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Description

Error 4, 'No Such Key', indicates that a requested field or key does not exist within the specified document or object in MongoDB. This typically occurs when an operation attempts to access, update, or project a field that is absent from the target data structure.

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Error Message

No Such Key

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Known Causes

4 known causes

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Typo in Field Name

A common cause is a simple misspelling or incorrect casing of the field name in a query, update, or projection statement.

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Missing Field in Document

The specified field genuinely does not exist in the document(s) being operated on, perhaps due to schema evolution or data inconsistencies.

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Incorrect Projection/Aggregation

An aggregation pipeline stage or projection is attempting to reference a field that isn't available in the current document stream or has been renamed upstream.

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Data Inconsistency

Documents within a collection might have varying schemas, and the targeted field exists only in a subset of the documents, leading to this error for others.

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Solutions

3 solutions available

1. Inspect and Correct Document Structure easy

Directly address the missing field by updating the document.

1

Identify the document causing the error. This often involves examining the logs or the specific query that failed. You'll need to know the collection and the `_id` of the document.

2

Connect to your MongoDB instance using the MongoDB Shell (`mongosh`).

mongosh

3

Switch to the correct database.

use your_database_name

4

Update the problematic document to include the missing field. Replace `your_collection_name`, `your_document_id`, and `missing_field_name` with your specific values. If the field should be null, provide `null`.

db.your_collection_name.updateOne( { _id: ObjectId("your_document_id") }, { $set: { missing_field_name: "some_value" } } )

5

Verify the update by fetching the document.

db.your_collection_name.findOne({ _id: ObjectId("your_document_id") })

2. Modify Application Logic to Handle Missing Fields medium

Adjust your application code to gracefully handle the absence of expected fields.

1

Review the application code that interacts with the MongoDB collection where the error occurs. Identify the specific queries or operations that are failing.

2

In your application's data retrieval logic, implement checks to see if the expected field exists. If it doesn't, provide a default value or handle it appropriately. The exact implementation will depend on your programming language and MongoDB driver.

Example in Node.js using Mongoose:

const document = await YourModel.findById(documentId);
const value = document.missing_field_name || "default_value";
// or
const value = document.get('missing_field_name', 'default_value');

3

Consider using MongoDB's `$ifNull` aggregation operator if you are performing complex queries or aggregations where you need to provide a default value for a missing field within the query itself.

Example aggregation query:

db.your_collection_name.aggregate([
  {
    $project: {
      _id: 0,
      existing_field: 1,
      missing_field_with_default: { $ifNull: ["$missing_field_name", "default_value"] }
    }
  }
])

3. Schema Validation for Data Integrity advanced

Enforce a consistent document structure to prevent future occurrences.

1

Define a schema validation rule for your collection using MongoDB's schema validation feature. This will ensure that all documents inserted or updated adhere to the defined structure.

db.createCollection("your_collection_name", {
   validator: {
      $jsonSchema: {
         bsonType: "object",
         required: [ "existing_field", "missing_field_name" ],
         properties: {
            existing_field: {
               bsonType: "string",
               description: "must be a string and is required"
            },
            missing_field_name: {
               bsonType: ["string", "null"], 
               description: "must be a string or null"
            }
         }
      }
   }
})

2

If the collection already exists, you can add the validator to it.

db.runCommand({ collMod: "your_collection_name", validator: {
   $jsonSchema: {
      bsonType: "object",
      required: [ "existing_field", "missing_field_name" ],
      properties: {
         existing_field: {
            bsonType: "string",
            description: "must be a string and is required"
         },
         missing_field_name: {
            bsonType: ["string", "null"], 
            description: "must be a string or null"
         }
      }
   }
}})

3

After applying schema validation, any attempt to insert or update a document that violates the schema (e.g., omits a required field) will result in a validation error, preventing the problematic data from entering the database.

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Related Errors

5 related errors

MongoDB Error 4: Missing Document Field