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MariekeGO committed Sep 17, 2024
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2 changes: 0 additions & 2 deletions tutorials/Dashboards_Low_Code_Apps.md
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Expand Up @@ -50,8 +50,6 @@ keywords: low-code, low code, lowcode
| [Creating a duration operator](xref:Creating_Duration_Operator) | Create a custom operator that calculates the duration based on two datetime values. |
| [Optimizing your custom operator](xref:Custom_Operator_Tutorial) | Optimize your custom operator while keeping an eye out for common pitfalls. |
| [Providing a custom sort order](xref:GQI_Redirect_Sort_Tutorial) | Implement a custom GQI column sort order using a custom operator. |
| [Forwarding dummy data to the GQI](xref:Ad_hoc_Tutorials) | Go through an example script that forwards dummy data to the GQI. |
| [Building a GQI data source that fetches satellites](xref:Ad_hoc_Tutorials_Satellites) | Go through an example script that forwards satellites data to the GQI. |
| [Creating a parameter table connected to an element feed](xref:Creating_a_parameter_table_connected_to_an_element_feed) | Create a parameter table connected to an element feed. |
| [Building a GQI data source that retrieves data from a DMS](xref:Ad_hoc_Tutorials_GQIDMS) | Create an ad hoc data source to retrieve data from your DMS. |
| [Scaling an ad hoc data source](xref:Ad_hoc_Tutorials_Scalable) | An example of how to build a highly scalable data source capable of serving many concurrent users. |
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---
uid: Ad_hoc_Tutorials
uid: Forwarding_dummy_data_to_GQI
---

# Forwarding dummy data to the GQI
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---
uid: Ad_hoc_Tutorials_Scalable
uid: Scaling_Ad_hoc_Data_Source
---

# Scaling an ad hoc data source

Each time a query is executed, a new instance of the data source is created. This makes scalability crucial, especially when building the underlying data source is time-consuming or resource-intensive. Keep in mind that the code you're writing could be executed concurrently by many users.
Each time a query is executed, a new instance of the data source is created. This makes scalability crucial, especially when building the underlying data source is time-consuming or resource-intensive. Keep in mind that the code you are writing could be executed concurrently by many users.

To optimize performance when real-time data isn't required, implement caching where appropriate, using a static cache. When querying data through the DMS interface, ensure that data is stored on a security group basis.
To optimize performance when real-time data is not required, implement caching where appropriate, using a static cache. When querying data through the DMS interface, ensure that data is stored on a security group basis.

Be aware that multithreading affects both the static cache object and the cache itself. Use consistent locking mechanisms during heavy operations to prevent multiple costly computations from running simultaneously.

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Expand Up @@ -24,7 +24,7 @@ To use an ad hoc data source in a query:
1. Above the class, add the *GQIMetaData* attribute in order to configure the name of the data source as displayed in the Dashboards app.

For example (see [Example ad hoc data script](xref:Ad_hoc_Tutorials) for a full example):
For example (see [Example ad hoc data script](xref:Forwarding_dummy_data_to_GQI) for a full example):

```csharp
using Skyline.DataMiner.Analytics.GenericInterface;
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Expand Up @@ -9,6 +9,7 @@ When developing a GQI extension, keep the following in mind:
- [Use DIS to create and publish extensions](#use-dis-to-create-and-publish-extensions)
- [Do not use Skyline.DataMiner.Automation](#do-not-use-skylinedataminerautomation)
- [Only use 64-bit assembly references](#only-use-64-bit-assembly-references)
- [Make your ad hoc data source scalable](#make-your-ad-hoc-data-source-scalable)

## Use DIS to create and publish extensions

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## Make your ad hoc data source scalable

Each time a query is executed, a new instance of the data source is created. This makes scalability crucial, especially when building the underlying data source is time-consuming or resource-intensive. Keep in mind that the code you're writing could be executed concurrently by many users.
Each time a query is executed, a new instance of the data source is created. This makes scalability crucial, especially when building the underlying data source is time-consuming or resource-intensive. Keep in mind that the code you are writing could be executed concurrently by many users.

An example of how to build a highly scalable data source capable of serving many concurrent users: [Scaling an ad hoc data source](xref:Ad_hoc_Tutorials_Scalable).
> [!TIP]
> For an example of how to build a highly scalable data source capable of serving many concurrent users, see [Scaling an ad hoc data source](xref:Scaling_Ad_hoc_Data_Source).
10 changes: 6 additions & 4 deletions user-guide/Advanced_Modules/toc.yml
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topicUid: Ad_hoc_Life_cycle
- name: Linking rows to DataMiner objects
topicUid: Ad_hoc_Metadata
- name: Tutorials
- name: Examples
items:
- name: Forwarding dummy data to the GQI
topicUid: Ad_hoc_Tutorials
topicUid: Forwarding_dummy_data_to_GQI
- name: Scaling an ad hoc data source
topicUid: Scaling_Ad_hoc_Data_Source
- name: Tutorials
items:
- name: Building a GQI data source that fetches satellites
topicUid: Ad_hoc_Tutorials_Satellites
- name: Building a GQI data source that retrieves data from a DMS
topicUid: Ad_hoc_Tutorials_GQIDMS
- name: Scaling an ad hoc data source
topicUid: Ad_hoc_Tutorials_Scalable
- name: Configuring a custom operator
topicUid: GQI_Custom_Operator
items:
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