9980

checked create connection per request

Keepalived = 0

Qsize = 1000

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Hi All,

We have few queries which are simple selects . For simplicity let's say there is a query that joins two tables and gets few columns and both tables have no indexes.

Select Tab1.Field1, Tab2.Field2
From Table1 Tab1
Join Table2 Tab2
On Tab2.FK = Tab1.PK

When we do query plan for this it shows approx 6 million, however if we make a simple adjustment to the query

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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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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?

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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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Running cache 5.0.21 64 bit on Windows server 2016 in virtual environment. Trying to understand why every single process disk read speed (simple sql data walks) caps around ~20MB/s, however 2 paralell such tasks on different data areas can reach 19MB/s each, four - 17MB/s each, that is 70MB/s total, etc. Also simple copy file to nul on that system reach ~400MB/s.

What can keep single query on idle system from reaching for example 200MB/s? Virtualization? Windows? Cache? Processors are below 1-3%

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Our team is reworking an application to use REST services that use the same database as our current ZEN application. One of the new REST endpoints uses a query that ran very slowly when first implemented. After some analysis, we found that an index on one of the fields in the table greatly improved performance (a query that took 35 seconds was now taking a fraction of a second).

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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.

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A customer recently asked if IRIS supported OpenTelemetry as they where seeking to measure the time that IRIS implemented SOAP Services take to complete. The customer already has several other technologies that support OpenTelemetry for process tracing. At this time, InterSystems IRIS (IRIS) do not natively support OpenTelemetry.

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Question
· Nov 5, 2017
TPC-E in Caché

I work in a small development company that uses Caché as a database. In some support cases I have doubts about whether the client's infrastructure environment is not affecting Caché's response time. Reading a bit about comparing installations in different environments, both in production as testing and homologation environments , I understood that the TPC-E is a benchmarking method accepted in the market.

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InterSystems IRIS offers various ways how to profile your code, in most cases it produces enough information to find the places where the most time is spent or where the most global sets. But sometimes it's difficult to understand the execution flow and how it ended at that point.

To solve this, I've decided to implement a way to build a report in a way, so, it's possible to dive by stack down

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If a picture is worth a thousand words, what's a video worth? Certainly more than typing a post.

Please check out my "Coding talks" on InterSystems Developers YouTube:

1. Analysing InterSystems IRIS System Performance with Yape. Part 1: Installing Yape

https://www.youtube.com/embed/3KClL5zT6MY
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Running Yape in a container.

2. Yape Container SQLite iostat InterSystems

https://www.youtube.com/embed/cuMLSO9NQCM
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Extracting and plotting pButtons data including timeframes and iostat.

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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.

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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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Dynamic PoolSize (DPS) Experiment

Purpose:

Enhance Ensemble or IRIS production so it can dynamically allocate pool size for adapter-based components based on their utilization.

Sometimes, an unexpected traffic volume occurs, and default pool size allocated to production components may become a bottleneck. To avoid such situations, I created a demonstrator project some 2 years ago to see, whether it would be possible and feasible to modify production, so it allowed for dynamically modifying its components per their load.

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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.

System Dashboard

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In the context of IKO (Iris Kubernetes Operator) the question of Service not redirecting dynamically to the correct Pod is still pending.
In production this can be dangerous since an overload (or any other simpler problem) can cause you to change the main Pod and leave the application inoperable until we intervene.

Intersystems support warned that this is still an issue of IKO, but there are some possibilities that I am studying.

To explore an idea I had, I would like the help of this Forum to answer the following question:

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