Introduction to MongoDB cursor.explain() Method

The cursor.explain() method in MongoDB is a tool used to explain the query plan, which can help developers view how MongoDB executes queries and optimize query performance.

Syntax

The cursor.explain() method can be called after aggregation pipelines, find, findOne, and other query operations in MongoDB. The syntax is as follows:

db.collection.find().explain()

Use Cases

Using the cursor.explain() method can help developers analyze performance issues with queries by viewing query plans, index usage, number of scanned documents, and other information, finding potential performance bottlenecks, and optimizing them.

Example

Assume that we have a collection named users, which contains the following documents:

{ "_id" : ObjectId("6156f5a5c5e6d5e6f5d6a852"), "name" : "Alice", "age" : 28 }
{ "_id" : ObjectId("6156f5b5c5e6d5e6f5d6a853"), "name" : "Bob", "age" : 35 }
{ "_id" : ObjectId("6156f5c5c5e6d5e6f5d6a854"), "name" : "Charlie", "age" : 42 }

We can use the cursor.explain() method to view the query plan:

db.users.find({ age: { $gt: 30 } }).explain()

After running the above command, we get the following query plan:

{
  "queryPlanner": {
    "plannerVersion": 1,
    "namespace": "test.users",
    "indexFilterSet": false,
    "parsedQuery": {
      "age": {
        "$gt": 30
      }
    },
    "winningPlan": {
      "stage": "COLLSCAN",
      "filter": {
        "age": {
          "$gt": 30
        }
      },
      "direction": "forward"
    },
    "rejectedPlans": []
  },
  "serverInfo": {
    "host": "localhost",
    "port": 27017,
    "version": "4.4.5",
    "gitVersion": "ff5cb77101b052fa02da43b8538093486cf9b3f7"
  },
  "ok": 1
}

We can see that MongoDB used a COLLSCAN (collection scan) approach to execute the query and did not use an index for optimization, which could lead to query performance issues. We can optimize query performance by creating appropriate indexes.

Conclusion

The cursor.explain() method can help developers gain a deeper understanding of MongoDB’s query execution process, discover performance issues by viewing query plans, index usage, and other information, and optimize performance accordingly.