In SharePoint applications, working with large amounts of data can lead to slow performance due to multiple HTTP requests being sent to the server. Each request involves network overhead, which can significantly impact the application's speed.
When interacting with SharePoint or Microsoft 365 via REST APIs or PnPjs, making individual requests for each operation can be inefficient, especially when multiple operations need to be performed in parallel.
To address this issue, SharePoint provides a feature called Batching. This allows multiple requests to be grouped into a single HTTP request, reducing network overhead and improving performance. In this section, we'll discuss batching in detail, with an example and its limitations.
What is Batching?
Batching in PnP (Pattern and Practice) is often used in the context of SharePoint and Microsoft 365 development, particularly when working with the SharePoint REST API or the PnPjs library.
It is a technique that allows you to combine multiple operations into a single HTTP request. This reduces the number of network calls, which improves the responsiveness of your application.
Where possible, batching can significantly improve application performance by combining multiple requests to the server into a single request. This is especially useful when first establishing state, but applies to any scenario where you need to make multiple requests before loading or based on a user action.
Batching is supported within the SP and graph libraries as shown below.
How to Implement Batching in PnPjs
In PnPjs, you can create a batch and then add various operations to that batch. Once the batch is ready, you execute it with a single API call.
Setting Up PnPjs
Make sure you have PnPjs installed in your project:
npm install @pnp/sp @pnp/logging @pnp/odata
Batching Example in PnPjs
Explain how to create and execute a batch in PnPjs. Example code:
import { sp } from "@pnp/sp/presets/all";
import "@pnp/sp/items";
// Create a batch object
let batch = sp.createBatch();
// Adding multiple operations to the batch
// Operation 1: Add an item to another list
let addItemRequest = sp.web.lists.getByTitle("List1").items.add({
Title: "Demo 1",
Status: "Testing"
});
// Operation 2: Update an item in the "Documents" list
let updateItemRequest = sp.web.lists.getByTitle("List2").items.getById(1).update({
Title: "Updated Document"
});
// Add these requests to the batch
getItemsRequest.inBatch(batch);
addItemRequest.inBatch(batch);
updateItemRequest.inBatch(batch);
// Execute the batch
batch.execute().then(([getItemsResult, addItemResult, updateItemResult]) => {
console.log("item is created:", addItemResult);
console.log("Document updated:", updateItemResult);
}).catch((error) => {
console.error("Batch operation failed:", error);
});
Best Practices for Batching
Limit the Number of Operations
SharePoint's REST API limits the number of operations per batch to 50. If you need more, break the batch into smaller chunks.
Error Handling
Handle errors in the response appropriately. If any operation fails in the batch, you’ll need to check the individual response for that operation.
Keep Operations Independent
While batching, make sure the operations are independent of each other. If an operation depends on the result of another, batching may not be ideal.
Monitor Batch Size
Monitor your batch size to avoid exceeding the limits (50 operations), as SharePoint might throw an error for a large batch.
Limitations of Batching
Timeouts
Large batches might cause timeouts, especially in slower environments or if you're performing complex operations. It's best to break large operations into smaller batches.
API Rate Limits
SharePoint’s REST API has rate limits. Batching helps, but you should still be mindful of how many requests you're making in a short time.
Request Size
If your batch contains a large amount of data, it might slow down the request or even fail.
Conclusion
Batching in PnPjs is a simple yet powerful technique to improve performance when working with SharePoint by combining multiple API calls into a single HTTP request. It reduces network overhead, speeds up execution, and helps manage API limits effectively. While it comes with some limitations, like batch size and error handling, it's an essential tool for building efficient, scalable SharePoint solutions.