Client-Side Vs. Server-Side Options For Sharepoint List Limits
What is the List View Threshold?
The list view threshold in SharePoint refers to the maximum number of items that can be displayed in a list view before performance starts to degrade. By default, SharePoint limits list views to 5,000 items to maintain optimal performance. When the number of items in a list view exceeds this threshold, users will no longer be able to view all items in the list or filter and sort the data as expected. This can significantly impact usability and accessibility of large SharePoint lists.
The list view threshold exists because displaying extremely large datasets requires significant server and database resource utilization. As more data needs to be handled by the SharePoint architecture with each request, performance suffers from processing overhead, extended load times, and potential timeout errors. Establishing a threshold prevents resource overutilization and allows SharePoint environments to remain performant.
Client-Side Solutions
Client-side solutions shift the responsibility of managing and displaying list data from the server to the user’s web browser. This avoids threshold limitations and can improve performance for specific use cases. Popular techniques involve utilizing indexed columns, implementing client-side data manipulation with JavaScript, and client-side data rendering.
Using Indexed Columns to Improve Performance
Indexed columns allow users to filter large lists more efficiently by rapidly searching indexed data instead of performing calculations across entire datasets. SharePoint creates indices during crawl operations for columns specified in search schema. Indexed columns can dramatically improve limiting filter performance for large lists without necessitating changes to view thresholds.
For example, consider a document library containing 100,000 items. Filtering this large list by content type may require significant server compute time even if the number of matches falls within view thresholds. However, filtering by an indexed managed property column can utilize pre-calculated search indices to return matches in milliseconds.
Implementing Client-Side Data Manipulation with JavaScript
Custom JavaScript embedded in SharePoint pages can retrieve, filter, sort, and render list data directly within the browser instead of relying on server-side processing and thresholds. This client-side approach reduces the amount of data transferred from server and can handle much larger result sets without list view governance limitations.
A common client-side technique loads all list data in chunks using the SharePoint REST API, processes and stores the data in browser memory using JavaScript, then dynamically renders UI elements to display a manageable subset. Additional data can be seamlessly appended from the client-side cache as the user scrolls, enabling smooth paging of 100,000+ records from a single huge dataset.
Example Code for Client-Side Rendering
```js
// Helper method to load list data in batches
const getListData = () => {
// SharePoint REST API endpoint
const url = `/_api/web/lists/getbytitle('ListName')/items`;
let data = [];
// Retrieve list items in batches
return fetch(url)
.then(response => response.json())
.then(responseData => {
// Concatenate batch results
data = data.concat(responseData.value);
// Recursively call for next batch
if (responseData.__next) {
return getListData(url + responseData.__next);
}
// Return all data when finished
return data;
});
}
getListData()
.then(fullDataset => {
// Local data manipulation
let filteredData = fullDataset.filter(item => {
return item.Status == 'Complete';
});
// Render to DOM
const ul = document.getElementById('listData');
filteredData.forEach(item => {
let li = document.createElement('li');
li.textContent = item.Title;
ul.appendChild(li);
});
})
.catch(err => { console.log(err); });
```
Server-Side Options
Increasing list view thresholds, enabling large query support, configuring PerformancePoint Services, and leveraging the SharePoint REST API all provide server-side methods for overcoming default limit constraints. While client-side solutions may be preferable for specific lightweight scenarios, enterprise solutions typically warrant robust server-side implementations.
Increasing List View Threshold through Central Admin
SharePoint Central Administration provides a configuration option to increase the list view threshold up to 20,000 items for the entire farm or individual site collections. This can improve usability of large lists but may degrade performance at scale.
Farm administrators should carefully test configurations in staging environments before rolling out to production. Incrementally adjusting thresholds while monitoring resource utilization and load times will determine optimal settings.
Enabling Large Queries with PowerShell
SharePoint’s Large Query feature allows admins to selectively remove list view thresholds for designated site collections via PowerShell. This bypasses hard-coded governance and fully loads query results regardless of size. Large queries utilize resource-intensive dynamic filters and should be enabled judiciously.
```PowerShell # Set large query for site collection Set-SPSite http://siteCollectionUrl -LargeListsEnabled $true ```
Implementing PerformancePoint Services
For business intelligence solutions displaying extremely large datasets in SharePoint, PerformancePoint Services can visualize dashboard renderings bypassing standard thresholds. Integration with SQL Server Analysis Services and PowerPivot data models provides robust enterprise capabilities.
While PerformancePoint overcomes restrictions, improperly configured data connections, dimensional model design, or suboptimal dashboard architecture can still inhibit performance at scale or overburden resources.
Custom Server-Side Data Access with REST API
For advanced scenarios or fully custom applications, SharePoint’s REST API exposes direct access to list data for raw CRUD operations and queries. Developers can interact server-to-server with the API to pull list information into external data stores for customized processing.
Retrieving large volumes of SharePoint data through the REST endpoints before manipulating externally avoids threshold limitations. Results can be queried, filtered, and sorted with optimized data engines like SQL Server before re-integration.
Hybrid Approaches
Combining complementary client-side and server-side techniques creates hybrid solutions for optimal large list performance. Caching data locally while spreading resource utilization across layers increases efficiency and stability at scale.
Combining Client and Server Techniques
A hybrid approach might leverage PowerShell and PerformancePoint for optimized server querying, then implement client-side rendering for last mile processing. This balances processing to prevent overloading any single component while delivering performant experiences.
Caching Data Client-Side
Client-side data caching provides low latency responses to repeat requests by retaining queried information locally for reuse. JavaScript stores frequently accessed data in browser sessions, avoiding redundant server round trips.
For example, when paging through catalog items, cached dataset filters could display the next item page instantly from memory rather than requerying the entire catalog contents from the database.
Partitioning Data with Folders
Organizing extremely large lists into logical folder partitions splits data vertically into separate containers with independent thresholds. This structure circumvents single list caps while maintaining usability.
Folders inherit security simultaneously, so governance remains consistent. PowerShell automation can expedite migrations from flat structures when partitioning existing large lists.
Conclusion
Key Takeaways and Recommendations
When approaching SharePoint list view limits, client-side solutions focusing on browser processing may sufficiently overcome thresholds in specific lightweight scenarios. However, most robust enterprise solutions will leverage server-side configuration adjustments, custom data access, or coupled Power BI integrations.
Carefully testing adjustments to validate performance and resource constraints before deploying changes or upgrades prevents unexpected limitations. Monitoring utilization with tools like Resource Monitors allows administrators to fine tune for optimal throughput.
As requirements expand from departmental collaboration to organization-wide Access needs at enterprise scale, only platform-level enhancements with finely tuned components can reliably deliver performant, available solutions while safeguarding stability.
