Question: Why is MongoDB distinct slow?


MongoDB's distinct operation can be slow for several reasons. Understanding these can help in optimizing queries and improving database performance.

Large Datasets

When applied to a large dataset, the distinct operation may take considerable time because it scans through all documents to find unique values of the specified field. This is particularly slow if the field has a high cardinality (i.e., many unique values).

Lack of Indexes

If the field on which distinct is used is not indexed, MongoDB must perform a full collection scan to retrieve the unique values. Creating an index on this field can significantly speed up the operation.


db.collection.createIndex({ fieldName: 1 });

Working Set Size vs. RAM

If the working set size (the data and indexes that the database accesses most frequently) exceeds the available RAM, MongoDB will have to read from disk more often, slowing down the operation. Ensuring your working set fits into RAM can improve performance.

Read Locks

MongoDB uses a read lock while performing the distinct operation, preventing write operations on the same collection until it completes. This can lead to performance issues in highly concurrent environments.

Optimization Strategies

  • Use Indexes: Ensure the field you are using with distinct is indexed.
  • Project Only Necessary Fields: When possible, limit the fields returned by the query using projection to reduce the amount of data MongoDB has to process.
  • Consider Aggregation Framework: In some cases, using the aggregation framework with $group stage might offer better performance than distinct, especially if you can leverage indexes or if additional filtering/aggregation is needed.

Example Using Aggregation Framework:

db.collection.aggregate([ { $match: { /* your query filter */ } }, { $group: { _id: '$fieldName' } } ]);

By understanding the factors that influence the performance of the distinct operation and applying appropriate optimizations, it's possible to mitigate its slowness in MongoDB.

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