Optimizing fetch performance in Entity Lists

When working with Entity Lists in Power Pages (Power Apps portals), fetching data efficiently is crucial for ensuring that the user experience remains smooth, especially when dealing with large volumes of data. Optimizing the performance of these fetches can significantly reduce load times, improve responsiveness, and provide a better overall experience.

Here are some strategies for optimizing FetchXML performance in Entity Lists:

1. Use FetchXML Views and Predefined Filters

One of the most effective ways to improve fetch performance is to leverage FetchXML views and predefined filters. Rather than writing custom FetchXML queries on the fly, use views in Dataverse (or Dynamics 365) that are already optimized and indexed. This allows Power Pages to retrieve data faster and reduce the load on the server.

Predefined filters can be applied in views to only pull the relevant records.
FetchXML queries benefit from leveraging these optimized queries to limit data retrieval to only what’s necessary.

Example: Using a Predefined View in FetchXML

<fetch>
  <entity name="contact">
    <attribute name="firstname" />
    <attribute name="lastname" />
    <filter>
      <condition attribute="statecode" operator="eq" value="0" />
    </filter>
    <order attribute="lastname" />
  </entity>
</fetch>

Here, the query is limited to the contacts that are active (statecode = 0), which reduces the result set and improves performance.

2. Limit the Number of Records

One of the easiest ways to enhance performance is by limiting the number of records returned in the query. Power Pages supports paging, which allows you to fetch and display a limited number of records at a time, reducing the impact on performance.

Use the top parameter to restrict the number of records returned.
Enable pagination to display results across multiple pages rather than pulling all data at once.

Example: Fetching a Limited Number of Records

<fetch top="50">
  <entity name="contact">
    <attribute name="firstname" />
    <attribute name="lastname" />
  </entity>
</fetch>

This query retrieves only the top 50 records, which can improve load times compared to fetching all records.

3. Apply Proper Indexing

For faster data retrieval, ensure that the Dataverse tables (or entities) you are querying have proper indexing. Use indexed attributes in filters, as this improves the speed of query execution.

Attributes that are frequently used in filtering or sorting should be indexed.
Check the entity metadata to identify which attributes are indexed for efficient querying.

Example: Querying on Indexed Attributes

<fetch>
  <entity name="contact">
    <attribute name="firstname" />
    <attribute name="lastname" />
    <filter>
      <condition attribute="emailaddress1" operator="eq" value="example@domain.com" />
    </filter>
  </entity>
</fetch>

In this example, emailaddress1 is typically indexed by default in Dataverse, allowing for faster lookups.

4. Use Server-Side Filtering When Possible

Wherever feasible, use server-side filtering as opposed to client-side filtering. This helps offload work from the client and ensures that only the necessary data is sent from the server.

In Power Pages, you can set filters on Entity Lists to apply on the server-side. This reduces the amount of data transferred to the browser.

5. Avoid Complex Joins and Nested Queries

Complex joins and nested queries can severely degrade performance. FetchXML supports relationships, but over-complicating the query with many relationships or complex filters can slow down the performance.

Minimize the use of linked entities or complex joins.
Simplify the relationships in FetchXML queries to ensure faster execution.

Example: Avoiding Complex Joins

Instead of querying multiple entities in one go, break down the logic into separate calls, or retrieve data from related entities in smaller, more manageable chunks.

6. Implement Caching Strategies

Caching can significantly reduce the load on the server and speed up data retrieval. Implement a caching mechanism for frequently accessed data in your Entity Lists.

Use browser caching to store data that doesn’t change often, so subsequent visits to the page don’t require fetching the data from the server again.
Utilize server-side caching or Content Delivery Networks (CDNs) to cache large data responses, particularly for static resources.

7. Optimize Views in Dataverse

Before querying data in your Entity List, optimize the views in Dataverse for better performance.

Only display relevant columns in your views to minimize the data load.
Remove any unnecessary columns and ensure that only the required attributes are included in the view.

This ensures that the Entity List fetches only the relevant columns, reducing data payload and improving performance.

8. Batch Requests for Multiple Queries

If your Entity List requires multiple FetchXML queries (e.g., for different sections or parts of the data), consider batching multiple requests into a single call. This can improve performance by reducing the number of individual requests.

Power Pages can handle batch requests, and this can help optimize the overall fetching process when dealing with multiple data sources.

9. Asynchronous Data Fetching

For some scenarios, consider using asynchronous fetching to prevent blocking the UI thread. This allows the user interface to remain responsive while waiting for data from the server.

By fetching data in the background, you can ensure that the page content is loaded first, and then populate the data dynamically after it’s ready.

10. Optimize FetchXML Queries for Complex Data

For more complex data fetching scenarios (like retrieving large datasets or working with many records), consider optimizing your FetchXML queries using techniques like:

Using aggregate functions (e.g., count, sum, avg) to reduce data size.
Specifying only the required attributes in the <attribute> tag rather than fetching all attributes.

Example: Fetching Only Required Attributes

<fetch>
  <entity name="contact">
    <attribute name="firstname" />
    <attribute name="lastname" />
    <attribute name="emailaddress1" />
  </entity>
</fetch>

This query only fetches the necessary attributes, reducing the payload size.