PyMongo CursorNotFound error: Cursor not found/valid at server

The Problem

The CursorNotFound error in PyMongo represents situations where a cursor, an essential part of MongoDB’s functionality for traversing through query results, becomes invalid or is no longer available on the server. This can lead to unexpected halts in your application, preventing you from accessing your query results beyond a certain point. Understanding why this error occurs and how to fix it is crucial for maintaining the efficiency and reliability of your database operations.

Common Reasons

• Timeout: MongoDB cursors have a default inactivity timeout of 10 minutes. If your application does not fetch the next batch of results within this time, the cursor is automatically closed by MongoDB.
• Resource Constraints: On high-load systems, cursors might be prematurely closed by the server to free up resources.

Solution 1: Increase Cursor Timeout

Modifying the cursor’s timeout value can prevent the cursor from closing too early due to inactivity.

This approach involves changing the default server-side timeout for cursors. It’s particularly useful for operations requiring long processing times per document.

Steps:

1. Establish a connection to your MongoDB instance using PyMongo.
2. Use the find method with the no_cursor_timeout=True option to prevent the cursor from timing out.
3. Remember to close the cursor manually using .close() when done.

Code Example:

from pymongo import MongoClient

client = MongoClient('mongodb_uri')
collection = client.db.collection

# Enable no_cursor_timeout
cursor = collection.find({}, no_cursor_timeout=True)
for document in cursor:
    print(document)

cursor.close() # Remember to close it manually

Note: This solution alleviates the issue of timeout but mandates careful management of cursors to prevent memory leaks.

Solution 2: Batch Processing

Processing results in batches helps manage large datasets without hitting cursor timeouts.

Fetching documents in smaller batches can reduce the load on both the application and the database, making it a practical approach for handling extensive datasets.

Steps to Implement:

1. Query the database with find and set a reasonable batch_size.
2. Iterate through the cursor to process documents in batches.

Code Example:

from pymongo import MongoClient

client = MongoClient('mongodb_uri')
collection = client.db.collection

cursor = collection.find().batch_size(50)
for document in cursor:
    print(document)

Note: While this approach reduces immediate load and avoids timeouts, it may still encounter limits with massive datasets or under heavy system load conditions.

Conclusion

The CursorNotFound error can significantly disrupt database operations, but with the right strategies, it’s manageable. Assessing the specific needs of your application and wisely choosing between increasing cursor timeout and batch processing—or a combination of both—can effectively mitigate this issue.