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Hashed Indexes

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  • Use Cases
  • Behavior
  • Floating-Point Numbers
  • Limitations
  • Get Started
  • Details
  • Hashing Function
  • Embedded Documents
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Hashed indexes collect and store hashes of the values of the indexed field.

Hashed indexes support sharding using hashed shard keys. Hashed based sharding uses a hashed index of a field as the shard key to partition data across your sharded cluster.

Using a hashed shard key to shard a collection results in a more even distribution of data between shards compared to ranged sharding.

If your shard key monotonically increases, using a hashed index as the shard key evenly distributes data between shards, as opposed to writing data to the shard with an upper bound of maxKey.

Common examples of monotonically increasing shard keys are timestamps and ObjectId values.

Hashed indexes truncate floating-point numbers to 64-bit integers before hashing. For example, a hashed index uses the same hash to store the values 2.3, 2.2, and 2.9. This is a collision, where multiple values are assigned to a single hash key. Collisions may negatively impact query performance.

To prevent collisions, do not use a hashed index for floating-point numbers that cannot be reliably converted to 64-bit integers and then back to floating point.

Hashed indexes do not support floating-point numbers larger than 2 53.

Hashed indexes have limitations for array fields and the unique property.

The hashing function does not support multi-key indexes. You cannot create a hashed index on a field that contains an array or insert an array into a hashed indexed field.

You cannot specify a unique constraint on a hashed index. Instead, you can create an additional non-hashed index with the unique constraint. MongoDB can use that non-hashed index to enforce uniqueness on the chosen field.

To create a hashed index, see Create a Hashed Index.

This section describes technical details for hashed indexes.


When MongoDB uses a hashed index to resolve a query, it uses a hashing function to automatically compute the hash values. Applications do not need to compute hashes.

To see what the hashed value would be for a key, use the convertShardKeyToHashed() method. This method uses the same hashing function as the hashed index.

The hashing function collapses embedded documents and computes the hash for the entire value.

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